Students' Attitudes and Intentions of Using Technology Such As Virtual

Students’ Attitudes and Intentions of Using Technology such as Virtual Reality for

Learning about Climate Change and Protecting Endangered Environments

A dissertation presented to

the faculty of

The Gladys W. and David H. Patton College of Education of Ohio University

In partial fulfillment

of the requirements for the degree

Doctor of Philosophy

Kristina Adanin

December 2020

This dissertation titled

Students’ Attitudes and Intentions of Using Technology such as Virtual Reality for

Learning about Climate Change and Protecting Endangered Environments

KRISTINA ADANIN

has been approved for

Educational Studies

and The Gladys W. and David H. Patton College of Education by

Greg Kessler

Professor of Educational studies

Renée A. Middleton

Dean, The Gladys W. and David H. Patton College of Education 3

Abstract

ADANIN KRISTINA, Ph.D., December 2020, Educational Studies

Students’ Attitudes and Intentions of Using Technology such as Virtual Reality for

Learning about Climate Change and Protecting Endangered Environments

Director of Dissertation: Greg Kessler

At a time when the world is facing a range of significant challenges, including a rise in air temperature, rapidly evolving droughts in some areas, and floods, a new technology in education can help inform people of current issues that may not be close to them but, nevertheless, can have a significant impact in the future. Our planet has been warming steadily for over a century, and the preponderance of evidence has pointed at human action as the main contributor to the change (Hansen et al., 2010). The evolution of technology has brought tremendous change. Virtual Reality (VR), 360-degree video, has the potential to bring the environment to the students since it can provide a close to real-life situation.

The use of VR for educational purposes has been quite unknown to most school systems. There are many gaps that need to be investigated prior to the effective implementation of VR-learning, such as the factors that influence students’ intention to use it. This study fulfilled some of these gaps by focusing on the potential of using VR for future education and raising awareness of the climate change occurring in remote areas, specifically tropical regions. The findings of this study will hopefully encourage students to play a more responsible role in the development and implementation of VR education worldwide and help enhance the academic quality of courses for instructors 4 and students. This study examined students’ behavioral intentions towards using VR in their learning about climate change utilizing the Technology Acceptance Model of Davis

(1989), combined with the spatial presence experience scale (Hartmann et al., 2015).

Phase 1 was created in order to understand students’ salient beliefs about the use of VR for educational purposes and learning about climate change. Furthermore, 65 students participated in this phase and reported that VR can be beneficial for educational purposes to learn about global climate change, and 95.2% of participants fully agreed.

Phase 2 occurred among 227 students from around the globe. The Phase 2 study was manipulated because students chose their own technology devices to watch the VR content about the last tropical glaciers, thereby making it a pseudo-experimental study.

Six variables were used to explain students’ intention of using VR: attitude toward use, perceived usefulness, self-location, perceived ease of use, possible action and behavioral intention. The best predictor of intention to use VR was perceived usefulness. On the other hand, after doing a confirmatory factor analysis (CFA), the spatial presence variables were modified, which improved the model. A path analysis was conducted in order to define the relationship between the variables. The path coefficient from perceived usefulness to behavioral intention had the strongest regression weight, while from perceived ease of use to attitude toward use had the lowest regression weight. The structural equation model (SEM) indicated that the best model excluded factors, such as attitude toward use, and combined possible action and self-location as one factor. This study only included students as participants. Future studies including instructors could bring a new perspective for using VR in education to learn about climate change. 5

Dedication

Vse je to Pot…

Acknowledgments

On this expedition, I was lucky to have a badass committee (See Appendix E for the meaning of the word). I can say this expedition would not be successful without my advisor, Dr. Greg Kessler, as well as my supervisor, Dr. Gordon Brooks. Dr. Alan Wu showed me how education can be better with the use of new technologies, and Brian

Plow taught me how much storytelling plays an important role. Dr. Bob West helped me to put my thoughts on paper. He was with me from the first page to the last, even for this section, too.

Let me start from the beginning. When I quit working on my undergraduate studies, Dr. Sretenka Dugalić did not give up on me. She pushed me to finish my undergraduate degree and gave me hope that education is the key.

I need to apologize to my family because I stressed them every day, sharing with them my ideas and projects that were difficult to follow. I want to thank my brothers,

Goran Kovačević and Boris Toljaga, and their families, for supporting me all these years and taking care of Mira. I wish I could share my degree with my husband, Miha, because he deserves this as much as I do. I hope he will soon have the opportunity to do his own doctoral degree.

Two people that have had the biggest influence on me to go farther in academia and in doing what I want to do were Rob Warner (soon to be a doctor) and Dr. Heïdi

Sevestre. Guys, when I grow up, I want to be like you two, also badass!

Kristin Diki, Elizarni, Andrew Wild and Preeti Patil, we can move the mountain together, and I hope our roads will cross again soon! Life without telenovela is boring! 7

Dr. Jorge Ceballos, thank you for taking us to Nevado Santa Isabel and been a real protector of tropical glaciers. This project would never be done without your expertise and help in Colombia.

Thank you to the GRID lab and Terrance Reimer for helping me with all of the equipment that I used on the expedition. Terrance, I can’t thank you enough for all of your help with editing the video. Don, Lisa and Beth, you were the best bosses that a student could have.

Table of Contents

Page

Abstract ...... 3 Dedication ...... 5 Acknowledgments ...... 6 List of Tables...... 11 List of Figures ...... 12 Chapter 1: Introduction ...... 13 Rationale ...... 14 Research Questions ...... 23 Significance of Study ...... 23 Researcher Assumptions ...... 25 Organization of Dissertation ...... 26 Chapter 2: Literature Review ...... 28 VR and Educational Technology ...... 28 Virtual Reality ...... 33 VR and Diversely Abled Populations ...... 37 Storytelling ...... 38 Storytelling as Tool for Advocacy ...... 41 Digital Storytelling ...... 45 VR and Storytelling ...... 46 Environmental Interpretation ...... 47 VR as a Safe Learning Experience ...... 49 Distance Transformative and Adventure Education ...... 52 Climate Change and Education ...... 53 Tropical Glaciers ...... 54 Effects of Climate Change on Tropical Glaciers ...... 56 The Role of Education on Climate Change ...... 57 Theoretical Framework ...... 61 Technology Acceptance Model ...... 62 Spatial Presence ...... 68 Chapter 3: Methodology ...... 74 9

Research Questions and Hypotheses ...... 76 Population ...... 78 Instrumentation and Measures ...... 80 Phase 1 – Elicitation Study ...... 81 Phase 2 – Final Study ...... 83 Ethical Protection of Research Participants ...... 84 Data Analysis ...... 87 Techniques for Ensuring Reliable and Valid Data ...... 89 Internal Consistency Reliability ...... 90 Validity ...... 91 Chapter 4 ...... 93 Phase 1 – Elicitation Study ...... 94 Data Collection and Response Rate for Phase 1 ...... 94 Phase 1 Analysis ...... 95 Question 1: Do Students Think the Use of Technology as Virtual Reality will Impact Students’ Learning Outcomes Related to Climate Change and Tropical Glaciers? ...... 96 Phase 2 – Final Study ...... 107 Descriptive Statistics ...... 107 Test of Reliability and Validity ...... 111 Exploratory Factor Analysis ...... 114 Confirmatory Factor Analysis ...... 114 First Model - The Hypothesized Model ...... 115 Question 2: Do College Students Intend to Use Virtual Reality Applications for their Future Learning and Understanding the Climate Change at the Tropical Region ...... 121 Path Analysis ...... 126 Question 3: Does the VRTAM Model Predict Intention to use Virtual Reality among College Students? ...... 129 Supplemental Analysis ...... 138 Summary ...... 141 Chapter 5 ...... 144 Summary of the Study ...... 145 Purpose Statement ...... 149 10

Review of the Methodology ...... 149 Major Findings ...... 150 Phase 1 & Overview of Research Question 1...... 150 Phase 2 & Overview of Research Questions 2 and 3 ...... 152 Practical and Theoretical Implications...... 155 The Challenge of VR Design for Education...... 157 Limitations ...... 159 Recommendations for Future Research ...... 160 Conclusion ...... 161 References ...... 163 Appendix A: Phase 1 Elicitation Study ...... 194 Appendix B: Phase 2 Final Study...... 196 Appendix C: Approval for the use of SPES questioner ...... 198 Appendix D: Storyboard ...... 199 Appendix E: Meaning “badass” ...... 200

List of Tables

Page

Table 1 Salient Behaviour Beliefs ...... 100 Table 2 Demographic Information for Phase 2 ...... 109 Table 3 Knowlage and Interest in Climate Change and Tropical Glaciers ...... 110 Table 4 Cronbach’s Aplha for the Variables ...... 112 Table 5 Final CFA ...... 117 Table 6 Goodness of Fit for Model 1 and 2 ...... 119 Table 7 Descriptives Statistics ...... 122 Table 8 Correlations Between VRTAM Factors ...... 124 Table 9 Multiple Linear Regression ...... 125 Table 10 VRTAM Analysis of Hypothesis ...... 128 Table 11 Estimated Model 1 ...... 132 Table 12 Compared Models 1 2 3 ...... 135 Table 13 Estimated Model 3 ...... 137 Table 14 Descriptive Information for Ed. Level ...... 139 Table 15 Descriptive Information for Device Users ...... 140

List of Figures

Page

Figure 1. Multimedia Cone of Abstraction ...... 30 Figure 2. VR Figure...... 34 Figure 3. TAM Model...... 65 Figure 4. Hypothesized VRTAM Model...... 71 Figure 5. Garther Hype Cycle for Emerging Technologies...... 73 Figure 6. VRTAM Model...... 75 Figure 7. Hypothesized Model and Modified VRTAM Model ...... 114 Figure 8. CFA for Hypothesized Model ...... 116 Figure 9. Model 2 CFA after Modification...... 120 Figure 10. Path Diagram...... 127 Figure 11. Model 1 SEM...... 131 Figure 12. Model 2 SEM Diagram...... 133 Figure 12. Continued...... 134 Figure 13. Model 3 SEM Diagram...... 136 Figure 14. Model 3 Path Diagram...... 137 Figure 15. Canonical Scores and the Structire for Device Users...... 141 Figure 16. Nevado Santa Isabel Glacier 2010 and 2020...... 147 Figure 17. Hypothesis Diagram among all Variables for VRTAM...... 154

Chapter 1: Introduction

Education is the most powerful weapon which you can use to change the world.

—Nelson Mandela, Madison Park High School, Boston, 23 June 1990

Our planet has been warming steadily for over a century, and the preponderance of evidence points to human activities as the main contributor to this potentially unstoppable phenomenon (Hansen et al., 2012). Imagine that every day we are bombarded with shocking news stories of myriad events worldwide: war, conflict, displacement, and natural catastrophes, such as droughts and floods, which create burdens on many affected societies. However, most of the time, conflicts such as war, displacement and discrimination have their roots in the deep desire of one group to impose its superiority over others. It seems that these conflicts are about humans dominating other humans. But then how about the existence of non-human entities like glaciers that keep shrinking every day? Who should be held accountable for their destruction? To solve human conflicts, there are options available to implement, such as peace building and infrastructure reconstruction, when these conflicts end. But this is not the case for the current climate crisis. How can we address this issue since climate is an intangible and abstract concept? In this case, educators can offer informative approaches to evoke a critical awareness of how we as humans can take a moral stance when it comes to protecting the environment.

Education plays an important role in changing how humans understand climate change and how they can respond to this problem. In my opinion, Nelson Mandela would agree with this argument, perhaps largely because he believed that “education is the most 14 powerful weapon which you can use to change the world.” Again, critical educational theorists, such as Freire, would remind us of the need for education to foster critical consciousness raising.

The United Nations Intergovernmental Panel on Climate Change (IPCC) in 2007 brought together 1,300 scientists from all over the world to evaluate the impact of human activity on rising temperatures and to present mitigation strategies that policy makers could use in the future. In its Fifth Assessment Report, the panel asserted, with over 95 percent probability, that human action significantly contributed to change. The IPCC estimated there to be an average rise in temperature on a global level of 1 degree Celsius in the last 150 years (between 0.8°C and 1.2°C) with a predicted future increase of 0.2 degree Celsius per decade. Similar results are presented in an ongoing temperature analysis by the climate experts in NASA’s Goddard Institute for Space Studies (GISS).

Their results show a 0.8-degree Celsius increase in temperature in the period since 1880, with a current alarming rate of 0.15-0.20°C per decade.

Rationale

I participated in a 2018 expedition known as “Glaciers on the Move.” The project was designed to call attention to the glaciers on the Arctic to highlight their uniqueness.

Moreover, this project explored their influence on the polar environment and intended to educate the locals and visitors of Svalbard about the beauty and the dynamic surging of the archipelago glaciers. As a polar observer, I found it surprising how climate change leads to higher temperatures, causing the snowpack in this region to quickly dissipate.

According to Nuth et al. (2010), the mass volume of glaciers on Svalbard changed 9.71 15

Gton yr-1 with the sea level rising 4% between the last 15 and 40 years. At the same time, on the other side of the world, glaciers scarily began process generating ice and snow; melting in higher altitudes created under-ice water that pushed a mass of snow and ice down.

Glaciers are an essential source of water for societies and agriculture, as well as an important environmental factor for many species that have found habitats in tropical mountain regions. Many studies have shown how global warming influences tropical glaciers, causing them to abruptly shrink, which subsequently poses impeding threats to biodiversity (Zimmer et al., 2018). According to Rabatel et al. (2018), the surface of the

Columbian glacier Nevado Santa Isabel in the Los Navados National Park has reduced

3% per year. Moreover, according to the same study, it is obvious that most of these glaciers, especially the smaller ones, will disappear in the coming era.

Even though this change in climate will only directly harm a small number of residents, their plight needs to be known by as many people as possible. The worldwide youth movement, fueled by their use of technology and social media to share their message, has had a significant impact on world leaders. Together this distribution of information has created an informal education that needs to also have a structured formal element as well.

UNESCO (2014) argued that education is a crucial component of the global reaction to climate change:

It helps people understand and address the impact of global warming, increases

“climate literacy” among young people, encourages changes in their attitudes and 16

behavior, and helps them adapt to climate change related trends. Education and

awareness-raising enable informed decision-making, play an essential role in

increasing adaptation and mitigation capacities of communities, and empower

women and men to adopt sustainable lifestyles. (para. 1)

To foster change regarding the crisis triggered by climate change, policymakers and educators worldwide have committed to engage individuals and the public to be part of the solution. Therefore, the self and the public consciousness regarding climate literacy becomes a crucial element. Education, thus, becomes a necessary tool to evoke public consciousness and nurture a community equipped with the necessary knowledge and skills to raise awareness about climate change and take critical actions to prevent or stop the destruction. Such collective advocacies, then, inform decision-makers to formulate policies that correspond to the current societal happenings as the consequences of climate change. Accordingly, using different educational tools, such as media advocacies, can be an effective communication platform to raise climate change awareness in the community as a way to foster climate transformation.

The United Nations’ meeting, which took place 2016 in Morocco, concluded that education is the most important component in accomplishing the Sustainable

Development Goals (SDG) and putting the Paris Agreement concerning climate change into deed (United Nations Climate Change). The prevailing importance of education is further upheld in the UN's 2030 Agenda for Sustainable Development, as well as in the

Paris Climate Change Agreement. The agreement in Article 12 declared, “Parties shall cooperate in taking measures to enhance climate change education, training, public 17 awareness, public participation and public access to information, recognizing the importance of these steps with respect to enhancing actions under this Agreement” (U.N.

Charter art. 12, para. 1).

The traditional way of learning and teaching has focused on an educational system that typically spotlights standardized testing and accountability. However, there is a need for different educational approaches that can help galvanize students to better understand and think more critically about climate change and its repercussions.

According to critical theorists, the traditional way of education has devalued the experience of students. For instance, such an education tends to put undue pressure not only on students, but also on educators, teachers, communities and parents. Against this backdrop, it is more productive and effective to adopt an egalitarian approach to education. This type of approach can enable educators to incorporate real-life situations and experiences in addressing critical issues, such as climate change, and make the learning available to everyone.

Education should be presented not necessarily as a means to prepare students for future work, but rather to enable them to evoke their political decisions for present and future life, benefitting themselves and their community (Apple & Beane, 2007; Fischman

& McLaren, 2000; Freire, 2008; Green, 1999; Jaddaoui, 1996; Kincheloe, 2007; Ravitch,

2010; Rose, 2009; Simpson, 2006; Weis & McCarthy, 2006). Thus, schools as social institutions should not produce hierarchies and inequalities; education should be an instrument to liberate individual consciousness in order for people to adapt to actual situations, for regulations have degraded students’ intellectual capacity. The subjects 18 valued are those that appear on standardized tests, while other subjects, such as science, history, social studies, art and music, are considered less important. Dewey’s philosophical concept of education might help resolve the issues. For Dewey, education should direct students to become reflective thinkers that reject dogmas, thus school as a social institution should be a place for students to practice freedom (Freire, 2008), where diversity is appreciated, and the interests of the marginalized are accommodated.

Dewey’s ideas of curriculum, therefore, should be based on ecological, anthropological, pedagogical, and epistemological aspects of life so that education can be a manifestation of personal, social, and ecological transformation. Students as the product of such education should take concrete actions to solve the problems within the societal happenings-political, social, economic, and ecological. Critical theorists are rooted in social justice and equality. Thus, education should aim at connecting the cognition and pedagogy while allowing love, solidarity, and the desire to flourish. Therefore, education should pursue a democratic end which enables people to think, feel, and act to solve the concrete problems, such as climate change, that affect almost everyone on the planet.

Education should contribute to the increasing of intellectual capacity that promotes cultural and ecological sensitivity. To this extent, such sensitivity, according to Green

(2008), could be approached through two schools of thought: John Dewey and

Jurgen Hebermas. Dewey and Hebermas suggested that the use of transformative communication is an effective way to solve current problems. Therefore, cultural pluralistic transformation can be implemented through the use of the power of art, such as music, storytelling, and poetry among others. Deep democracy in Green’s argument 19 should oppose the power of neo capitalism in education. The value of democracy while emphasizing protecting the environment is an important purpose of deep democracy. As

Green (1999) pinpointed, to solve the current problem, we need a transformative tool to communicate current issues.

Storytelling has been among the answers used by educators to communicate as well as to disseminate the research findings. James Holland Jones (2019), the biological anthropologist and environmental scientist, shed light on how storytelling as a communication tool can be used to inspire change, especially within the issues of the environment. It is especially true that the neuroscience of narrative storytelling fits the human brain.

World War II brought advances in technology that not only changed people’s lives, but it also changed what many people valued in life. These changes had huge implications in the field of education, too. According to Reuell (2013), fast developing technology in the last decade has brought a rapid increase of educational opportunities.

The number of educational opportunities has not only increased on campuses but has also exploded into online and distance educational tools in recent years. Bowen et al. (2013) suggested that this increase in distance educational opportunities is due to the fact that implementing technology in teaching has the ability to provide economic benefits and better access while reducing achievement gaps, particularly in higher education where online courses are getting more popular.

Nowadays we are using diverse technologies on many levels, from practicing for a driver’s license exam and preparing for a school class, to training professionals in fields 20 of study, especially in the military where technology is a primary tool for protecting vital national interests. Furthermore, the revolution in technology has made immersive VR education the preferred method of knowledge transfer for numerous people around the world. This is because VR education ignores borders, as well as physical spaces and sometimes cultural-social barriers. Availability of such technology influences teaching- learning approaches and has drawn many educators to test and examine distance learning possibilities. Although there are many kinds of distance learning courses offered, there are few that revolve around climate change with a focus on tropical glaciers. The number of virtual learning options is expanding, and universities are using it to compete for a share of the rapidly developing market. Implementing VR in teaching and training has become more popular in recent years. According to ICEF Monitor (2015), distance learning and virtual education brought approximately 1.1 billion dollars in revenue to the

US in 2015. This number is expected to grow to 2.5 billion by 2020 (ICEF Monitor,

2015). Some universities have transformed to profitable distance learning institutions

(e.g., Univeristy of Phoenix) or developed substantial virtual business programs (e.g.,

Pennylvania State University and University of Massachusetts).

Modern technology, including the integration of 360-degree video, also known as

VR, available for everyone to use easily. Thus, students can have a chance to use modern technology tools for understanding on a specific topic. However, there is limited research focusing on VR and learning about the effects of global warming on tropical glaciers.

Virtual experiences with the use of VR can have a significant impact on someone’s consciousness. The online Oxford dictionary described Virtual Reality (VR) as “images created by a computer that appear to surround the person looking at them and seem almost real” (para. 1). Virtual reality gives the opportunity and possibility of being transported to other areas by creating visual and audible stimuli that, when combined, create a sense of being fully immersed in a place far from where a user is sitting or standing and stimulating their sense of wonder and exploration. According to Bryant and

Bates (2015), in a comparison with a traditional class, distance learning classes record a significantly higher satisfaction rate among participants. The survey recorded a 75 percent satisfaction rate among online students in comparison to a 55 percent rate among students participating in on-campus delivery programs. The authors further argued that satisfaction provides improved grades and an institutional performance. The primary reason for higher satisfaction is in the flexibility and comfort offered as students may approach the course materials and other resources at different times, without geographical or demographical restrictions. For many individuals, who are not physically able to attend traditional classes, distance learning options present the only means by which they can earn their degree. 22

Students’ acceptance of the use of technology in their learning about climate change may play an important role in building an improved environmental consciousness.

Therefore, this study examined the students’ perceived acceptance of VR technology in their choice of knowledge acquisition to inform their life decisions concerning the most important environmental threat of our time. If we are not able to take students to see the last tropical glaciers, I believe education delivered through the use of virtual reality (VR) can “bring” these remote areas to the students, especially when climate change must be understood in the present and the future if the global population wants to have hope.

To identify if college students intend to embrace 360-degree lectures with a VR headset and to see as well as hear about climate change and tropical regions, it is crucial to establish a theoretical foundation. To accomplish this, the Technology Acceptance

Model (TAM) (Davis, 1989) was the “Atlas” used in this study as one successful method to predict and explain technology acceptance and the user’s intention to employ it in the future (Davis & Venkatesh, 1996). This model has been tested and proven to be reliable.

It has also shown promise within testing the acceptance of technologies in outdoor environments (Nikou & Economides, 2016). Since the spatial presence is the key component of VR, external variables that were used in this study were based on the spatial presence experience scale (SPES), self-location and possible action (Hartmann et al., 2015). This study proposed a new model VRTAM that incorporated TAM and spatial presence in order to answer the following research questions. 23

Research Questions

The purpose of this study was to investigate the learning effectiveness of a pedagogical approach involving virtual reality technology in higher education to raise awareness of climate change in high mountain tropical regions. It also examined students’ perceptions of the benefits of virtual reality to comprehend climate change. The following research questions guided the study:

1. Do college students think the use of technology as virtual reality will impact

students’ learning outcomes related to climate change and tropical glaciers?

2. Do college students intend to use virtual reality application for their future

learning and understanding climate change in tropical regions?

3. Does the VRTAM model predict an intention to use virtual reality among college

students?

A quantitative research approach was used to investigate intention prior to actual use of VR technology devices by college students. In order to answer all three questions, this study was split in two different phases. Phase 1 sought to determine the core beliefs students had about the use of virtual reality (VR) to experience a natural environment.

The second phase, with the use of statistical tools such as path analysis and structural equation model, answered research questions 2 and 3.

Significance of Study

This study was developed in order to help raise awareness of the issue of climate change in remote areas, such as tropical regions, through the application of VR. This was of great significance because using VR for an educational purpose was still in its infancy, 24 especially in the learning of endangered natural regions and the influence of climate change on tropical glaciers. This study was an in-depth study of these issues. To that end, it seeked to address some of the discrepancies that exist in the literature and aimed to bring new perspectives and lay the foundation for future research in VR education of the remote areas.

According to Christiana Figueres, Executive Secretary of the UN Framework

Convention on Climate Change (UNFCCC), action starts with each individual:

It is critical to include [climate change] in curricula, but it needs to be embedded

in the DNA of today’s very education concept. It is not just another course; it is

about how everything else we study or do is affected by climate change. It is

about understanding the transformation to be able to act on it. (Figueres, 2015,

para. 3)

In this context, I believe this study can support the objectives that Christiana Figueres suggested above, and that is important to the development and implementation of VR education worldwide. In fact, this study expanded the existing body of knowledge and literature in the field of educational technology, particularly in the area of VR learning and technology acceptance. Further, it helped to promote the role of VR technology in enhancing the quality of education for instructors and students. In particular, the results of this preliminary study can be applied to support innovative research and/or to develop technology for future VR learning. Therefore, this study filled some of the gaps between current and potential uses of VR technology in education. 25

Since the use of VR for educational purposes has been quite unknown to school systems, there are many factors that need to be investigated prior to effectively implementing VR in education, such as students’ intention to use it. In this regard, the results of this study could inform pedagogical decisions in designing learning activities involving VR to improve students’ critical thinking abilities.

Researcher Assumptions

The assumptions for this study were difficult to identify because they were existing in various categories: educational, environmental, social and psychological.

1. This study had a quantitative survey. An online survey was given to the

participants immediately after they used VR. Therefore, it was assumed that all

participants will complete the survey.

2. The survey questions will be clear enough and easily understood so that all

participants are likely to respond accurately and honestly.

3. There are potential inconveniences and side effects associated with using VR,

such as motion sickness (Lin et al., 2007), anxiety, confusion, disorientation, and

so on.

4. The theoretical assumption will be that the TAM will prove to be a valid and

reliable instrument.

5. It is assumed that exposure to our environmental crisis may change students’

behavior. 26

6. This study will look at college students, and it will not be possible to cover the

entire student population due to time and budget limits. It will cover students from

20 - 40 different universities worldwide.

Organization of Dissertation

This study is structured into five chapters. The following section is a short description of each chapter:

Chapter 1 provides overall the background such as my personal interested and problem statement, research questions, purpose of the study, significance of the study, assumptions regarding the study, and general aim and outline of the dissertation.

Chapter 2 presents the background information relevant to this study, as well as prior findings. In particular, this chapter is organized in four sections. The first section gives an overview of VR and educational technology. The second section discussed climate change and education about this issue and the importance of studying tropical glaciers. Finally, in the third section, I introduced the theoretical framework that I used in this study.

Chapter 3 describes the method of the study, including the restatement of research questions, research setting, participants, IRB procedures, data collection methods, and the data analysis procedure.

Chapter 4 analyzes collected data from two different phases: the elicitation study

(Phase 1) and the final study (Phase 2). Phase 1 examined research question one, while

Phase 2 assessed research question two and three. 27

Chapter 5 is comprised of my final thoughts, the major findings from both phases, the practical and theoretical implications, the limitations of the study and the questions that need to be studied in the future.

Chapter 2: Literature Review

Where must we go, we who wander this wasteland in search of our better selves.

—The First History Man, Mad Max: Fury Road, 2015

In this chapter, I have attempted to do a review of the scholarship that currently exists on the topics of educational technology and virtual reality (VR). Prior to conducting the study, a literature review was developed to establish a comprehensive understanding of the current knowledge of the use of VR. In addition, this literature review sought to expose gaps, such as unfulfilled potential uses and future uses.

The basis of this chapter is to review literature and background information relevant to the study that investigate the factors that impact the use of VR among university college students, as well to promote tropical glaciers as an environment that should be more carefully studied and preserved due to the impact of global warming in the last couple of decades. The chapter also presents current knowledge of the variety of

VR use and the proposed potential use, especially for educational purposes.

VR and Educational Technology

The affordability and ubiquity of educational technology drastically revolutionize the way learners interact with educators and gain information about the world at an accelerating rate (Dunleavy et al., 2008; Huang et al., 2019). According to the

Association for Educational Communication and Technology (AECT, 1977),

“Educational technology is a complex, integrated process involving people, procedures, ideas, devices and organization for analyzing problems and devising, implementing, evaluating and managing solutions to those problems involved in all aspects of human 29 learning” (p. 1). With this definition, AECT proposed that educational technology plays a major role in the learning process because it incorporates different aspects and requires efforts from individuals and society. The most recent technology that has been used in education is VR (Prinsloo & Van Deventer, 2017).

Historically speaking, the aviation industry and the military developed VR as an instructional tool for pilots and soldiers respectively for flight simulations and practices.

Lele (2011) recognized the importance of VR technology for military training. In particular, exploiting VR was beneficial for preparing trainees in the navy and air force branches to drive specialized army vehicles and to be exposed to controlled virtual environments that resemble real combat situations and circumstances prior to going into battle. According to “Virtual Reality: State of Military Research and Applications in

Member Countries,” a 2003 Hague report by NATO, the “key to the effectiveness of virtual reality for military purpose is the man–machine interface or human–computer interaction. Military personnel must be able to perform their tasks and missions using VR sensory display devices and response devices” (p. iv). This report solidified the prominent status of VR in military training globally. Other industries, such as chemistry

(Isabwe et al., 2017), medicine (Mazurek et al. 2019; Klinger at al. 2004), engineering

(Liarokapis et al., 2004), art (Huang at al., 2016), and sport (Gomez-Garcia et al., 2018), have recognized the usefulness of VR and have started to include this modern technology in improving their technical and practical expertise. Therefore, it seems that education can benefit from VR as well. 30

Dale (1946, 1969) developed the Theory of Cone of Experience (CoE), which explains that students only remember 10% from reading content, 50% from seeing and hearing at the same time but 90% if they see and physically do it in simulation experiences. Baukal et al. (2013) updated Dale’s CoE (1954, 1969) and introduced the

Multimedia Cone of Abstraction (MCoA) (Figure 1). In this model, there are seven levels: symbol, text, narration, nonverbal audio, image, video and virtual reality (VR).

According to them, it is more difficult to represent reality with symbol or text. However, it is easier to depict reality with VR. Therefore, it is reasonable why Baukal et al. (2013) place VR at the bottom of the MCoA.

Figure 1

Multimedia Cone of Abstraction

Winn (1993) concluded with the results of his study that VR helps to create first person, non-symbolic experiences that better assist students to retain educational materials. He also indicated that an educational VR experience is different from a traditional learning experience because VR presents non-symbolic and visual methods of education. According to Slavova and Mu (2018), students who use VR to learn about mandatory subjects, such as the history of Stonehenge, demonstrate better performance over those who listen to content and watch the PowerPoint slides. At the same time, the authors suggested that instructors should make short lectures in VR because that can be a good tool for delivering content in university settings, especially for blended classes.

However, in this study, students reported a lack of peer communications as a disadvantage of the use of VR and that it was difficult to take notes while using VR headsets.

There are four recognized advantages of using VR. The first advantage identifies the ease of redesigning some complex experiments. The second advantage determines that dangerous experiments can be done safely. The third explains that some physically impossible experiments can be done in a VR environment. Lastly, the fourth advantage of using VR is that it is more affordable to repeat experiments utilizing VR, especially when dealing with expensive experiments (Ying et al., 2017).

Horvath (2019) concluded that when teachers and other educators use MaxWhere, an educational platform, instead of a traditional 2D interface, they are able to achieve the same performance with better practical use: “The number of complex operations decreased by 35%, with a 73% decrease in Heavy operations. Compared to the Moodle 32 technique, an even greater efficiency gain can be demonstrated for the operations performed, which is a 64.5% decrease” (Horvath, 2019, p. 6). Freina and Ott (2015) stated that the impulse to use VR provided a good environment for learning, especially when some objects or events are physically far from a learner. However, immersive VR is able to provide a safe environment by removing risks in dangerous situations. In a

Korean study of geography classes in which students needed to learn about digital globes and virtual cities, instructors indicated a strong aspiration to use VR for these purposes

(Cho & Chun, 2019).

Chen et al. (2012) claimed that VR “can provide students with a vivid, rich, varied and realistic learning environment. Students are changed into real participators in the virtual environment” (p. 1217). In a study from Chen et al. (2007), the results were statistically significant for the pre-test and post-test with the use of VR; however, it demonstrated that VR can help students in sixth grade gain a better understanding of astronomy. Nowadays, students and educators are highly influenced by the rapid growth in technology, and, therefore, a new interactive learning environment like virtual reality must be used in different areas prior to being implemented into a school’s curriculum.

Martín-Gutiérrez et al. (2015) further elaborate on how academic institutions have avoided traditional teaching methods, despite their excellent track record, in favor of a more beneficial form of instruction which focuses on increasing a student's overall cognitive ability. An important aspect and indicator for education is the question of how students can memorize some information they learn, as well as for how long they can retain that knowledge. 33

Virtual Reality

Virtual reality has been rapidly gaining popularity during the mid-1900s. Morton

Heilig is considered to be the father of the virtual experience (Gaggioli, 2001; Primetel &

Teixeira, 1993). In 1962, he produced the first multi-interactive sensory experience called

Sensorama. This simulation experience was originally made for only one person to view at a time. It was a simulation ride with a motorcycle through the streets of New York. In his prototype, a fan-generated wind was included, in addition to a smell and noise to stimulate the olfactory and auditory senses to fulfill this unique experience in a closed environment. With the advancement of technology in general came further advancements in virtual technology. In 1968, Ivan Sutherland, at the University of Utah, created the first

VR head mounted display that resembled more closely the VR headsets that are produced today, except that it was much larger and heavier and required a suspension device to hold the weight (Sutherland, 1968). As VR became more prominent, it began being officially utilized by the military, mapping companies, the National Aeronautics and

Space Administration (NASA), in addition to many others. Currently, virtual reality is becoming more widespread and versatile for many different uses, some of which have been discussed in this chapter. Virtual reality researchers are careful to downplay the capabilities in order to not produce hype that can actually be detrimental to users that expect more and lose interest in VR when they do not get what they thought they would from it (How Did Virtual Reality Begin, 2017).

Figure 2

Adopted from “Immersive learning spaces” by Moore, 2019

Extended Reality (XR) /

Mixed Reality (MR)

Theatre Audio Tours Projection Scannable 360 Video Mapping Technology Completely 3D Printing Prerecorded Cave Digital Interactive Interactive Physical Holograms Projection Environments Hologram Overlays Models Digitally- Uses Head- s HoloLens Real enhanced Mounted Body Reality Simulations Display Detection (HMD)

Augmented Virtual Reality Reality (AR) (VR)

VR, virtual reality, is often labeled as a virtual environment, 360 video, augmented reality, and virtuallity, among many other descriptors. It is essential to note the distinction between VR and a 360-degree video for this study. This multidisciplinary field of research is still in growth mode, and every new invention related to the VR arena may become a new field rather than a subset. Extended reality (XR) has formed a variety of mix reality (MR) areas (Figure 2). Technology tools, such as 3D printers, have become more affordable in recent years and are therefore more commonly used devices for educational purposes. On the other hand, VR is a 3D space learning environment, where learners can be in a fully digital environment encompassed in the virtual world, such as the 360-video cave projection (Moore, 2019). Hence, augmented reality (AR), in the 35 middle of Figure 2, is a combination of a virtual and a real environment, augmented by technology (Resnyansky et al., 2018). A study by Huang et al. (2019) showed that both

AR and VR environments improved knowledge retention because of spatial presence which resulted in psychological and cognitive reactions.

In an article linking the use of VR to happiness, Gotsis (2018) discussed that individual happiness in connected to who we are on the inside, as well as our background

(from where we came), and that true happiness does not originate from simple basic pleasures. The author claimed that augmented VR helps to connect the spaces between humankind’s need to bond with others, as well as connecting with the present and past in order to help generate true happiness. Allowing a person, the ability to explore and interact with the VR world around them will also help with creating a desire to explore, ultimately leading to happiness. One of the goals for implementing VR into daily life is to foster inclusiveness and happiness. Both inclusiveness and happiness are related because if VR is to be implemented into natural environments, it must be inclusive of all people, and a way of measuring inclusiveness is through happiness levels.

Forman and Korallo (2014) stated in their article that, in general, VR has been a success. Successes mentioned include mobility, architecture, and medical applications.

Individuals suffering from medical conditions, including cerebral palsy and spina bifida, have been able to successfully help effects, such as spatial awareness, with VR. In regard to education, virtual reality has been a success as well in the history category. Virtual reality has the ability to be utilized to create historical timelines that students can visually see, which makes sequencing the information at hand an easier task. Individuals that 36 suffer from limited mobility have the opportunity to benefit more than those who do not in park settings. VR is shown to generally be not only effective by means of easy usability and enhanced understanding, but educationally, it is a success as well. Park employees are typically meant to be stewards of the parks, and stewards, such as naturalists, do that by means of education. Ecological and cultural histories have been a large part of that education, and VR in parks can help bring that education to life. A study done by Lacko (2019) showed a significant difference between two groups of students learning the same subject, where one group of students used VR while the other group did not. The study showed that VR helped students achieve a better percentage of correct answers immediately among the group that did not use it. Furthermore, the same study indicated that students that used VR performed better after one week and after one month. Students with VR answered with 71% accuracy compared with the students without VR who had 52% of correct answers after one month. Despite the results, motion sickness, which is discussed in the next section, manifested in about 12% of students that participated in this study.

Detrimental Consequences. Some detrimental effects of using VR have been reported. With the use of VR, as well as Virtual Environments (VE), one major issue that can occur is called visually induced motion sickness (VIMS) (Keshavarz, 2016).

According to Keshavarz (2016), typical negative effects that can appear to a user who is interacting with VR can range from pallor, cold sweats, and oculomotor issues, to awkwardness and nausea. The symptoms present in typical motion sickness can also occur as a result of VIMS and is caused by the visual simulation of VR use. There are 37 few theories that attempt to explain this phenomenon, but the origin of VIMS in not fully studied. Overall, the average occurrence of VIMS has been estimated from 5% to 60% for someone who has used VR (Kennedy et al., 2010). There are a few techniques that can help reduce VIMS. It is important to mention that VIMS is mainly based on aspects of VR application rather than hardware limitations (Sevinc & Berkman, 2020).

Keshavarz (2016) claimed that supporting postural stability and promoting a pleasant ambience are some methods that can significantly decrease the negative effects of VIMS.

Moreover, to better understand natural phenomena, images in textbooks or on a screen are not sufficient. They will not allow learners to fully grasp a concept, especially if it is important to see glaciers calving and dynamic movement of the ice and snow in a mountain region (Pena & Gil Quilez, 2001). In preparing study material for students, it is important that the environment be pleasant and secure to avoid VIMS.

VR and Diversely Abled Populations

Keller et al. (2017) discussed public perceptions of healthcare as they relate to virtual reality. Most public responses indicate positive feelings about its use. The only perceived limitations of virtual reality currently are in the development of current VR technology. Results show that typically the majority of people think that virtual reality is beneficial to different demographics of individuals, primarily people with limited mobility (Keller et al., 2017). There are limitations to the study, which include the participants’ biases. The study was also implemented in a positive method, which could lead to increased positive responses. A further limitation of the study is participants only included Facebook users, and it was only users that had it appear on their general 38

Facebook feed. No detailed demographics were truly conducted, and people that participated had the option to leave no comment.

Public perception is important when implementing something into a public park system. Elected officials generally lead public parks, so those officials in charge must keep the public's desires in mind. If the general public did not desire virtual reality, then that decreases the incentives of different park directors to approve funding for VR as a way to increase exposure in parks. Utilizing social media platforms is one of many ways to assess public perceptions as it can reach many people instantly and provide immediate feedback. This is just another way to estimate perceptions of VR as well as educate others on the potential that virtual reality has to offer in parks, especially for people with limited mobility. For better understating students with special needs, University of Ottawa created specific VR to teach non-disabled students about the hurdles that students with mobility impairments are faced with every day in school and in the classroom (Jeffs,

2010).

Storytelling

When we think about storytelling, the first image that comes to mind is a mother telling a bedtime story to her child or an older man sharing his experience with a young audience by the evening campfire. This image takes us back, sometimes as far as we can remember, and revives an innocent feeling of belonging to humanity. People are storytellers, and this did not evolve just from a wish to entertain others, but also as a necessary tool in the evolution of human culture. Our reaction to stories is instinctive, and their form makes them easy to comprehend and recall. Due to significant cognitive 39 consequences, physiologists define stories as “psychologically privileged," meaning that our brains process them differently than other types of information (Willingham, 2009,

2012). Stories can be both dangerous and a path to emancipation. Stories can change the mindset to look at the different possibilities of life. A story ignites consciousness and shares the narratives of those who cannot speak for themselves. By combining the elements of reality in the story, it can show a different reality other than what is presented:

[Stories] can show that what we believe is ridiculous, self-serving, or cruel. They

can show us the way out of the trap of unjustified exclusion. They can help us

understand when it is time to reallocate power. They are the other half—the

destructive half—of the creative dialectic. (Delgado, 1989, p. 2415)

To understand the advantages of this type of delivering of material, one must understand the fundamental structure of stories. Although there is no acknowledged definition of what a story is, the majority of theorists agree that it has a basic structure. The basic features in a structure are referred to as a "The 4 C's” (McKee & Fryer, 2003). These C's are Causality, Conflict, Complications, and Character. Causality refers to the relation between events, meaning that one event starts and consequently leads to another. The second C stands for Conflict, meaning that a lead character, in order to achieve their objectives, must face and overtake obstacles. Conflict stands between the protagonists and their goals and can be external (e.g., a business that destroys nature for its profits) or it can be internal (e.g., self-doubt of characters). Every conflict needs a villain. 40

The third C is Complications. Their steps in facing hurdles are the means that carry a story forward. In the process of overcoming obstacles, the lead character usually creates and solves additional complications that need to be dissolved in order to achieve desired results. Finally, the fourth of the C's is Character. Interesting stories need fascinating characters that can carry action and keep us animated. The main protagonist can also be a group of people, however there must be a lead character that embodies their endeavor. Stories are typically structured in a way to keep a spectator engaged by presenting the information gradually. This measured delivery seems to be more efficient than if the information comes too easy or in a very complex form. Presenting it too easy can be dull, but on the other hand, people can become frustrated if the form is too complex. People more easily comprehend information when it is delivered in the form of a story, regardless of what the topic is. Graesser et al. (1994) tested this idea in a way to expose subjects to different texts; some were narrative texts, and the others were expository texts. The researchers then analyzed the complexity of texts and how much time subjects need to grasp the information delivered. The study showed that people read and comprehend stories much faster, and, therefore, it is easier than narrative text.

People use stories to deliver messages and inform our attention. All stories are valuable, and no story is more important than another. Thus, a story as a communication tool has been used by people to intentionally affect the consciousness of people.

Sometimes creators are professionals and also amateurs. Storytelling has been used in different professions: political, social, and educational. For example, social workers use stories to bring about change and to better communicate the message about social 41 inequality. Frequently, they want to counteract the false stories that have been created by master narratives and that have mistakenly represented the real situations of a community. In this case, they wanted to present the alternative to the stories that have been created to evoke people’s consciousness. To this extent, such story telling becomes pivotal means to advocate for the rights of marginalized communities (…..) and to bring people’s awarensess about the conditions of non-human chacters such as glaciers (…)

Storytelling as Tool for Advocacy

Storytelling has been used as a tool for advocacy from long ago. Especially in today’s world, freedom of expression allows everyone to tell their stories. The question becomes which stories are legitimate, and which ones are not. For example, human rights groups and conservators and protectors of nature around the world have utilized storytelling through video as a tool for advocacy. They have integrated campaigning strategies, both printed and online, to deliver the messages of what is happening within the society. An example is the work by Witness Organization that uses video as a tool for social change through the sharing of stories that support the local people in the

Philippines to voice their rights. “WITNESS helps people use video and technology to protect and defend human rights.” (2019, para. 1). Through video storytelling, their motivation was to reach out to multiple stakeholders, such as the government, news media, activists, and policy makers that they could take into consideration to frame such issues in their work. Employing the testimonies as part of the story of the local community through a video story helps to share the underlying structural realities at the local level, as well as the mobilization strategies, both local and global. It provides an 42 impression of the context through visual images and through the story people narrate.

When visual imaginaries and stories both coexist, it provides the authenticity that enhances the real meaning of advocacy and goals for the purpose of change. Therefore, the motivation to use the video story approach enables the human rights workers:

To collect, analyze, edit, and disseminate information for maximum advocacy

impact. The goal is to complement—not replace—other forms of advocacy, by

supporting our partners in identifying the audiences they need to reach with their

arguments and by drawing on by video’s unique power to bring these stories, as

well as the visual “evidence” of human rights abuses, directly to a human rights

decision-making body, a government policymaker, a community, or the global

public. (Avni, 2006, p. 207)

According to Lambert (2013), “[story] work is the quiet place around which the storms can blow” (p. 3). Educators have used storytelling as well to improve the literacy of students in improving their academic understanding as aesthetic ways of knowing (Aiex,

1988; Miller & Pennycuff, 2008). For example, research shows that using storytelling as classroom pedagogy enhances students’ ability in reading and writing (Miller &

Pennycuff, 2008). Such a pedagogical strategy does not only improve their academic achievement but also motivates these students in learning. The use of story can capture the attention of the students, which improves the sense of story itself in students. By interacting with stories, students improve their learning of certain social aspects. In addition, when students retell stories, they have the ability to deeply comprehend them through expressions that reveal the meaning because the stories themselves evoke a 43 strong sense of emotion (Eder, 2007). In writing, students can first select their own stories that they want to tell. Allowing students to choose their own story in writing motivates them to accomplish the task as they own the story itself. Teachers can then serve as facilitators. Instead of giving students what to write, the teachers can let them own their story by having them put it in writing. Besides students owning their unique story, in addition, their motivation, their confidence, and their motivation to craft the stories increases because they feel like they played an active role in the process, and thus becomes meaningful to them (Miller & Pennycuff, 2008).

Story as a Way of Approach. Story as a way of approach usually is implemented by a narrator to engage in the experience of someone who is listening/watching. By listening to their story at hand, it could overly establish new knowledge that might have been represented differently in other interpretations. By having such a story, the new knowledge could establish the process of change in which such knowledge could provide a new approach on how to respond to particular situations (Clandinin, 2016). Thus, the underpinning of the use of a story as a tool of approach is based on the following assumption:

People shape their daily lives by stories of who they and others are and as they

interpret their past in terms of these stories. Story, in the current idiom, is a portal

through which a person enters the world and by which their experience of the

world is made personally meaningful. (Clanidin, p. 375)

Telling a story is a challenging approach. It requires time and effort to study the places and the context. Therefore, the researchers need to unearth extensive information about 44 the story they told. To fully capture the context of the stories, collaboration needs to take place. Therefore, understanding the context is pivotal in storytelling

(Clandinin, 2016). For example, when talking about the inequality in other parts of the world, not everyone has access to be able to see the reality of that place, such as tropical glaciers. It is through stories and through other medias, such as digital storytelling, that people are able to at least have a near-authentic experience, closer to the real world. For example, children all over the world experience different phases in life. They could share their stories to connect with the world as part of global advocacy. Similarly, people were projected through videos, printed news with different catastrophes in which where we learned how to know about people suffering in different part of the world.

Acknowledging that people learn differently was among the pedagogical efforts to advance creative learning for students, and at the same time, evoke their awareness about the social injustice happening worldwide.

For example, in developing science policy, the stakeholders need to provide a better tool of communication that can deliver messages that inform the policy.

Storytelling has been used as one of the effective strategies, particularly bloggers, to inform policy makers. Oliver and Cairney (2019) advised the use of the storytelling approach to better communicate narrative science with the policy makers. They argued that storytelling has been an effective tool of persuasion that informs action and change.

Indeed, not everyone can understand well on particular contexts, so perhaps, storytelling can play a role in communicating the meaning to lay persons that are not familiar with them. 45

Digital Storytelling

Storytelling is a tool of communication, and digital storytelling is telling a story with digital technology (Alexander, 2017; Bryan, 2011). As Alexander (2017) stated, with the new technologies that appear every day, it creates a myriad of opportunities for some stories to be told to a variety of people. Thus, digital storytelling is:

The practice of combining narrative with digital content, including images, sound

and video. The purpose of a digital story is the same purpose of the stories of oral

tradition—to invoke an emotional effect and/or to communicate a message to its

audience. (Malita & Martin, 2010, p. 3601)

Digital storytelling has been utilized by educators as a learning tool to engage students in their learning (Oppermann, 2007; Robin, 2008). Educators have used digital storytelling as a means of instruction to help students understand a concept as it can be a powerful way to produce a historical documentary (Robin, 2008). The use of digital storytelling as classroom instruction has been known to improve students’ motivation in learning. It helps students increase their understanding as well as confidence about the subjects

(Yoon, 2013). Perhaps the most common type of digital storytelling is the author sharing their own personal experience. Sharing such an experience can conjure up an emotional response to add to the personal meaning for both the story’s narrators and the audience who is listening to the story. Digital storytellers can utilize a story derived from a historical photograph, newspaper headlines, or a speech (Robin, 2008).

Digital storytelling is considered the most powerful tool to capture a story in a relatively short time with significantly less money (Tucker, 2006). What makes a digital 46 story a good story? Lambert (2013) shared characteristics of a good digital story: owning the insights, owning the emotions, finding the moments, seeing the stories, hearing the stories, assembling the stories and sharing the stories.

VR and Storytelling

Storytelling is not limited to conveying stories from one individual to another; rather it is often utilized in a virtual reality (VR) platform to communicate stories and produce meaning. Involvement in a virtual reality simulation is user-focused and engages users in real-time, utilizing authentic or fictional locations and objects (Dooley, 2017).

Within these fictional locations, an individual is, in essence, a character in the VR simulation. Users typically wears a headset, earphones, and hand-held controllers, which allow them the ability to interact with the surrounding VR environment (Dooley, 2017).

Engaging the senses, such as sight, sound, and the ability to interact with the environment, are all utilized within the 360 VR platform. This enables a user to relate to a broad range of VR locations, which fosters anthropomorphic meaning for the intended simulation (Dooley, 2017; Root-Bernstein et al., 2013).

One ability of utilizing a VR platform is its capability to encourage conservation through education. According to Root-Bernstein et al., (2013), people understand representations of animals in VR better than if they were to have contact with them in the wild. For example, a bear living in the wild will not be as understood as the anthropomorphic image of Smokey the Bear, and by utilizing the bear's image, people become more connected with it and its messages. By using VR in an educational role, the content of the simulation will not only be able to tone down the emotional aspect 47 pertaining to conservation or environmental issues but will also instill a sense of interest in scientific findings (Martinez-Conde & Macknik, 2017). Morris et al. (2019) stated that

"eliciting emotional arousal likely improves the odds that listeners will not only engage with the material but also act on it as a result" (para 7).

Researchers are often puzzled how to communicate with the general public about scientific matters effectively, often creating gaps in information, making it challenging to develop policies to deal with concerns (Martines-Conde et al., 2019). By using VR as a basis for digital storytelling, topics can be addressed using a platform that allows users the ability to interact with a real environment, digitally. These interactions can exploit real-time issues in the form of games, utilizing characters that users can connect with and ultimately advocate for their survival or the survival of their ecosystem. However, to communicate stories effectively, researchers often use a perspective to deliver the messages from such stories, especially before the stories are told through VR. The researchers often connect their experience and frame the stories before they disseminate them. Therefore, the knowledge of interpretation becomes a salient aspect in this case

(Martines-Conde et al., 2019).

Environmental Interpretation

Environmental interpretation/education of high mountain regions, and the importance of telling a story and sharing it with a broad audience, started first in the US national park, Yellowstone (Tilden, 2009). According to Ham (2016), environmental interpretation has been applied in a variety of additional settings, including museums, 48 galleries, historical landmarks, heritage attractions, schools, zoos, aquariums, gardens and food production (e.g., vineyards), essentially anywhere of special interest or importance.

Characteristically, the interpretation technique is thought of as an attractive way of employing a guided talk that is used for natural spaces not accessible to everyone

(Ham, 2016). The environmental interpretive approach is a cutting-edge form of communication which tries to to generate enjoyment, commitment and knowledge through visual and written technology (Ren & Folta, 2016; Tilden, 2009). Furthermore, this approach is a discretionary form of education for a non-captive audience, hence students choose how much or how little they wish to partake (Ashraf & Aqma, 2017;

Ward & Wilkinson, 2006). Interpretation creates the inherent meaning of the natural surroundings of some specific area by examining communication strategies that aim at increasing knowledge to influence the behavior of visitors.

Ham (2016) suggested the interpretive approach should follow the ‘TORE’ structure: A Theme (T) that is Organized (O) which visitors can Relate to (R) whilst holding their interest and therefore is Enjoyable (E). However, each maintains a version of TORE, which succinctly describes how the interpretive approach must engage and entertain whilst maintaining an educational relevance (Ham, 2016; Tilden, 2009; Ward &

Wilson, 2006). In the form of this structure, education has the ability to provide understanding, eliminate negative molds and generate pro-environmental attitudes among students (Ren & Folta, 2016). The way in which the interpretation of the unapproachable or forgotten areas are presented is often through storytelling. More so, interpretation has 49 evolved to include forms of digital, visual and audio displays which can aid in further immersing visitors (Kundson, 2003; Tilden, 2009).

The rapid growth of modern technology brings new access to nature where individuals will be able to visit the wilderness without having to travel to that specific location. Even those individuals who have social anxiety could benefit and be affected by this concept, especially when considering the number of people who visit some national parks each year. In these instances, virtual reality provides a way for these types of individuals to experience the environment in a way they have not been able to before; they are able to stay within their comfort zone or face less exposure to risks because the area they want to see is difficult for them to access under their circumstances. Winn

(1993) conducted a study that concluded that virtual reality (VR) helps to create the first- person, non-symbiotic experiences that better help students retain educational materials.

Moreover, he indicated in the research that an educational VR experience cannot be achieved in any other way than in a traditional learning environment, and that VR helps students retain knowledge by presenting a method of education that is non-symbolic.

Different types of learners exist, and virtual reality creates a method of learning that is beneficial to visual learners, especially for environments that will soon be gone forever.

VR as a Safe Learning Experience

In order to expose students to challenging learning environments that are inaccessible due to weather, difficult terrain, political issues, distance or human mobility, technology in the form of VR may present a solution. A study done by Yu et al. (2018) supports the idea that VR has the ability to be an option for individuals with limited 50 mobility to approach remote regions that would previously be inaccessible to them to gain an environmental experience.

Riva (2020) discussed the possibility for virtual reality technology to be used as an environmental conservation tool. At the Stanford Virtual Human Interaction Lab in

2014, a virtual reality game was introduced which attempted to visualize and conceptualize ocean acidification. Essentially, the prolonged addition of carbon dioxide into the atmosphere creates ocean acidification over very long periods of time. However, with this VR game, the process is sped up to occur right before your eyes so that the visual stimuli generate an emotional response. This response is one means of conservation for the environment. This type of method helps the many visual learners in the world who are not impacted by textbooks or by mere verbal delivery of information from an educator.

Environmental health starts with education. Implementing virtual reality to look at current environmental health issues is a step in the right direction for education. Miller’s article is simply a reactionary article, but it is important because it invokes dialogue about virtual reality and the implications that can be utilized to help benefit many different aspects of the environment and the people that enjoy it. The current limits of VR in regard to Stanford’s lab are storage capacity, computing generation and speed. In addition, a popular article, such as Miller’s, is one that will reach more people than one that is hidden in a scholarly library, such as Google Scholar. This allows for the educational benefits to reach a larger audience. This large scale education about the environmental health impacts of our delicate areas coincides with many different park 51 missions, such as the mission of the National Park Service (NPS), which “...preserves unimpaired the natural and cultural resources and values of the national park system for the enjoyment, education, and inspiration of this and future generations…” (About Us, par. 1, 2018). This environmental health impact that Stanford University is taking part in stands as support for the foundational idea that virtual reality should be implemented in parks. Virtual reality can educate previously unreachable people and show firsthand environmental changes that would previously not be something that could be witnessed.

An article by Lovell (1996) discussed the notion that by the early 2000s, VR would be in homes everywhere. Though the availability of VR did not boom as predicted by Lovell, his prediction could definitely be a reality in the next 50 years as technology in

VR becomes cheaper and more realistic with even better resolution and a more comfortable fit. This will invoke readers to think about the possibilities of VR in our everyday lives, including in the recreation field. People are still talking and writing 20 years later about VR as shown by Millar (2016), and it is this public dialogue that pushes progress forward; when people are interested in something, markets emerge. Guttentag

(2010) claimed that the tourism industry can benefit financially by helping people create memories in places that people cannot typically travel to. There is potential for people using virtual reality headsets to be led on guided informational programs, which the tourism industry can be a part of. Public and private tourism organizations can utilize virtual reality in marketing techniques to pass along information in new ways. Virtual reality tourism implications were tested further by Tussyadiah (2016) who documented participants’ satisfaction and enjoyment levels and also noted whether or not the 52 experience felt more fluid or if it felt more live than viewing pictures. The research shows that, in general, the participants typically felt more adventurous and explorative

(Tussyadiah, 2016). The participants voiced that they had positive feelings of successfully navigating through virtual reality and not simply staring at photographs. This study also indicated in the research that VR can be utilized as a tool for persuasion as a means to have more tourists travel to destinations by creating virtual environments that are free from distraction and which are also aesthetically and audibly stimulating.

Distance Transformative and Adventure Education

For educational purposes and gaining new knowledge, diverse technologies have been incorporated on many different levels, from online streaming lectures (Shiozawa et al., 2017) and self-paced classes (Ironsmith et al. 2003) to training medical practitioners with the use of VR (Machado et al., 2011). Distance education, according to Henrickson and Doering (2013), can help students to explore alternative learning modalities, exponentially improving didactical goals. On the other hand, Lloyd (2010) argued that this kind of education is not good for those students who prefer kinesthetic learning modalities.

Students can experience the real world, such as an extreme environment in the

Artic Circle, while using a blended educational environment through a specially designed distance learning lecture. This type of learning is called adventure learning, and it was established by Doering (2006; Henrikson & Doering, 2013). Furthermore, Doering

(2006) indicated that online adventure education has the possibility of preparing students for real life situations. 53

Climate Change and Education

Senator Al Gore (1992), Jim Hansen (1981), and many other scientists and politicians in the beginning of 1980 started the task of presenting climate change data around the globe with the intention of changing attitudes of people and the hope that their behaviors would shift towards protecting the planet from extinction. This idea of using climate information is still present and recognized as the key in preserving and sustaining many regions worldwide, including the often-endangered species that reside there.

According to Burkholder et al. (2017), young college students are going through the epoch of changing personal identity and perceptions, as well as beliefs, during their time spent in a college. At the same time, this can impact students’ views and beliefs on the certainty of climate change. Many educators have recognized this important time in students’ growth and development. Therefore, the college years may be the best time to introduce into the curriculum the climate crises as the biggest threat to humanity and nature with the hope that this knowledge will inspire students to shift their habits in their everyday life and to encourage a sustainable way of living that incorporates one’s natural surroundings.

The main future-orientated global policy action related to climate change is embedded in the Paris Agreement, adopted by 195 nations in 2015. The agreement was the first global initiative tackling the problem of rising temperatures. The main goal set in the document was keeping the rise of the global temperature below 2 degrees Celsius, with a long-time effort of containing global warming to 1.5 degrees Celsius. In order to achieve this goal, the countries agreed to establish appropriate financial flows, enhance 54 new technologies, and assist developing countries in sustainable development. Every party involved in the Paris agreement had to set Nationally Determined Contributions

(NDCs) that reflect each country's specifically sustainable targets that they aim to achieve.

According to The Commonwealth press release draft (n.d.) and Confalonieri et al.

(2007), the most significant negative impact on human life so far has been felt in low- income countries. Among the hardest hit are the poorest citizens, especially children and the elderly. The Displacement Solutions and the United Nations Environment Programme

(2015) reported that the entire country of Kiribati will vanish in the next 30-60 years, as well as other countries with similar situations due to rising sea levels.

Tropical Glaciers

Do glaciers really exist in the tropics?! In fact, we can find them all over the highest mountains in the world, even in the tropics, as long as the mountains are high enough. The word "tropics" is typically associated with sandy beaches, tropical forests, and hot and humid weather. Rarely are they associated with snow, ice mass, and high mountains. According to an article published in the National Geographic (n.d.), "The tropics are regions of the Earth that lie roughly in the middle of the globe" (par. 1). Thus, tropics can be referred to as regions with glaciers, too. Inherited from the last Ice Age, today about 3,000 glaciers are still holding onto their elevated summits between the

Tropics of Cancer and of Capricorn. These tropical glaciers, the last of their kind, are disappearing fast, directly affected by increasing air temperatures and changing weather patterns. 55

As stated by Kaser and Osmaston (2002), tropical glaciers could be found in

South America, East Africa, and in the southwestern Pacific islands of Papua New

Guinea. Tropical glaciers archive important information about the climate, and at the same time, provide a water resource for humans, in addition to the local flora and fauna. Since this study is 24 years old, it is a relevant question for these areas: do their glaciers even exist today?! Most of the tropical glaciers are tourist attractions. Ascending a mountain, visitors can experience the multiformity of different and unique vegetation, wildlife and natural scenes that can leave a significant impact on human behavior.

Roughly 96 percent of all tropical glaciers were discovered in the Andes.

According to Enslin (2017), the glaciers in Peru have deteriorated considerably. Over the last 50 years, their surfaces have reduced by half. This regional-scale model showed different dominant drivers in the transformation of the Andeans glaciers. The difference occurs as a consequence of a local microclimate situation with a domination factor of an annual participation. According to Kaser and Osmaton (2002), there have been several vicissitudes of changes in the tropical glacier environments that directly influence the forming of dangerous proglacial lakes: "In this steep, tectonically active, third-world mountain environment where suitable engineering solutions are confounded by socio- political instability and a lack of consistent funds or institutional support" (p. 3298).

However, it is important to be aware of the future risk to clean water and a safe environment for local societies.

Effects of Climate Change on Tropical Glaciers

The glaciers that are found in the tropical regions are losing their fight against climate change. The impacts of global warming on tropical glaciers are remarkably negative. First, even though surging glaciers create some of nature's most dramatic visual phenomena, they imperil human and animal populations living around them on a very large scale. Second, climate change has been determined to be the number one cause of glacier recession, by increasing global air temperatures. However, other factors, such as

El Niño effects and volcanic eruptions, also cause glaciers to retreat (Houghton, 2001).

Many studies utilizing everyday monitoring indicate that there is a dramatic increase in temperature, especially in tropical areas. Ceballos et al. (2006) attested to the glacier retreat that has been taking place over recent decades in the highest mountain elevations of Colombia. Furthermore, in Colombia, topographic positions of glaciers create specific microclimates at elevations that are higher than 4700 m (Ceballos et al., 2006). Scientists caution that within a few decades, the world's tropical glaciers will vanish (Whitfield,

2001).

Already the beginning of this shrinkage of glaciers has impacted people living downstream in tropical mountain areas but later will affect the world on a global scale.

For example, as a result of the 2016 El Niño, Bolivia faced the most severe drought since

1980 (“We are Water Foundation”, 2017). Moreover, according to a 2020 study, 1.9 billion people depend on water from mountains and glaciers as their primary source

(Immerzeel et. al., 2020). All these people rely almost entirely on water from glaciers for drinking, agriculture, irrigation, hydroelectricity generation, and other purposes. Glaciers 57 are an important source of water for society and agricultural use, as well as a necessary environmental element for many of the species that inhabit these tropical mountain regions. As the glaciers melt, they alter the human story in a reflective way. Many studies have shown how global warming influences tropical glaciers, causing them to abruptly shrink and create or cause impending threats to biodiversity (Zimmer et al., 2018).

According to Rabatel et al. (2018), the Colombian glacier Nevado Santa Isabel in Los

Navados National Park has a glacier surface that reduces by 3 percent per year.

Moreover, according to the same study, it is obvious that most of these glaciers, especially the smaller ones, will disappear in the coming decades. The Colombian glaciers have gone from 374 km2 to 37 km2 in 2017; hence, Colombia has lost 92% of its glacier area in the last 170 years (IDEAM, 2017). Against this backdrop, the study of tropical glaciers is in its embryonic stage despite its impact on the local population and its scientific importance.

The Role of Education on Climate Change

Irwin (2020) identified that education and teachers play a key role in the development of students’ attitudes towards life and guide the roles the students will fill in society. This influence could be used to develop an awareness of existential issues around the globe. Furthermore, students also need to recognize that radical changes in education are necessary to place climate change as a top priority for study in order to find a possible solution for shifting to a post-carbon world.

Our education system is failing us. We’re not being adequately taught about the

climate crisis in our classrooms. Schools are not preparing us for the world we’re 58

about to enter, yet still prepare us for jobs and a society based on the system that

caused the crisis. We must urgently reform the national curriculum and learn to

address the ecological crisis as an educational priority. (UK Student Climate

Network, 2019)

Different approaches have been taken by different stakeholders from all over the world.

Even children and young adults have recognized the need for extensive reflection about what is being taught in schools. Changing the minds of educators is essential to reflect the change necessary to existing strategies so that new solutions can be developed. Educators can offer better scholastic approaches that evoke critical awareness in students’ minds so that they give the same moral standing to people throughout the world. In this case, education plays an important role in producing a resilient generation who will take action to promote the issues necessary to prevent human extinction.

Strategy of Change. Ballegeer et al. (2019) stated that the universities must take a leading role to promote education, communication and research related to climate crises in order to prepare new generations for the future where mitigation and adaptation will be the only options to survive. Climate change is an abstract and complex issue that involves a longer process and a larger spectrum of disciplines. A movement that began in 2019 and was started by 15-year-old Greta Thunberg under the name “Schools Strike for

Climate” has increased global climate change communication and put pressure on the educational system as well. Ballegeer et al. (2019) recognized steps that universities should follow in order to step up against the most significant threat to all species on our planet. First, schools need to recognize and improve climate change through research as 59 one of the highest priorities. Second, they must raise awareness and provide communication on this issue, and third, schools should promote learning and caring about climate change, not just studying it as a topic. However, the role of universities is also to transfer a message of possible solutions and to create resilient students that are willing to act in order to save the ecosystem that is crucial for all living species. Swarat, et al.

(2012) stated that 7th and 8th grade students in the Midwest region of the US reported a higher interest in activities that were hands-on in nature, particularly those that involved the use of technology. The collaboration improves learning as shown by the Globe

Network, where they have involved scientists in designing protocols for data collection and educating students on climate science learning and investigation (Butler &

Macgregor, 2003; Tessendorf et al., 2012). Furthermore, a project under the name

“GoNorth!” led by Doering in 2006 involved 65 middle school students in the Midwest and Northwest United States that used online platforms to follow the expedition in real time and studied environmental change with experts in the field (Doering & Veletsianos,

2008).

Gold et. al. (2015) also tackled the importance of collaboration and the use of technology for learning about climate change. In incorporating technology, such as making a video about climate change, it was shown to improve learning among 64 middle and high school students in Colorado. These students created videos on “locally relevant climate change topics” for a period over six months (Gold et al., 2015). Prior to using any technology in environmental education, it is crucial for instructional designers to learn about students’ needs, capabilities and intentions in order to provide instructional 60 technology that is likely be used and included in the curriculum (Dailidiene et al., 2019).

According to Makrakis and Kostoulas-Makrakis (2012), several major developments are determining and driving education in this century. First, information and communication technologies are now highly involved in educational systems. Second, transformative and lifelong learning are considered to be the most desirable approaches in education. Third, sustainable development is getting attention and is becoming the standard educational curricula. A study from Dailidiene et al. (2019) showed that all graduate students agreed

(89% highly agreed and 11% agreed) that environmental change management is only possible through the integration of a new technology in education in order to understand current issues and advocate for the future.

Climate change will likely define the environment and the speed of melting glaciers worldwide, especially those in tropical areas. To learn about these glaciers is a race against time. For the majority of students, the only way to see these mountain areas are with the use of technology and distance learning. Technology has the ability to enhance the quality of academic courses on climate change for instructors and students when field classes are impossible. However, different mountain areas compared at the same time may increase enjoyment and education as a foundational aspect. It is important that VR meets those requirements, especially as tropical glaciers disappear due to global warming. Therefore, a critical analysis of different educational applications of VR is important in relation to teaching and learning about climate change and tropical enviroment. 61

Theoretical Framework

Because technology began to develop more rapidly in the last century, many theoretical theories came with technology innovations in order to understand a user’s intention and decision to use some device or technology application, particularly for educational purposes. Generally, theoretical frameworks help to determine what things will be measured, as well as guide a research and help determine what statistical relationship will be examined. One research study that seems to explain and predict the process states that theoretical frameworks “provide a conceptual guide for choosing the concepts to be investigated, for suggesting research questions, and for framing the research findings” (Corbin & Strauss, 2008, p. 39).

For students to benefit from technology for the purpose of education and to better understand scholastic content, it is indispensable to use technology more often in the classroom setting, as well as outside of classroom. Many studies have been done that examine the use of technology among college students (Zogheib et al., 2015), some focusing on software and some on hardware use (Ducey & Coovert, 2016). To better understand the use and the intention of using some technology in education, throughout the last couple of decades, researchers have developed many different frameworks and have tested a variety of technology tools that can increase students’ learning and performance.

The most dominant theories in relation to technology research are:

1. Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975)

2. Theory of Planned Behavior (TPB) (Ajzen, 1991) 62

3. Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et

al., 2000; 2003)

4. Innovation Diffusion Theory (IDT) (Rogers, 1962, 2010)

5. Technology Acceptance Model (TAM) (Davis, 1989; Davis et al., 1989)

6. Extended Technology Acceptance Model (TAM 2) (Venkatesh & Davis, 2000)

7. Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) (Venkatesh

et al., 2012)

8. Fit between Individuals, Task and Technology (FITT) (Ammenwerth et al., 2006)

9. Information Technology Adoption Model (ITAM) (Dixon, 1999)

10. Task Technology fit model (TTF) (Goodhue, 1995)

All the models have their own independent and dependent variables, but some of them have other commonalities that overlap. Hence, most previous theories adopted the technology acceptance model (TAM) to study the user’s intention for the acceptance of some technology. However, the success of VR for the purpose of learning depends on student acceptance and implementation of such technology. Adesina and Ayo (2010) in their study investigated 500 survey questionnaires and concluded that TAM is the most commonly used model for technology implementation.

Technology Acceptance Model

Davis (1986) introduced the Technology Acceptance Model (TAM), one of the most recognized models used to evaluate technology, particularly educational technology. The Technology Acceptance Model (TAM) was built on the Theory of

Reasoned Action (TRA) by Ajzen and Fishbein (1975) from the arena of social 63 psychology, which explains intention based on general human behavior. The TAM adopted the model from TRA and enlightens user acceptance or rejection of some informational technology. Based on both theories TRA and TAM, intention is the major factor of usage behavior, however, the usage behavior should be predicted by intention

(Amin et al. 2015; Davis et al., 1989; Mathieson, 1991). One of the biggest differences between TAM and TRA is that TRA includes subjective norm, social influence and social beliefs (Davis et al., 1989). Over time, TAM, the original model, has gone through many altered constructs and has been developed for different purposes, seeking special acceptance in technology (Davis, 1989; Davis et al., 1989; Venkatesh, 2000; Venkatesh

& Davis, 1996; Venkatesh & Davis, 2000).

TAM has been applied to a variety of diverse technology use disciplines, including business (Bach et al., 2016), medicine (Handy et al., 2001), school counseling

(Anni et al., 2018) and a few studies in the educational context, like e-learning (Chang &

Tung, 2008; Tarhini et al., 2015). Moreover, Chen et al. (2012) suggest core TAM as a useful model in virtual reality studies, and, at the same time, it may be a useful theoretical framework for examining the factors driving college students’ use of virtual reality to better understand climate change and its effect on glaciers in a tropical area.

As mentioned by Martín-Blas and Serrano-Fernández (2009), many higher educational institutions have applied various technology devices and tools that students, as well as educators, can use to enhance students’ learning. In addition to investigating and evaluating a student’s impetuses to accept and use an innovative technology, (TAM) is also used widely across many disciplines to explain how and why people decide to 64 adopt different technologies (Davis, 1986). TAM is used for generating explanations for the factors of technology acceptance and has confirmed validity and robustness in explaining diverse technology contexts (King & He, 2006; Ma & Liu, 2004). Beliefs are defined as an individual’s expectations when performing a given behavior as to what outcome will be produced (Ajzen & Fishbein, 1980). The user’s acceptance can be explained by two beliefs: perceived usefulness and perceived ease of use. Perceived usefulness is a subjective belief and represents “the degree to which a person believes that using a particular system would enhance his or her job” (Davis, 1989, p. 320).

Perceived ease of use is defined as “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p. 320). The perceived usefulness is the strongest predictor of user acceptance based on several research studies (Davis,

1989). However, the key factors of TAM are in the belief that technology, like VR, will support students in improving knowledge, and the belief that using VR is easy to use for students (Davis et al., 1989).

Figure 3

Technology Acceptance Model; Source: adopted from Davis (1989)

In Figure 3, one’s attitude toward using a particular technology is a central feature that is influenced by perceived usefulness and ease of use (Saeed et al., 2008). TAM is comprised of 19 items that represent the different constructs, each measured on a 5-point

Likert scale. TAM split TRA’s attitude construct into two concepts: perceived usefulness

(PU) and perceived ease of use (PEU). For a better explanation of individuals’ intentions, Davis (1989) included three factors related to attitude in adopting technology: perceived usefulness, perceived ease of use and attitude toward technology. The predictor variables in this study were: a) Perceived Usefulness (PU),

Davis (1989) defined PU as “the degree to which a person believes that using a particular system would enhance his or her job performance” (p. 364). As reported by Subramanian

(1994), PU as a primary determinate had a significant correlation with attitude toward usage behavior in communication technology adaptation. Davis (1989) considered this 66 factor since it showed the extent to which technology will improve a person’s productivity or job performance. The following hypotheses were created:

H1: Perceived usefulness (PU) has a significant positive direct effect on college students’ attitude towards using (AT) VR for learning about climate change and tropical glaciers.

H2: Perceived usefulness (PU) has a significant positive direct effect on the behavior intention (BI) to use the VR for learning about climate change and tropical glaciers. b) Perceived Ease of Use (PEU).

One of the major determinants of attitude toward the use in TAM is perceived ease to use

(PEU) as a secondary determinant. PEU is defined as “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p. 320).

H3: Perceived ease of use (PEU) has a significant positive direct effect on college students’ attitude towards using (AT) VR for learning about climate change and tropical glaciers.

H4: Perceived ease of use (PEU) has a significant positive direct effect on the perceived usefulness (PU) of VR for learning about climate change and tropical glaciers. c) Attitude toward Use

According to Davis (1989) and Karjaluoto et al. (2002), attitude is a user’s desirability to use technology. For this study, it was college students’ interest in using VR for learning about the high mountain glaciers. Attitude is based on the salient belief which a student has about the significance of a given behavior, as well as their view and judgment about the specific technology: “Customer attitude is formed based on characteristic beliefs about the object and perceived importance of those characteristics in making the decision 67 to adopt” (Adesina & Ayo, 2010, p.7). Based on literature, a hypothesis related to students’ attitude is:

H5: Students’ attitude (AT) has a significant positive direct effect on behavioral intention

(BI) of VR for learning about climate change and tropical glaciers.

The model ultimately predicts and explains behavioral intention (BI) as an individual’s attitude towards using a VR headset and a 360-video about tropical glaciers.

The predictor variables in this study will be a) perceived usefulness (PU), and b) perceived ease of use (PEU). The criterion variable will be behavioral intention (BI) to use VR to better understand climate change. BI within the model is said to be determined by the following specific beliefs, perceived usefulness (PU) and perceived ease of use

(PEU). Many studies have confirmed that attitude is a direct determinant of BI (Liu et al.

2009). The criterion variable will be behavioral intention (BI) to use VR to better understand climate change. Suki and Ramayah (2010) stated for the TAM model that attitude is described as the arbitrating affective response between PU, PEU and BI in the use of technology.

According to Davis and Venkatesh (1996), it is important to emphasize external factors that will affect PEU and PU. Questions revolving around PU ask the user to identify to what extent they believe that VR/360 video could enhance their performance, effectiveness and productivity in students’ education about climate change and a geological formation that is going to disappear under the effects of global warming.

Whereas, questions about PEU ask the user to identify their beliefs about their control, freedom and ease in using VR. The above describes the original TAM model, designed 68 for static office and learning environments (Davis, 1986). Since TAM was designed, there has been a considerable advancement in VR technology and use of technology for fun and learning, which should be also considered. TAM is examined via several constructs. Firstly, perceived usefulness (PU) describes how much the individual feels using a technology system in question will enhance their performance on a task (Davis,

1989). Secondly, perceived ease of use (PEU) describes the effort the individual perceives would be involved in using this system (Davis, 1989).

A study by Zogheib et al. (2015) demonstrated that gender does not play any role in PU, AT and BI. However, on the other hand, PEU on AT is statistically significant for male college students. According to Mathieson (1991), TAM provides general information on a person’s belief about technology, and TAM does not contain any social variables. Hence, the modified TAM model designed for this study will contain two constructs added from the spatial presence experience scale (SPES) (Hartmann et al.,

2015) to fulfill students’ intentions to use VR for educational purposes when learning about climate change.

Spatial Presence

It is necessary to identify the difference between two concepts that are often conflated. Kim et al. (2017) claimed that immersion represents a technological appearance on one hand, while on the other hand, spatial presence is a heuristic and perceptive experience that often emanates from VR. This connection ensues from immersion because immersion can trigger spatial presence, and that spatial presence is highly dependent on immersion. Slater and Wilbur (1997) described immersion as the 69 physical state of being enclosed by an artificial environment and to be involved in a different reality in order to gain a new experience. Slater and Sanchez-Vives (2016) defined and explained differences between immersion and presence:

A subjective correlate of immersion is presence. If a participant in a VR perceives

by using her body in a natural way, then the simplest inference for her brain’s

perceptual system to make is that what is being perceived is the participant’s

actual surroundings. This gives rise to the subjective illusion that is referred to in

the literature as presence – the illusion of “being there” in the environment

depicted by the VR displays – in spite of the fact that you know for sure that you

are not actually there. (p. 5)

Biocca (1997) described presence as the idiosyncratic conscious impression of

“being there,” even when the actual user is situated in a different place. When immersion triggers presence, which commonly happens in VR or 360-video, the user will behave within the virtual environment that is displayed by a medium instead of the real setting

(Slater & Wilbur, 1997; Slater, 2009; Sundar et al, 2017). According to Tichon (2007), spatial presence is important in the process of learning. In a study by the same author, results showed that presence in a virtual training environment for delivery drivers can significantly improve practical implications in degraded road conditions. Hence, according to Hartmann et al. (2015), subjective self-reported measures are crucial to understanding students’ presence in VR, where they can experience environments, such as high mountain tropical glaciers in Colombia, without the discomforts of having been 70 exposed to an extreme environment where there is a lack of oxygen, cold temperatures, glacier travel, and an increased exposure to risk (Linxweiler & Maude, 2017).

The spatial presence experience scale (SPES) was built on a theoretical model of spatial presence by Wirth et al. (2007). It has eight items per subscale that are self- location and possible action (Hartmann et al., 2015). Accordingly, self-location items include four items and represent users’ feeling of “being there.” Biocca (1997) explained that self-location can infer that a user of VR, in this case a student, has a feeling that he or she is transferred from a real environment to the high mountains in Colombia. On the other hand, possible action items “dealt with users’ subjective impression that they would be able to carry out actions in the environment” (Hartmann et al., 2015, p. 5).

Furthermore, the students should have the impression that they are standing on the glacier or they are walking through vegetation of the tropical mountain region.

However, to better understand VR’s usefulness and the intention to use it in educational settings, it is important to investigate how much students are feeling they are on Santa Isabel glacier in Colombia or have the impression that they could be active in that environment.

Based on the proposed literature, the following model was developed for this study (see Figure 4), as well as the following hypotheses.

H6: Possible action (PA) has a significant positive direct effect on college students’ attitude towards using (AT) VR for learning about climate change and tropical glaciers.

H7: Possible action (PA) has a significant positive direct effect on perceived usefulness

(PU) of VR for learning about climate change and tropical glaciers. 71

H8: Self-location (SL) has a significant positive direct effect on perceived usefulness

(PU) of VR for learning about climate change and tropical glaciers.

Figure 4

Hypothesized VRTAM model

According to Holden and Karsh (2010), there are several general guidelines and research questions that can be suggested to improve the TAM model for a specific interest. The following guidelines, developed for future work on TAM in health care from Holden and Karsh (2010), were modified and used for this study:

1. With added new variables, it is necessary to test the model. For this study case,

self-location and possible action are added variables.

2. Beliefs elicitation has been used in the educational settings to identify the

importance of the TAM variable and additional variables.

3. College students are the representative sample size that were used to test the

final model.

4. Longitudinal studies using TAM were conducted among different individuals

and groups.

Hype Cycle

Modern technology, including the integration of 360-degree video, also known as

VR, has proven to be effective in educational and school settings around the globe. A variety of researchers have reported the advantages of using VR in educational contexts, such as ameliorating learning outcomes (Lin et al., 2013), increasing student motivation and engagement (Sattar et al., 2019; McMillan at al., 2017), and increasing knowledge retention and awareness (Pérez-López & Contero, 2013). However, many educators and organizations use VR for an environmental experience and for teaching specific subjects related to outdoor surroundings. Nowadays, there are many educational lectures offered on VR, available for everyone to use easily. Thus, students can have a chance to use modern technology tools for understanding a specific topic. The level of familiarity with educational technology among students currently entering the system of higher education is superior to those who entered 5 years ago.

A graphical representation (see Figure 5) of the newest emerging technology trends by Gartner (Hype Cycle) has been considered as an effective tool to learn the trend of the use of technology globally (Frenn & Raskino, 2008). Hype cycle is split into five phases. The first phase is overzealous adaptation, while the last phase is when the new technology finally gets adopted (Linden, Fenn, 2003). Based on the study from

Prinsloo and Van Deventer (2017), VR was one of the highest scored trend technologies, followed by Augmented Reality.

Figure 5

Gartner Hype Cycle for Emerging Technologies

Chapter 3: Methodology

Education is a field that is becoming increasingly improved by technology. The role of education in addressing current problems, such as climate change, requires this type of advanced teaching and learning with the use of technology. In order to examine the relationships between the variables and the use of the Technology Acceptance Model

(TAM) among college students, this study employed a correlational research design.

Furthermore, this design supported identifying predictors that impact students’ acceptance of virtual reality (VR) as a learning device to better understand climate change in the tropical mountain regions, such as Nevado Santa Isabel in Colombia. As stated by Creswell (2014), a correlational research design is used to define and measure the degree of a relationship between two or more variables. This research design, based on previous literature, was used for this study as an approach in order to answer some of the research questions. A quantitative research approach was utilized in order to investigate intention prior to actual use of VR technology devices by college students.

Quantitative research is a scientific approach for testing objective theories by understanding the interconnected relationships among variables (Creswell, 2014).

Therefore, it is necessary for students to accept VR by having a positive behavior toward using it and feel that VR is an easy and useful tool for learning about glaciers in tropical regions, while also having the intention of using VR in the learning process.

Davis’s (1986) TAM model appears to have the potential to determine students’ behavioral intention to accept and use virtual reality in a college setting. According to

Davis, Bagozzi and Warshaw (1989) indicated that the significant factors that predict the 75 actual usage of some technology are perceived usefulness and perceived ease of use. At the same time, external variables construct a substantial influence on the prediction. Moreover, attitudes are the connection between factors and intentions before the actual behavior (Fishbein & Ajzen, 1975). Based on the original TAM model (Davis,

1986), the research model in this study was modified with additional external variables identified in the literature, as well as from the elicitation study that was conducted in

Phase 1 and suggested from the previous studies. For this study, external variables were based on the spatial presence experience scale (SPES) that was built on the theoretical model of spatial presence by Wirth et al. (2007) and has eight items per subscale, which are self-location (SL) and possible action (PA) (Hartmann et al., 2015). The final model in this study was named VRTAM (see Figure 6).

Figure 6

VRTAM model

Based on the model in the Figure 3, adopted from Davis (1989) and Harmann

(2015), external variables were influencing the perceived usefulness (PU) and attitude toward use (AT). The main concepts of the original TAM model are perceived usefulness 76

(PU), perceived ease of use (PEU), attitude toward use (AT), and behavioral intention to use (BI). To understand the influence of external variables that were defined after the elicitation study (Phase 1 on internal beliefs, intention and attitude), TAM also suggests that perceived usefulness (PU) and ease of use (PEU) are essential factors in predicting and explaining VR use (Davis, 1989). The TAM model explains various multiple external factors that people consider before accepting and using technology. Several studies have shown that external variables contribute to both a greater understanding of why students choose to use technology in education, as well as a better grasp of what impacts PU and

PEU.

Research Questions and Hypotheses

The research questions below were used to inform the study:

1. Do college students think the use of technology as virtual reality will impact students’ learning outcomes related to climate change and tropical glaciers?

2. Do college students intend to use virtual reality applications for their future learning and understanding climate change in tropical regions?

3. Does the VRTAM model predict an intention to use virtual reality among college students?

After conducting the literature review, which suggests that spatial presence plays an important role in predicting the behavioral intention to use VR in educational settings to better understand climate change, the researcher for this study developed the following hypotheses: 77

H1: Perceived usefulness (PU) has a significant positive direct effect on college students’ attitude towards using (AT) VR for learning about climate change and tropical glaciers.

H2: Perceived usefulness (PU) has a significant positive direct effect on the behavior intention (BI) to use VR for learning about climate change and tropical glaciers.

H3: Perceived ease of use (PEU) has a significant positive direct effect on college students’ attitude towards using (AT) VR for learning about climate change and tropical glaciers.

H4: Perceived ease of use (PEU) has a significant positive direct effect on the perceived usefulness (PU) of VR for learning about climate change and tropical glaciers.

H5: Students’ attitude (AT) has a significant positive direct effect on behavioral intention (BI) to use VR for learning about climate change and tropical glaciers.

H6: Possible action (PA) has a significant positive direct effect on college students’ attitude towards using (AT) VR for learning about climate change and tropical glaciers.

H7: Possible action (PA) has a significant positive direct effect on perceived usefulness (PU) of VR for learning about climate change and tropical glaciers.

H8: Self-location (SL) has a significant positive direct effect on perceived usefulness (PU) of VR for learning about climate change and tropical glaciers.

The model ultimately predicts and explains behavioral intention (BI) as an individual’s attitude towards using a VR headset and a 360 video about tropical glaciers.

The predictor variables in this study were a) perceived usefulness (PU), and b) perceived 78 ease to use (PEU). The criterion variable was BI to use VR to better understand climate change. BI within the model is said to be determined by the following specific beliefs,

PU and PEU. Many studies have confirmed that attitude is a direct determinant of BI (Liu et al., 2009). Suki and Ramayah (2010) stated for the TAM model, attitude is described as the arbitrating affective response between PU, PEU and BI for the use of some technology.

Population

As a result of the interaction between technology and education, changes in the school system are evident, both in the classroom and in distance learning. The most significant impact is reflected on the students. According to Privitera and Alhgrim-

Delzell (2019), a population can be determined as any group of interest. According to

Creswell (2005), a population is a group of individuals with comparable features.

Participants selected for this study, based on APA (2009), are referred to as humans and as the accessible population, which were college students from 51 different universities around the globe, including Ohio University, University Centre in Svalbard, University of

Alicante Spain, National University of Colombia, as well as many others. The study was announced through social media and through previous instructors and faculty members with whom I had previously worked and personally known. Purposeful recruitment was used for both phases in order to get participants for this study. I actively recruited participants at Ohio University, while recruitment at the other universities was done through instructors who all had specific and detailed guidelines on how to provide a VR 79 headset to students, as well as direction on how to access the online platform

Oculus/YouTube.

The participants volunteered to watch the video (8 minutes long) using a VR headset or device that they own or chose to use for this purpose. After watching the video, participants took the online survey on Qualtrics. The video was a 360-degree projection of the tropical glacier in Colombia with Dr. Sevestre, a glaciologist, who served as the narrator and storyteller in the video (see Appendix A). Dr. Sevestre gave a short lecture and virtually guided the audience on a tour of the glacier that is going to disappear in 2020 (IDEAM). For this study, an announcement was distributed on social media targeting college groups specifically interested in VR. It is important to take notice of the time period during which data was collected, which happened to be during the

COVID-19 pandemic. This specific time period, during the pandemic, greatly influenced face-to-face interactions. Attempting to collect data in person was not a possibility, which was how the study was initially designed. During normal circumstances, students at Ohio

University who are interested in VR could quickly get access to the latest technology VR innovation at Ohio University’s Scripps College of Communication, Game Research and

Immersive Design (GRID) Lab that has operated since 2005. The GRID Lab provided significant support for this study in providing equipment for recording 360 videos and editing footage upon my return from Colombia.

Statistical G*Power analysis was used to define the minimum sample size required for this study. However, Kline (2015) stated that there is no simple rule about sample size. In order to fulfil the structural equation modem (SEM), Jackson (2003) and 80

Kline (2015) recommended a sample size ratio of 20:1. However, this study was based on the total items from two different construct models. There were 271 participants for the

Phase 2, yet after screening, the number came to 227 that fully completed the survey. For the Phase 1, 65 college students finished the survey.

Instrumentation and Measures

For collecting data, online questionnaires were used as the instrument, for both phases of the study, based on the Qualtrics platform provided by Ohio University. The survey for Phase 2 was comprised of the following sections: basic demographic information, VR ownership, VR experience, technological acceptance, and spatial presence. The first section of the survey collected demographic information and information regarding VR ownership for each participant (see Appendix x). This information was used to further extract data from the following outlined measures. The two defined measures integrated into the questionnaire were questions from the

Technology Acceptance Model (TAM) and the spatial presence experience scale (SPES) for the primary survey (Phase 2). The secondary survey (Phase 1) that was distributed was a salient belief survey (Ajzan, 2013). Each survey contained the same demographic questionnaire information: name of school, age, gender, home country, previous experience with VR and level of interest in a learning about climate change and tropical glaciers. As previously mentioned, this study was synthesized from two phases, Phase 1 and Phase 2, that were analyzed separately in order to address three research questions and eight hypotheses.

Phase 1 – Elicitation Study

This part of the research sought to determine the core beliefs students had about the use of virtual reality (VR) to experience a natural environment, such as a specific, previously unexplored area. In order to develop a Technology Acceptance Model (TAM), a crucial first step was to identify the core beliefs that existed among the target population (Ajzen, 2013; Ajzen & Fishbein, 1980).

For this study, I adapted Ajzen's (2013) study to develop the instrument that aimed at measuring both direct and indirect behavioral determinates. In order to create the instrument, I utilized the information gathered from Phase 1. The goal was to determine whether or not students consider VR as a suitable platform to cultivate a positive learning experience on tropical glaciers and climate change.

An elicitation study (Phase 1) was conducted before the Phase 2 questionnaire was designed and distributed. The study shed light on the salient beliefs of students in regard to the use of VR in higher educational settings. According to Downs and

Hausenblas (2005), because an elicitation study typically depends on the targeted survey population, it downplays a need to take into account subjectivity or intuitive belief statements. However, this kind of study is not consistently implemented in TAM research. I conducted an elicitation study to help determine these salient beliefs, since the final model VRTAM was not defined in the time of creating Phase 1. I also conducted the initial study to highlight why this kind of elicitation study can be beneficial for research that uses TAM as a model in the future. 82

For this stage of the study, I used purposeful sampling to select and recruit participants who were students in classes where I had been a guest speaker, or students with whom I had attended classes. Students who agreed to voluntarily participate in this study were asked to first provide demographic information, and then, to answer open- ended questions. These open-ended questions asked them to write about what comes to their mind about the usage of VR, as well as who they think should use VR in college settings.

Aimed at Phase 1, I developed the open-ended survey in Qualtrics, an online platform recommended by Holden and Karsh (2010). According to Privitera and

Ahlgrim-Delzell (2019), open-ended questions would allow the students for this study to give their responses in their own words without any word limit. These kinds of questions helped me to understand the students’ behavior and normative beliefs in more detail.

Each student was expected to conduct this open-ended question survey individually and in a free response structure. The students were asked to then highlight their perceptions of what constitutes the strengths and weaknesses of utilizing VR in an educational setting.

The survey also asked students to express three different aspects of their beliefs regarding the use of VR technology in education. First, they responded to questions that asked them to differentiate between who might approve or disapprove of the use of VR during the school year. These questions determined the salient normative beliefs that students have regarding the use of VR for educational purposes. Second, the students were asked to identify what factors they believe are assisting in the use or non-use of VR at schools. This part of this elicitation study was created for the purpose of understanding 83 control beliefs. The third section looked at the students’ behavioral beliefs in the use of

VR in education. To determine the salient behavioral beliefs, I asked students to identify factors that they believed facilitate the use or nonuse of VR in educational settings.

In order to better understand the salient beliefs that students gained toward the use of VR in educational settings, I followed the following three steps in my data analysis.

First, I coded the results from the open-ended questions in the survey into meaningful categories. Then, I identified common themes and patterns related to key constructs in order to identify a possible form for VRTAM. Finally, I linked the findings to the first research question.

Based on the findings of this elicitation study and recommendations from the literature, I developed the instrument in the second phase of the study. Furthermore, the outcome of Phase 1 also showed if students had interests in using VR to learn about climate change and the disappearance of tropical glaciers.

Phase 2 – Final Study

TAM is comprised of 15 items that represent the different constructs, each measured on a 5-point Likert scale. First proposed by Davis (1986), TAM is used as a predictor and explanation of a user’s acceptance of various technologies. One successful method to predict and explain technology acceptance and future use is through a user’s intention to use (Davis & Venkatesh, 1996). This model has been tested many times and is recognized as a reliable instrument; importantly, it has also shown promise within testing the acceptance of technologies in outdoor and extreme environments (Nikou &

Economides, 2016). The model ultimately predicts and explains behavioral intention (BI) 84 as an individual’s attitude towards using VR. BI within the model is said to be determined by the following specific beliefs: perceived usefulness (PU) and perceived ease of use (PEU). Questions revolving around PU ask the user to identify to what extent they believe VR could enhance their performance, effectiveness and productivity, whereas questions about PEU ask the user to identify their beliefs about their control, freedom and ease in using VR enviroment. The above describes the original TAM model, designed for static office and learning environments (Davis, 1986). Since TAM was designed, there has been a considerable advancement in educational technology and use of technology for fun and learning. Participants in this study were asked to respond to each of the 15 items using a 5-point Likert scale from 1 (totally disagree) to 5 (totally agree). The total of each external variable was used to explain and predict the acceptance of VR for environmental interpretation and intention of using this kind of device. In addition to this model, the 2 variables self-location (SL) and possible action (PA), each with 4 items, were added to the final model (Hartmann et al., 2015) in order to explain spatial presence.

Ethical Protection of Research Participants

Prior to conducting research, the nature of quantitative, as well as qualitative, studies indicate that the interaction between researchers and participants in a study must be ethically considered, as they are personally involved in different stages of the study.

According to Berg (2002), the participants have to be informed about the purpose of the study and the potential risks to them, especially when involving sensitive issues.

Therefore, any research that involves human subjects must be reviewed by the 85 institutional review committees, called institutional review boards (IRBs), to help prevent researchers from inflicting potential harm on both researchers and participants. Before conducting research, researchers must submit the consent form to the IRB committee.

The consent form serves as a social contract between researchers and participants. In other words, when participants sign the consent form, they have provided their consent to let researchers become involved in their life experience (Berg, 2002). Furthermore, a research study collects considerable amounts of information about participants’ personal lives, as well as information about their families. In a case where someone’s identification appears, it can potentially lead to a problematic situation (Shank, 2006). All of the data gathered was confidential, and participants’ personal information was protected. For this study, there were no monetary incentives offered to participants.

However, participation in this study could be beneficial in raising awareness about climate change and giving the participants an experience that they may find helpful in their own research.

Data Collection Procedures

After receiving IRB approval for Phase 1, the data were collected using the

Qualtrics online platform. After the coding procedure was complete, the data were analyzed with SPSS 26. Prior to applying for IRB approval, a pilot version was sent to a small sample of people that I did not include in the final version that was later distributed.

A pilot study was developed in order to measure the reliability of the items. For Phase 2, the process was repeated. 86

In order to complete Phase 2, it was necessary to expose students to the virtual environment of the Santa Isabel glacier in Columbia. To achieve this, a 360-video was created with Premier Pro software with footage that was collected in the fall of 2019 in

Colombia. I used a 360 One X camera and a Zoom H 4 audio recorder to assemble the video and audio material on one of the last tropical glaciers, located at a height of 17,000 ft. The video about the tropical glacier was distributed to different colleges around the globe with the use of an Oculus platform where I uploaded the video. The participants for

Phase 2 voluntarily watched the video, which was approximately 8 minutes long, using a

VR headset. After watching a video, participants took the online survey on Qualtrics. The video was a 360-degree projection of the glacier in Colombia with a narrative lecture provided by a glaciologist, Dr. Sevestre. There were a few steps in the process of conducting Phase 2. First, before participants partook in the VR experience, they were informed of the purpose of the study and asked to provide their consent to participate.

Further, the questionnaire was thoroughly explained to both the participants and the VR crew on site, professionals whom I had previously known.

Every participant received the informed consent form prior to filling out the questionnaire and watching the video. Special equipment was provided to some of the participants in the form of a VR headset since I did not have access to many people due to the COVID -19 restrictions involving face-to-face interactions. I also monitored some participants with the use of video call while they watched the video in the event that something did not work, or in case participants did not feel comfortable while viewing the video. In other instances, research assistants, who were familiar with me and with the 87 study, monitored students in a similar way. However, I was unable to monitor the majority of participants. Most of them chose their own device and completed the process on their own. In total, 25 VR headsets, model Oculus Go, were sent to several universities with which I was in contact and who agreed to help for this study. They were trained in advance on how to operate the VR and became familiar with the entire process involved in conducting the study.

Data Analysis

The data acquired from the online questionnaire were exported from Qualtrics to

IBM SPSS Version 26 and Rstudio in order to be analyzed. The demographic information was summarized, and descriptive statistics were utilized to understand the sample in detail. Structural equation modeling (SEM) was used to test if the model fit with the proposed model and to answer the research questions. Incomplete data from participants were removed and not used in the analysis. To identify outliers, the Mahalanobis distance was used (Mertler & Vannatta, 2002).

New variables for each construct of the Technological Acceptance Model (TAM) were computed using SPSS 26, and descriptive statistics were run to gain general insights into the data. To measure scores of variables, multiple items were assessed on Likert scales. Therefore, to test the reliability of these, Cronbach's Alpha was used. To test the above hypotheses, bivariate correlations were run to examine whether relationships were positive or negative. This statistical test did not provide any reference to causation.

Statistical null and alternative hypotheses were created from the hypotheses above. The magnitude of the relationship was identified within this test, and generally relationships 88 were explained based on Cohen: relationships are small at r = .1, relationships are medium at r = .3, and there is a large relationship above r = .5. A correlation of 0 indicates there is no relationship. Whether the number is positive or negative indicates the direction of the relationship between the variables. The direction and strength of the relationship are two distinct properties. From this test, the direction of relationships, the strength of relationships and effect sizes can be identified.

The first research question asked, “Do college students think the use of technology as virtual reality will impact students’ learning outcomes related to climate change and tropical glaciers?” The elicitation study (Phase 1) was conducted to identify students’ beliefs as predictors for using and not using VR in an educational setting. The students’ experience was analyzed to explore how VR can be used in educational settings for students to learn issues related to climate change and tropical glaciers. Students’ salient beliefs were ascertained through behavioral outcomes, normative, and control factors that revealed the advantages and disadvantages of VR use. The next few steps in data analysis occurred in order to answer this research question. The results from the open-ended questions in the survey were coded into meaningful categories followed with identification of common themes and patterns related to key constructs.

The second research question developed was, “Do college students intend to use a virtual reality application for their future learning and understanding of climate change in tropical regions?” In order to predict the behavior intention to use VR, it was first necessary to identify a regression equation. Second, it was important to find the most influential variable among all variables in predicting BI, in other words, to identify 89 significant path coefficients (β). Further data analysis used correlation and descriptive analyses to determine the possibility of significant relationships between VRTAM variables. Path analysis determined the extent to which variables predicted intentions and answered all the hypotheses statements.

Through SEM (Structural Equation Modeling), the third question was analyzed and answered: Does the VRTAM model predict an intention to use virtual reality among college students? For this, all variables and constructs from the study’s model were included in the analysis to find a model fit statistics and parameter estimates. In doing so, there were a few indicators: Chi-square/degree of freedom where the value less than three implies a good fit, Goodness of Fit Index (GFI), Adjusted Goodness-of-Fit Index (AGFI),

Normalized Fit Index (NFI), Non-Normalized Fit Index (NNFI), Comparative Fit Index

(CFI), Standardized Root Mean Squared Residual (SRMR) and Root Mean Squared Error of Approximation (RMSEA). However, with the third question with SEM, I checked to see if model was consistent with the data in this study.

Techniques for Ensuring Reliable and Valid Data

Creswell (2014) shed light on the importance of reliability and validity in conducting the study. They were used as instruments to provide “an accurate assessment of the variable and enable the researcher to draw inferences to a sample or population” (p.

180). Furthermore, reliability is a very important process for building the theory in quantitative research (Creswell, 2014). According to Gulliksen (1950), the idea of reliability comes from a measurement theory, where the true score is measured with 90 random errors that cause fluctuations in the measurement. These errors degrade the relationship between true and observed scores.

Internal Consistency Reliability

According to Gabrenya (2003), internal consistency reliability is the coefficient that assesses the inter-relatedness of all items in a test or survey. In other words, all items oblige one function in a survey. Individual items must fit together and measure the same thing in a test (Gabrenya, 2003). For instance, a measure of attitude for this study about the use of VR might have items that produce a similar response. The collection of these items produces a total score which was intended for construct. There are three main ways to measure reliability: Cronbach's alpha, split-half, and Kudar-Richardson 20 (KR-20)

(Gabrenya, 2003). For this study, Cronbach’s alpha was primarily used to evaluate internal consistency of the instruments and to secure the reliability of the study. Crano and Brewer (2002) stated that the Coefficient alpha is “a measure of the hypothetical value that would be obtained if all of the items that could constitute a given scale were available and randomly put together into a very large number of tests of equal size” (p.

41). The original reliability of this instrument for AT was 0.95 based on many studies, while PEU was 0.94 in many studies that examined the use of different technology tools.

Furthermore, for BI, the original reliability of the scale was 0.86, PU was 0.98 (Segars &

Grover, 1993; Szajna, 1996). A pilot study was conducted with ten students at Ohio

University. Based on their feedback concerning the instrument, procedure and approach, the instrument was revised, especially in regard to their understanding of the questions.

Validity

According to Messick (1989), validity is a “judgment of the degree to which evidence and theoretical rationales support the adequacy and appropriateness” (p. 13). In other words, it is a continuous process and an aspect of clarification and interpretation of a measure. Polit and Beck (2012) stated the importance of an appropriate item sample for the construct that will be measured in an instrument. For this study, specifically the evaluation of the instrument’s content validity, a few experts from Ohio University’s

Writing Center reviewed and provided feedback to assist in developing an instrument that would provide more trustworthy information.

Construct Validity. Crano and Brewer (2002) claimed that construct validity is a

“test of whether or not the hypothesized construction plausibly exists” (p. 48). For this study, the data were collected directly from the participants and therefore presumed accurate. The studies (for Phase 1 and Phase 2) received approval from the IRB, and the surveys were distributed directly from me. Participants for this study were not asked to have any prior knowledge or any specific skills prior to taking the survey. Confirmatory factor analysis (CFA) was carried out to determine factorial construct, and structural equation modeling (SEM) was used for model comparison and hypotheses testing.

In addition to what was previously mentioned, external and consequential are also aspects of construct validity. The external component looks at the degree to which external variables play a role in the construct that is being tested and the impact they have on assessment scores. The consequential component of construct validity is comprised of

“evidence and rationales” (Messick, 1985, p. 746) in the evaluation of the consequences, 92 both deliberate and unintended, of how scores are interpreted and used. For this study, it was crucial that the target population, in this case college students, had an equal opportunity to participate. The way in which they were informed and invited was a key piece of the entire research. Predictive validity is when the purpose of a study is to predict behavior. The major concern in this case was predictive validity.

There were a few important limitations that were considered for this study and are explained in more detail in Chapter 5. The most important limitation regarding predictive behavior intention was the question of how to explain why such a relationship occurred between factors in the theoretical model.

Chapter 4

This study aims to create experiences based on virtual reality (VR) 360 content, set in one of the fastest-disappearing environments on Earth: the Santa Isabel Mountain,

Nevados National Park in Colombia, home to one of the last glaciers of South America and a myriad of endemic species. This study also looked at how VR can help to transform education on climate change and bridge the knowledge-action gap among the younger generations.

In order to understand and learn what predictors guide students’ intention to use

VR for educational purposes, I used two phases to collect data for this study. First, I coded and analyzed the data from Phase 1, which I collected from an online open-ended survey. Second, after creating an educational VR experience about one of the last tropical glaciers in Colombia, I exposed students to the eight-minute VR lecture using different

VR technology devices that will be elaborated upon later in this chapter. Finally, I conducted an online survey for the students that were accepted to participate in this experiment and the study. Phase 1 data collection will be reported first with response rate and demographic data, followed by research question one. After that, Phase 2 will be fully analyzed and reported for the second and third research questions. Participants with missing responses were omitted from the analyses. Furthermore, to confirm there is no violation of the assumptions of normality, linearity, and homoscedasticity responses, all responses, as well as variables, were tested and examined. The summary of findings will be presented at the end of this chapter. 94

Phase 1 – Elicitation Study

Data Collection and Response Rate for Phase 1

For Phase 1, data was collected using an online survey (through Qualtrics) sent via email and social media, using a purposeful sampling technique. The survey for Phase

1 was adopted from previous research studies (Ajzen & Fishbein, 1980; Ajzen, 2013).

Email and social media messenger were used to invite students to participate in this study and to provide answers about their experience in using, or inexperience in using, VR in educational settings through a series of open-ended questions.

I used open-ended questions that included a demographic section, previous VR device experience, behavioral outcomes, normative referents and control factors related to VR education. A total of 110 students were invited to participate in this study, but only

65 responded to the survey. After screening the data, it was determined that 62 participants could be included in this phase, which I coded manually and independently.

The participants in the elicitation study were comprised of 62 college students (56.5% male and 43.5% female) from nine different universities around the globe. The majority of students (79%) that participated in this phase were from Ohio University. While the remaining 21% of participants came from other colleges, they were mostly from

European universities.

Even though this study only considered college students, in terms of age, it presented a very broad range from 20-52 years old, with a mean age of 31 years.

Regarding previous use of VR, 59.7% of students reported that had had experience with 95

VR, while 40.3% of students had never used VR. In this phase, however, they only expressed their opinion since the focus of Phase 1 was salient beliefs.

The students’ responses in a series of open-ended questions were recorded and saved on Qualtrics, Ohio University’s software platform. Furthermore, a content analysis was performed after the survey was closed. This IRB approved survey was opened in the beginning of the spring semester, 2020 for approximately one month. However, salient beliefs that were elicited in Phase 1 were merged with Phase 2 to better understand students’ needs and intention of using VR for learning about climate change.

Phase 1 Analysis

To understand, predict, and describe a broad scope of behaviors, many different theories have been used, such as the theory of reasoned action (TRA; Ajzen & Fishbein,

1980; Fishbein & Ajzen, 1975), the theory of planned behavior (TPB; Ajzen, 1991; Ajzen

& Madden, 1986), and the technology acceptance model (TAM; Davis 1989). In all of these theories, the key to understanding all constructs (attitude toward the behavior, subjective norm, perceived behavioral control, behavioral intention, etc.) is knowing the salient beliefs. First, salient behavioral beliefs are obtained to define the attitude toward the behavior. Second, to explain the subjective norm, salient normative beliefs are identified. Third, salient control beliefs are implicit to detained perceived behavioral control. Furthermore, to understand what the participants’ salient beliefs are, it is important that their responses reflect the first thing that came to their mind while answering the open-ended questions, such as “What do you think would be the advantages of using VR in educational settings?” 96

In order to identify all the models of salient beliefs for this study, I piloted an elicitation study that was developed and conducted among representative college students worldwide during spring semester of the 2020 school year. However, this phase was developed in order to identify some of the beliefs as predictors of students with varying experiences in using or not using VR, as well as consideration of how VR can be used in educational settings.

Question 1: Do Students Think the Use of Technology as Virtual Reality will Impact

Students’ Learning Outcomes Related to Climate Change and Tropical Glaciers?

Many different projects and organizations around the globe have a mission to educate students and young people on the science of climate change and empower them to take action. The most endangered areas that have been affected by global warming, however, are at a vast distance from school locations, such as polar regions, high mountain environments, as well as many others. In order to understand students’ beliefs, it was important for me as a researcher to understand what the main source was that students planned to use to learn about and see the impact of the global temperature rising around the world.

The results from Phase 1 (the elicitation study) signified that a majority of the students surveyed in this phase intended to use YouTube, online internet sources, as well as VR if they had the opportunity to use it in order to learn about climate change and the impact of global warming during the next school year. Students highlighted the aspect that VR can be beneficial for educational purposes to learn about climate change around the globe with 95.2% fully agreeing and with 4.8% indicating that maybe VR could be 97 beneficial for these reasons. Furthermore, the elicitation study specifically identified students’ salient beliefs about device use, such as their beliefs about VR usefulness and thoughts on how VR could be used for educational purposes, ascertained behavioral outcomes, normative and control factors.

Device Use. The first block of questions looked at students’ use of VR, specifically if it is useful in education and how it can be used in the future. The following question was developed to understand salient beliefs of use or potential use of VR: “What are all the ways in which you use or you think you might use virtual reality during school year?”

The majority of students reported that they think that VR is useful for education.

Particularly, 38.7% of participants revealed that they intend to use VR for environmental education, 27.4% expressed the usefulness of VR as a device for virtual travel, and other participants indicated that they would use VR for fun, for gaming, and for new ways of exploring different subjects. In connecting with such findings, the participants have identified that VR can be a unique teaching tool that provides a solution for a class field trip. VR is especially essential to use when the subject being studied is located at a great distance. For example, one participant shared the following thought:

I might use VR as a means to teach my students by providing them a unique new

way of experiencing remote ecological sites and letting them focus on their points

of interest. The time-lapse technique with VR could really make a great solution

for my field of science. 98

Most students agreed that VR would have a greater impact on learning. Other participants believed that the use of VR could help students learn better. As opposed to just looking at pictures or reading a book about the subjects, VR can be a unique way to engage a diverse community in learning, especially when the settings are located in a challenging geographical context. Participants in the elicitation study also revealed that by using VR, they could acquire a more authentic experience exploring other cultures globally without being present in an actual environment. One participant addressed the important impact implementing VR in a learning environment could have:

I think it would completely change student engagement and learning for the

better. I can't always travel to visit other countries and their school systems, but if

I could have an experience of that through virtual reality, it would provide me

somewhat of a more authentic learning opportunity than what I would typically

have in a college classroom setting.

Participants also reported that VR may provide opportunities for them to experience being at some of the locations, such as the high alpine environments or some exotic locations, to which they may not be able to travel. Furthermore, some students also thought that VR had been useful for predicting and simulating the future condition of the

Earth, which could greatly aid in studying, analyzing and taking necessary actions. In addition to such findings, some students suggested that VR could be applied to simulate actual walking in a polar environment as a ‘tour’ or a new kind of scientific field trip. It could be used to show how an area, in this case a glacier, used to look, how is currently looks, and how it may look in the future. Seeing the progression of the life of a glacier 99 could be truly impactful for the viewer and a learner. In order to understand what drives students to think how VR could be used, it is necessary to understand how students see the possibilities of VR use. The following section specifically described how participants expressed the advantages and the potential drawbacks of VR use.

Behavioral Outcomes. To elicit affective beliefs (i.e., behavioral outcomes), respondents were asked to list the things they liked or enjoyed about VR if they had an opportunity to previously use it. In addition, they were also asked to indicate what they thought the disadvantages and possible threats of using it in the future were. I constructed the following question: “What do you see as the disadvantages of using VR during your next school year?” as well as the question “What do you see as the advantages of using

VR during your next school year?” The following table lays out the advantages and disadvantages of VR in educational settings (see Table 1).

100

Table 1

Salient Behavior Beliefs – Behavioral Outcomes

Salient behavioral beliefs The Use of VR in educational settings Advantage

New way of education Environmental experience Travel experience Safe environment Entertainment New technology New perspective

Disadvantage

Cost Lost human connection Technical issue Motion sickness Learning to use VR is not easy Not recognizing any disadvantage

Students identified several advantages of using VR in an education setting. They associated the benefits of VR as a new learning tool. They also recognized an advantage of VR as a device to experience environmental issues, such as travel experience. Many students also agreed that VR provides a safe environment. Since some travels or field trips require specific skills and knowledge, VR allows everyone access to have an authentic experience without being exposed to dangers, such as high altitude or coldness.

Many of the participants revealed that the use of VR in education, especially in learning about climate change, can change the students’ perspective. VR exposes learners 101 to subject matters like climate change, which could have an impact on developing people’s empathy, possibly leading to collective action being taken. One participant stated that VR can change students’ perspective in learning about climate change:

When it comes to climate change, I think that there are two major hurdles that we

have to get past as a society: (a) that it is human-caused and happening, creating

major changes that are irreversible; and (b) the question of how we as individuals,

communities, and countries can change the way we live without a negative impact

to the quality of life to adapt to and mitigate these changes. Both hurdles can be

addressed through education and exposure, leaving people knowledgeable and

sympathetic to the effects of climate change. This is why I think virtual reality is

an excellent medium to use as an immersive exposure to what is going on.

Tropical glaciers are a monumental visual example of the effect of our warming

planet. VR takes people to places they are unable to go: physically, financially,

etc. To care about an issue or place, people need to see and experience it. While

physically living or being somewhere will always trump a secondhand

experience, it is unrealistic (and damaging to those delicate environments) to

suggest everyone should go there. In this way, I think VR's biggest advantage in

addressing climate change is that it provides a new, more immersive medium that

I believe will affect viewers more strongly than a traditional video, photo, or text

by making them a stakeholder and participant in what is going on.

VR also can be used as a device for experiencing an environment that is dangerous to access, such the catastrophes. VR, thus, can potentially help people to visualize such 102 events. One student commented that VR “could provide visual illustrations of a situation, which could not be seen in real - life or have not happened yet. For example, a post- nuclear disaster or the disappearance of ice in the Arctic.”

On the other hand, students also identified some disadvantages that VR might have, such as the high price of a VR device and specific applications that are necessary for using VR. Furthermore, VR could possibly lead to lost human connection. By putting on a device and entering the virtual world, real human interaction could be lost. Technical issues were also mentioned as one of the biggest concerns that students had. Since nearly everything is based on technology and these devices are relatively new on the market, many issues arise on a daily basis. Some of the students shared that they had experienced motion sickness or cybersickness, a highly unpleasant experience that can happen to users. Finally, concern regarding how to operate the technology devices was one of the main disadvantages that students expressed in this part of the study. However, ease of use was used as one of the factors in Phase 2, which looks at how easy or difficult it is to operate some of the VR devices, one of the constructs for VRTAM model.

Normative Referents. When it comes to understanding groups that may potentially use VR (i.e., who would approve or disapprove of its use), participants shared their perspectives by answering the following question: “What types of individuals or groups would disapprove/approve or think you should not use a virtual reality set during the school year?”

Although most students expressed their support of the use VR in educational environments, they identified some potential groups who may be reluctant to use the 103 device. One of these groups included those who believe that a real-world environment can make students learn better, compared to a virtual world. One student shared the following opinion:

Groups who focus on being in the actual setting to learn better may not want to

use VR. For example, in the Outdoor Recreation industry, we are trying to get

more people outside and off of technology. Using VR might enable more people

to stay indoors and experience outdoors through NR instead of being in them

directly.

Other groups that they thought may oppose using VR included groups that by nature may be resistant or slow to change. Such groups included traditional instructors, religious groups, and conservative political parties. For instance, while liberals tend to be people open to change, students think that groups who are more conservative tend to be resistant to progressive change and are more cautious. In particular, older populations who are identified as having conservative values may resist progressivity. Moreover, elderly people who did not grow up with computer technology may find VR a greater hurdle for them to use.

Other individuals who might resist the use of VR are those who are afraid of leaving their comfort zone (teacher-oriented paradigm), those who are fearful of the potential negative impact of technology on students, and those who are skeptical of the notion of technology actually being able to improve the quality of teaching and learning.

Control Factors. This section explores the control factors of students’ use of VR during their next school year. The statement posed was: “Please list any factors or 104 circumstances that would make it easy or enable you to use virtual reality during your next school year.”

The students identified factors concerning their potential use of VR in their upcoming school year. About a third (35.5%) of the students reported that the biggest factor that would diminish their ability to use VR in education is the cost of the new VR devices. At the time of the survey, VR devices were still considered as expensive technical equipment. Some participants (12.9%) argued that the unavailability of the equipment could be another concern when it comes to students’ potential ability to use of

VR. Additional factors that followed included motion sickness and a lack of quality educational content that can be currently found on VR. However, the participants also identified factors that would enable them to use VR in the next school year. The majority

(56.5%) of participants advised that school-provided VR equipment would make it easier for them to use. Providing instructions on how to use VR was also found to be important to 8% of respondents. The rest of respondents advised that integrating VR into the curriculum and lowering the price of the devices would make it easier for students to use.

As previously mentioned, the availability of the equipment played a role in determining students’ intention to use VR in the next school year. According to one participant, “I can’t use it if it is not available or my technical devices don’t allow me to use VR technology.” Since VR is a costly tool, students were concerned about the availability of VR, and this may determine their choice of using VR in the next school year. Another student affirmed, “It would make it easy if the university could provide more VR to use for students. However, if the equipment is limited, it might be 105 challenging.” Furthermore, another student indicated that the use of VR will depend on its availability from the university. One graduate student commented:

Equipment used in developing videos and pics for VR, including VR devices,

may be a bit expensive, which would prevent its use on a regular basis in teaching

or research. Long term use of VR may lead to vertigo or sickness, and this may

limit or prevent the use of devices.

Students advised what universities could do to make this initiative happen. The university should have a commitment to integrate VR as part of the mandatory curriculum and provide the equipment as part of the learning devices. To avoid technical issues, the university could provide training for the instructors about how to use VR, and later the instructors could inform their students of its uses. One student shared their perspective on this:

First of all, it would make it easy if the department had the funds to provide

virtual reality experiences to their students. Secondly, I think faculty would

absolutely need training on how to implement it into the classroom. Also, I would

imagine that there would have to be research done to see what programs are

available that pertain to the curriculum and provide an enriching and meaningful

educational experience.

Another participant supported the argument that the use of VR should be part of the learning curriculum, and the content knowledge should be relevant to the study:

I would say it would be difficult if there was a lack of funding, if there was no

training provided for the professors to understand how to effectively implement it, 106

and if there was not any adequate virtual reality software that aligned to the

curriculum.

In addition, some students expressed their intention to use VR if the content knowledge available through VR was relevant to their interests. “The content is important. If the VR does not provide real settings or meaningful content, I would not want to use it.” Another participant added:

My academic focus is on statistical/psychometric analysis and quantitative

research. I need to be informed of how virtual reality can be useful for my studies.

Right now, I have all means I need for my studies and I will need some

information to convince myself that virtual reality can facilitate my work.

Students who participated in the survey believed that VR could be a useful device to learn about climate change and the impact of global warming worldwide. As a learning device, VR can offer several advantages and disadvantages as identified by the students.

They believed that VR could be a new learning tool to experience environmental issues, but also, in order to implement, they will need to learn more about how to use it for a specific use such as statistics. As VR is safe to access and use, students thought that this device could be a field trip option to experience the areas associated with danger such as high altitude or coldness. However, students also shared their perspectives about the disadvantages that VR can offer, including the loss of human connection, costly, motion sickness or cybersickness, and concerns related to technical issues.

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Phase 2 – Final Study

Descriptive Statistics

Sampling Procedure and Demographic Profile of the Participants.

Participants in both phases were identified through a purposeful sampling approach (that was explained in the previous chapter), asking them to complete an online survey through

Qualtrics, similar to Phase 1 but with a different IRB approval and questionnaire. For

Phase 2, students’ completion of a survey occurred after a VR experience using some of the technology devices, such as Oculus VR headset, Smartphone Cardboard, or some of the other accessible options they had available. However, since it was not manipulated, but because participants chose their own different technology devices to watch VR content about the last tropical glaciers, this could be called a pseudo-experimental study.

Social media platforms (e.g., LinkedIn, Facebook, and Viber) were used as recruitment tools as well as some personal connections for some students at other universities where I sent VR headsets. Video content was published on the Oculus platform and YouTube

VR. This pseudo-experimental study lasted approximately 25 minutes in total; the first part was watching the educational VR content followed by the second part, where participants completed the online survey.

Participants for Phase 2 study included a suitable sample of college students worldwide (N = 271). Because of missing data 44 cases were completely removed, of which 32 cases did not go further than the consent form, so I assumed these participants did not feel they met the requirements to participate in this study. Out of 44 students, 12 students didn’t finish the survey, even they though they indicated some experience after 108 watching the video. but still, these cases were withheld from further analysis. In doing so, the power estimate was not affected because there were missing values from a total sample size of N = 271 to N = 227.

The majority of participants were female with 52% (n = 120), followed by male

41.4 % (n = 94), and 5.7% (n = 13) self-identified as another gender. During the data collection period I was a graduate student and most of the students that I purposely chose for this study were also graduate students: graduate program (masters or doctoral) 63%, and undergraduate students represent 37% (see Table 2).

This study primarily examined the intention of using VR for educational purposes and learning about climate change, although it was crucial to learn it the participants had any previous experience using VR. According to Rogers (2010), compatibility dimensions between technology—in this case VR—and students' previous experience was important to investigate. Research suggests that past use of VR has positive influence on user’s behavior and beliefs as well on users’ intention and actual use and in many cases can develop spontaneous action for future use (Kim & Malhorta, 2005) (See the

Supplement Analysis of this chapter for more information). About 74% of participants said they had some experience with VR; however, 25.6% indicated that the VR video about the last tropical glacier of Colombia was the first experience of that kind. Students were from 51 different universities, with most from the US and reported they were from

35 different home countries (See Table 2 for more information about the sample). Most students used Oculus headset 27.3%, Smartphone-VR 52.4% as a technology tool to 109 participate in this study and to get the experience of VR education video about the last tropical glacier in Colombia, other students used desktop or laptop to access to the video.

Table 2

Demographic information for Phase 2

Features Participants Proportion (%) Female 120 52.0 Gender Male 94 41.4 Self-identification 13 5.7 Educational Undergraduate 84 37.0 background Graduate 143 63.0 Pre VR use No 58 25.6 Yes 169 74.4

The motivation and interest in learning about climate change can trigger a certain behavior and intention of using technology for educational purposes (Fishbein & Ajzen,

1975). An important element in the process of persuasion according to Fishbein and

Ajzen (1975) was behavioral intention. However, students’ interest in learning about climate change and disappearing of tropical glaciers can lead to the intention to act, and this behavioral intention could lead to particular conduct. In Phase 2, the term ‘interest’

(“Are you interested in learning about climate change?”) referred to the degree which explains how much students were keen to learn about one of the biggest problems that humanity is facing now. For this question, 81% of students were interested in learning 110 about climate change, where 17.2% were not sure, while only 1.8% of students reported that they do not have any interest in learning about climate change.

It is crucial to recognize that learning is not a replication or reproduction of any knowledge, but as stated from a constructive perspective, it is an active process where students as a learner concisely engaged (Dewey, 1913). For this study, I chose one of the last tropical glaciers of Colombia as a topic for VR experience. Thus, students’ interest in this topic and previous knowledge about the tropical glacier was observed. Frick (1992) stated that someone interested in a specific topic will lead to better engagement and possible future acts. However, not many students have previous knowledge about tropical glaciers, 60% of students said they had no previous knowledge, 20.7% who were not fully sure they know, but maybe they heard and learned something, and only 18.5% confirmed they knew about tropical glaciers, with most of these students being from

Colombia or in geology or glaciology field of studies (see Table 3).

Table 3

Knowledge and interest in climate change and tropical glaciers

Features Population Proportion (%) Interest in No 4 1.8 learning about Maybe 39 17.2 Climate Charge Yes 184 81.0 Do students No 138 60.8 know anything Maybe 47 20.7 about tropical Yes 42 18.5 glaciers

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Test of Reliability and Validity

Reliability. The reliability of the VR Technology Acceptance Model (VRTAM), was observed for each of the VRTAM scales: self-location, possible action, perceived ease of use, perceived usefulness, attitude toward use, and behavioral intention. In the

Phase 2 all of the final participants, after screening (N = 227), who voluntarily participated to watch the VR experience completed the VRTAM. SPSS and RStudio with mainly the “lavaan” package (Yves Rosseel, 2012) were used to examine the data.

This study was pursued using Likert-type scales and in that case, it is essential to calculate and report Cronbach’s alpha coefficient for internal consistency reliability for all scales that were used (Gliem & Gliem, 2003). According to George and Mallery

(2003), as well as Warner (2008), the following rules of thumb were applicable for the interpretation of Cronbach’s alpha: “ > .9 – Excellent,  > .8 – Good,  > .7 –

Acceptable,  > .6 – Questionable,  > .5 – Poor, and  < .5 – Unacceptable” (p. 231).

Table 4 shows the reliability coefficient for 6 items.

The range was from  = .75 to  = .91. After examination of reliability for this study the attitude toward use scale that is used from original TAM model had a

Cronbach’s  = .75, which was the lowest one but still indicates acceptable reliability. On the other hand, the perceived usefulness scale had a Cronbach’s  = .91 which according to George and Mallery (2003) is excellent reliability. Table 4 comprises scale items and the reliability coefficients of the scales of the VRTAM.

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Table 4

Cronbach’s Alpha () for Variables

Factors SL PA PEU PU AT BI PASL Number of observed 4 4 4 4 4 3 8* variables Cronbach  of .882 .845 .838 .912 .757 .815 .925* observed variables Note: * PASL is combine SL and PA

In order to achieve better consistency for this study I collapsed all SPES items in one internally consistent total scale variable called PASL. In a study done from Harmann et al. (2015), self-location (SL) and possible actions (PA) were showed as separate variables with high correlation (r = .81) among them; however, the authors considered also the possibility of marginalization of these two scales. Tabachnick and Fidell (1966) suggested that since there were very high correlations for SL and PA, they should not be included in multiple regression analysis. Since the bivariate correlation is more than 0.70,

I used both models in the Figure 7; with marginalized self-location and possible action called PASL as well as separate variables SL and PA for this study.

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Figure 7

Hypothesized model VRTAM

Modified model from original VRTAM

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Exploratory Factor Analysis

An exploratory factor analysis was examined due to a lack of standardized scales for measure student’s intention to use VR and to review the construct validities of all models that were used in this study. According to Schaubhut et al., (2009) this analysis defines whether the items measure what they intend to measure after grouping correlated variables.

At first, analysis of the TAM model was separated from the SPES scale, and after that, VRTAM was inspected. Prior to these analyses I used Kaiser-Meyer-Olkin (KMO) test on the items in order to measure sampling adequacy and suitability for factor analysis. Bartlett’s Test of Sphericity was also used in this analysis in relation to the students use of VR.

For the TAM the value of KMO was 0.763, while for SPES was 0.50, and for

VRTAM, that combed both models were 0.804. Furthermore, Bartlett’s Test of

Sphericity showed statistical significance among all scales, p < .001, with chi-square statistics for TAM of 310.302, SPES 286.223, and VRTAM 735.453. All these implied that the model VRTAM has all requirements satisfied for a factor analysis.

Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) was conducted to ensure adequate measurement models. To assess the better model, I compared two separate CFA models.

The first model was proposed that PA and SL are separated as variables while model 2 has joined variables PA and SL in one 8 item variable called PASL. 115

For the study I used for the first model six latent factors, based on VRTAM research framework (Table 5): Perceived ease of use (PEU, 4 items), perceived usefulness (PU, 4 items), behavioral intention (BI, 3 items), attitude towards use (AT, 4 items), self-location (SL, 4 items), possible actions (PA, 4 items). In the second, after modification, self-location and possible actions were combined, resulting in five latent factors.

First Model - The Hypothesized Model

Hair et al. (2006) stated that regression estimates (also called loadings) of latent to observed variable should be above 0.50. In regard of that statement concluded analysis showed that all observed variables/items in this study ranged from 0.482 for AT3 (Q31) item to 0.86 for PU1 (Q22) item. However, this reveals that not all constructs were fit for overall examination of construct validity (see Figure 8).

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Figure 8

Confirmatory factor analysis for the Hypothesized Model

Note: The Pearson correlation among latent variables are shown on the double arrow.

One-way arrows are shown the pattern coefficient linking the latent factors (see Figure

8).

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Table 5

Final confirmatory factor analysis results of construct variables

Variables Code Factor Variance Loadings Extracted Factor 1: Perceived ease PEU1 .719** of use (4 items) PEU2 .778** PEU3 .755** .567 PEU4 .766** Factor 2: Perceived PU1 .861** Usefulness (4 items) PU2 .885** PU3 .819** .720 PU4 .830** Factor 3: Behavioral BI1 .782** Intention to use (3 items) BI2 .860** .620 BI3 .698** Factor 4: Attitude towards AT1 .520** (4 Items) AT2 .855** .341 AT3 .482** AT4 .837** Factor 5: Self-location (4 SL1 .777** items) SL2 .761** SL3 .856** .658 SL4 .837** Factor 6: Possible Actions PA1 .856** (4 items) PA2 .776** .686 PA3 .723** PA4 .696** TOTAL 24 .561 items

Note: ** Significance for the Factor Loadings

As per the results the model chi-square 휒2(215) = 543.546, p < .05. Chi-square— as an index of absolute model fit—is statistically significant, therefore indicating that the model did not fit the data adequately. 118

In order to improve upon Model 1, an examination of the modification indexes suggested that the additions between pairs of error would improve the model fit. The results indicated that all factors had positive correlation. Since the chi-square statistic is a weak measure of overall model fit, other goodness of fit indicators were used to examine, such as Comparative Fit Index (CFI) 0.90, Tucker-Lewis Index (TLI) 0.88, and the Root

Mean Square Error of Approximation (RMSEA) 0.082, with 90% CI [.074 - .091]. Thus, the model did not fit the data well.

First, modification indices (MI) were observed to see how much the chi-square value for the model would drop if the changes were made in the model based on modification indices parameters. As per the MI, several changes were suggested.

Correlating AT - Factor’s items Q29 and Q31 with MI = 94.129, indicated highest value of drop in chi-squared if allow to covary. Based on this information suggested by MI, changes were made by correlating between Q29 and Q31. This modification was applied in respecified/second model. The second model, based on the graph (see Figure 9), showed evidence of high correlation between PA and SL with 0.99. Despite this, for the second model I used PASL as a joined factor of two variables as it shown in Table 6.

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Table 6

Goodness of fit analysis-CFA of model 1 and 2 (N=227)

Finals Models Hypothesized Model – Respecified Model – First Model Second model Factors 6 5

Items remain 23 23 Chi-Square 543.546 432.102 Df 215 219

p-value .000 .000 GFI .824 .859 CFI .906 .939 TLI .889 .930

RMSEA .082 CI [.074 - .091] .065 CI [.065 - .075]

SRMR .082 .062

Making changes in model did not improve the overall model fit, χ2 (219) =

432.102, p < .05 (see Table 6). The chi-square value reduced; however, not enough to make the model fit acceptable. The second model fit tests suggested some improvement,

(CFI =.94, TLI = .930, RMSEA = .065, 90% CI [.065, .076]). Hence, the (CFI) that was used in order to compare the fit of a model to one with no covariance among the variables is higher than in a model 1, where CFI values closer to 1 indicate better fit. Many authors, such as Browne and Cudeck (1992), concluded that RMSEA has estimates below 0.05 refer to close fit, between 0.05 and 0.08 acceptable fit, 0.08 to 0.10 mediocre fit, and above 0.1 poor fit (MacCallum, Browne, & Sugawara, 1996).

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Figure 9

Model 2 confirmatory factor analysis after modification

In summary, two models were examined through confirmatory factor analyses.

There were 21 observed items and 6 latent variables. The traits only model (Model 1) lacked adequate data fit. After modification, there was some improvement in the fit indexes. This pair of variables has shared variance and this variance had communalities beyond the shared factor variance. It was found to adequately fit the data; however, there were problems in several of the model coefficients. The chi-square was found to be 121 statistically significant again. Therefore, when comparing to Model 1 and Model 2, the chi-square and RMSEA values reduced and the IFI, CFI, and TLI scores were a little closer to 0.95.

Question 2: Do College Students Intend to Use Virtual Reality Applications for their

Future Learning and Understanding the Climate Change at the Tropical Region?

In order for universities and colleges to create the next generation of scientists, developers, and entrepreneurs, it is imperative to follow innovations in modern technologies and implement them in educational system worldwide. Prior to implementing a new technology such as VR it was crucial to ask: “Do college students intend to use VR?”, especially for an important topic such as climate change, and areas

(e.g., glaciers) that are disappearing.

According to Davis (1986) students’ behavior is characterized by their intention to use VR, which is dependent on the perceived ease of use or how much is difficult or easy to use VR and perceived usefulness of the VR. However, to fully explain the intention of virtual experience one additional construct was included beyond the TAM model: having a special presence or a sense of feeling that one has been in a virtual world.

As seen in Table 7, the mean for perceived ease of use was 4.17 (SD = 0.64), perceived usefulness 4.69 (SD = 0.52), attitude toward use 4.32 (SD = 0.68), self-location

4.27 (SD = 0.73), possible action 4.27 (SD = 0.72) and behavioral intention 4.55 (SD =

0.65). Furthermore, after marginalized self-location and possible action, a new variable

PASL had mean 4.27 (SD = 0.70). The variables were measured on a 5-point Likert scale 122

(developed from Likert, 1932), with a range from 1 to 5, with 1 being “Strongly

Disagree” and 5 being “Strongly Agree”. Based on the descriptive statistics that are shown in Table 7, all means were greater than 4 for both exogenous and endogenous constructs, which could indicate ceiling effect. Ceiling effect occurs when the most of participants answered in a highly positive manner. However, this effect could reduce statistical power on correlations between variables and impact the assumptions of the analyses.

Table 7

Descriptive Statistics for Direct Measure VRTAM Factors N Mean (SD) Minimum Maximum

Exo1 Self-Location (SL) 227 4.27 (.73) 1.00 5.00

Exo2 Possible Action (PA) 227 4.27 (.72) 1.00 5.00

Exo3 Perc. Ease of Use (PEU) 227 4.17 (.64) 1.00 5.00

End1 Perceived Usefulness (PU) 227 4.69 (.52) 1.00 5.00

End2 Attitude toward use (AT) 227 4.32 (.68) 1.00 5.00

End3 Behavioral Intention (BI) 227 4.55 (.65) 1.00 5.00

*Exo4 *Self-Location & Possible 227 4.27 (.70) 1.00 5.00 Action (PASL) Note: * Joined Self-Location and Possible Action in one factor

In order to define normality, skewness and kurtosis were examined. Because a

Likert scale can never generate truly normally distributed data, this study had non-normal distribution among items. Clason and Dormody (1994) stated that the non-normality of 123 single Likert items: “It is difficult to see how normally distributed data can arise in a single Likert-type item. The data will frequently be skewed, and often these items do not capture the true limits of the attitude” (p. 34). Inspection for outliers ensued through the

Mahalanobis distance. A few outliers were detected but I decided to keep them for the analysis.

Analyzing the data in the Phase 2, significant correlations between all variables were noticed (see Table 8). The magnitudes of the pairwise correlations indicated relatively strong relationships among pairs of variables. Pearson product-moment correlation signified that the highest correlation occurred between self-location and possible action (r =. 849, p < .001) and the lowest between attitude and perceived ease of use (r =. 313, p < .001). A variance inflation factor (VIF) detected very high correlation between the two variables of spatial presence (i.e., PA and SL), with VIF = 3.882, while the other VIF values ranged between 1 and 2. In addition to concerns raised during the

CFA (see above), this level of multicollinearity between PA and SL suggested it was reasonable to collapse the two variables into a single scale. The highest variance inflation factor was reduced in the new linear regression model, to VIF of 1.849. Partial plots among variable pairs were used to inspect existence of homoscedasticity. After examining assumptions, linear regression was the next step to be conducted.

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Table 8 Correlation between VRTAM Factors and Behavioral Intention BI AT PEU PU PA SL

Behavioral Intention (BI)

Attitude toward Use (AT) .566**

Perc. Ease of Use (PEU) .425** .313**

Perceived Usefulness (PU) .643** .568** .537**

Possible Action (PA) .416** .581** .334** .571**

Self-Location (SL) .465** .567** .322** .587** .849**

(PASL) .458** 597** .341** .602** x x ** = p < .001

For the Phase 2 linear regressions were conducted, in order to test the study hypotheses and assumptions. Combination of direct effects between predictors and outcomes that regression explains is evidence of the existence of mediated relationship between those variables (Baron & Kenny, 1986). Table 9 displays these relationships.

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Table 9

Multiple Linear Regression Testing the Relationship between Intention Using Direct Measures

Variable (n=227) B SE B β t p

Attitude Toward Use .293 .057 .296 4.793 .000***

Perceived Usefulness .521 .074 .475 5.893 .000***

Perc. Ease of Use .114 .058 .112 1.969 .050**

Possible Action -.148 .085 -.163 -1.735 .084

Self-Location .134 .084 .151 1.607 .110

Attitude Toward Use * .288 .061 .299 4.692 .000***

Perceived Usefulness * .530 .089 .422 5.982 .000***

Perc. Ease of Use * .109 .058 .108 1.883 .061

Self-Location & Possible -.010 .061 -.011 -.171 .864

Action (PASL)*

Notes: R2 = .489; ** p <.001 (*Model with combined PASL; R2 = .481; ** p <.001.)

Once significant relationships between VRTAM variables were established, a multiple regression was carried out to investigate whether attitudes, perceived usefulness, self-location, and possible action be good predictors for students’ intentions to use virtual reality in educational settings for learning about climate change.

Attitude toward use and perceived usefulness were shown to be strong predictors of behavioral intention. Overall, directly measured VRTAM variables accounted for

48.9% of the variance in college students’ intention (R2 =.489, F (5, 221) = 42.285, p 126

<.001) to use virtual reality in educational settings. Beta weights of each variables suggest contributions to the effect. However, PEU is close to be significant predictor of behavioral intention. After modification of the joined two variables, the regression suggested that the model explained 48.1% of the variance in college students’ intentions to use VR (R2 =.481, F (4, 222) = 51.538, p < .001).

Despite of modification that was done in second analysis, as better model was shown first model with separate variables of spatial presence explained 48.9% of the variance, where perceived ease of use was close to being significant predictor with p =

.0502, while in second model perceived ease of use was not significant p = .062.

Path Analysis

In order to observe potentially mediated relationships among variables, it is necessary to estimate a system of different equations. Path analysis as a form of structural equation modeling (Wright, 1921, 1923, 1934) was used in Phase 2 as a regression-based approach to define relationship between variables, because some variables appeared to mediate the relationship between others. A path analysis model was constructed using variable attitude toward use, perceived usefulness, perceived ease of use, possible action, self-location, and behavioral intention. The path diagram in the Figure 10 represents the hypothesized relationships, with results, between variables in the VRTAM model.

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Figure 10

Path diagram

Note: *= p <.05; **p < .01; ***= p < .001; Paths without results = p > .05

As per the results, the model chi-square 휒2(4) = 9.121, p= .058. Thus, the degree of freedom was positive, and the model is over-identified. The chi-square statistic was not statistically significant indicating that the model fit the data adequately. Goodness of fit statistics were also calculated in order to confirm model fit: (GFI = 0.987, RMESA =

.075, CFI = .993, TLI = .974, RMSEA 90% CI [.000, .141]). The path coefficient from perceived usefulness to behavioral intention had the strongest regression weight of .475.

On the other hand, the path from perceived ease of use to attitude toward use had the lowest regression weight of -0.003; therefore, the direct effect of perceived ease of use on 128 attitude was not statistically significant with p = .965. However, all other paths were statistically significant (see Table 10).

Table 10

VRTAM analysis of hypotheses

Hypothesis – β R2 p-value Relation path H1: PU  AT .351 .123 .000***

H2: PU  BI .475 .225 .000***

H3: PEU  AT -.003 .000 .965

H4: PEU  PU .376 .141 .000*** H5: AT  BI .296 .086 .000***

H6: PA  AT .381 .145 .000*** H7: PA  PU .180 .032 .046* H8: SL  PU .312 .097 .000*** Note: *=p < .05; ** p < .01; ***= p < .001

All seven hypotheses in this study were supported except for H3 (i.e., the PEU-

AT relationship) (see above). Perceived usefulness explains 22.5% of the variation for behavioral intention. However, this study found that students’ attitude and perceived usefulness played important direct roles in describing their intention to use VR (H2, H5).

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Question 3: Does the VRTAM Model Predict Intention to use Virtual Reality among

College Students?

At this point in time, students’ educational growth is directly dependent on technology, particularly in circumstances where students cannot be present physically in school spaces as has occurred during the COVID -19 pandemic. Hence, understanding technology acceptance among students is crucial to be studied as well as establishing and testing theoretical propositions that will explain acceptance and intention.

To answer the study’s third question, structural equation model (SEM) was used.

More specifically, I used the “lavaan”, “semPlot”, “lavaaPlot” and “DiagranneR” packages in RStudio and robust maximum likelihood procedures to estimate paths in a latent model. However, SEM is not just a “statistical technique but it integrates a number of different multivariate techniques into one model fitting framework. SEM integrates the various techniques such as measurement theory, factor (latent variable) analysis, path analysis, regression and simultaneous equations” (Thakkar, 2020, p. 113).

In Phase 2, the structural equation model was performed based on data from 227 students, on the twenty-three questions from 5 Likert-scale survey measuring, technology acceptance (TAM; Davis, 1986) and spatial presence (Hartmann et al., 2015). In order to test theoretical model for appropriateness, a few steps were developed. First, the model was specified, and model identification was determined. Next, all free parameters were estimated. Finally, model fit was assessed, and the model was modified to enhance the fit

(Thakkar, 2020). 130

The originally hypothesized model contained six latent variables. PEU was proposed to bring into play both a direct effect on variable AT and PU, an indirect effect on BI through AT. There was one mediation variable (AT) to influence BI. The endogenous variables (PEU, AT and BI) have error variables and also every measured variable associated with latent variables have error variables. VRTAM added external variables PA and SL. As measured variables, Q10 to Q13 belong to SL, Q14 to Q17 belong to PA, Q18 to Q21 belong to PEU, Q22 to Q25 belong to PU, from Q26 to Q28 belong to BI and from Q29 to Q32 belong to AT. The aim of this SEM analysis is to explain these endogenous variables, assess the quality of measurement, and improve the model (see Figure 11). Ovals indicated latent variables, while rectangles represented observed variables. A directional relationship between variables were explained using one sided arrow. On the other hand, covariances were explained with two headed arrows.

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Figure 11

Model 1 - SEM

Note: PEU path PU was 0.43, while SL on AT was -1.28

The first model (see Table 11) is over-identified (df = 219) and positive definite.

The chi-square value of 547.296 had a p-value of less than 0.05. The RMSEA (Steiger &

Lind, 1980) had a value 0.081 and 90% CI [.073, .090]), but smaller RMSEA (close to

.06 or below) is preferred since the number of free parameters increases, favoring more parsimonious models. The goodness of fit index (GFI; Jöreskog & Sörbom, 1981) had a value of 0.823 which should be greater than 0.95. So, these values indicate that the model is not a good fit. The (CFI; Bentler, 1990) was 0.906 (preferable is close to .95 or above) and normed-fit index (NFI; Bentler & Bonett, 1980) had a value 0.854. Among relative 132 fit indices, Tucker-Lewis index (Tucker & Lewis, 1973) had a value of 0.891 (should be close to .95 or above) and incremental fit index (IFI; Bollen, 1989a) was 0.907. The values did not meet preferable values therefore it was desirable to apply model modification.

As mentioned in CFA section, two factors (PA and SL) were highly correlated and that can cause problems in parameter estimation. High correlation between two factors can cause problems analogous to multicollinearity.

Table 11

Estimated Model 1

Regression Estimate C.R. p-value Weights Standardized (S.E.) PU ~ SL -.602 (2.097) -.287 .774 PU ~ PA 1.092 (2.103) .519 .604 PU ~ PEU .435 (.069) 6.344 .000** AT ~ PA .188 (.066) 2.824 .005** AT ~ PEU .006 (.069) .093 .926 AT ~ PU .732 (.077) 9.443 .000** BI ~ PU .367 (.140) 2.616 .092 BI ~ AT .432 (.142) 3.038 .153

The estimation results of SEM for Model 1 (see Table 11) suggested three significant direct effects. There were PEU (perceived ease of use on PU (perceived usefulness), PEU on AT (attitude), PA on AT and PU on AT. These results were in match 133 with some other studies that found similar results, such as Tan et al., (2012). However, since Model 1 did not achieve model fit a new model was generated and called Model 2.

Model 2 was modified by establishing a factor that joined the two factors SL and

PA. Observed variables from Q10 to Q17 belong to new factor called PASL.

Furthermore, in the Model 2, correlation between Q29 and Q31 also arose. Model 2 did not adequately fit the data, Chi-Square 휒2(221) = 433.141, p=.000, and these values get closer to .95; GFI= .824, NFI= .884, IFI= .940, TLI=.930, CFI=.939, RMSEA = .065,

90% CI [.056, .074]) (see Figure 12). However, even two paths were removed and created a new path between PASL, AT, BI and PU. All paths except PASL and BI were significant (p < .05). The model was improved from hypotheses perspective but not from model fit view.

Figure 12

Model 2 SEM Diagram and Path Diagram

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Figure 12 continued

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Table 12

Model 1 2 3 for SEM

Model df 2 SRMR RMSEA GFI CFI TLI AIC

Model 1 219 546.692 .067 .081 .823 .906 .891 8987.068

Model 2 221 433.141 .063 .065 .859 .939 .930 8868.902

Model 3 147 259.311 .051 .058 .894 .960 .951 7296.487

To reach an improved model, AT was removed from a model, because modification indices (MI) indicated high value and observed variables Q31 and Q29 indicated low value compared with other 0.43 and 0.48. Results reported above indicated problems with the measurement of AT. Many authors (e.g., Davis et al., 1996) have reported that attitude should be excluded from the parsimonious TAM since it only partially mediates the effect of perceived usefulness and perceived ease of use on behavioral intention, while some authors (e.g., Agarwal & Prasad, 1999; Kim et al.,

2009) have argued that attitude does not mediate the effect or other variables in TAM model. In order to find better model-fit, AT was removed from the model and the entire model (as recommended by David et al., 1996) showed better overall fit compared with model 1 and model 2 (see Table 12). Chi-Square 휒2(147) = 259.311, p=.000.

Furthermore, the results for Model 3 indicated GFI= .895, SRMR=.051, NFI= .912, IFI=

.960, TLI=.951, CFI=.960, RMSEA = .059, 90% CI [.046, .069]).

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Figure 13

Model 3 Diagram SEM

Note: PEU to PU was 0.45, while PASL to BI 0.036

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The estimation results of SEM were presented in the Table 12.

Table 13

Estimated Model 3

Regression Estimate C.R. p-value

Weights Standardized (S.E.)

PU ~ PASL .485 (.052) 9.282 .000**

PU ~ PEU .446 (.055) 8.127 .000**

BI ~ PASL .036 (.079) .449 .653

BI ~ PU .707 (.070) 10.169 .000**

Figure 14

Model 3 Path diagram

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Supplemental Analysis

Rogers (2010) stated that students' familiarity of using VR is important to be analyzed in order to better understand interactions between technology and users.

According to a study from Kim and Malhorta (2005), previous use of VR has positive influence on user’s behavior and beliefs as well on users’ intention and actual use. In this study, 74.4% of students had some experience of using VR; most students had experience from a class demonstration, or they personally own some kind of VR devices. On the other hand, 25.6% of students expressed that the first VR experience occurred through the video about one of the last tropical glaciers of Colombia. For this study, there was not a significant difference on behavioral intention between groups that had experience using

VR before (M = 4.577, SD = 0.654) and the group that used the VR for the first time (M

= 4.494, SD = 0.667), t (225, 97.202) = -.836, p = .404.

To better understand if these demographic groups differed, a one-way analysis of variance was conducted to evaluate the relationship between gender and behavioral intention to use VR. The ANOVA was significant, F(1,224) =4.131, p = .017, 2 =.047.

The strength of the relationship between gender groups and behavioral intention, as assessed by 2 (called partial eta squared), accounted for 5% of the variance of the dependent variable.

In order to test the differences in all primary variables based on the technology students used, there was a significant multivariate effect reported. Multivariate ANOVA

(MANOVA) was used to determine whether there was any distinction on VR acceptance between the level of students, either graduate or undergraduate level. There was a 139 significant difference between undergraduate and graduate when considered jointly on all variables, with Wilk’s L=.942, F (5,221) =2.719, p=.021 partial 2 =.058. Furthermore, a separate follow-up ANOVA was conducted for each dependent variable from this study and each ANOVA was evaluated at a Bonferroni-adjusted alpha level of .0125. First, there were significant differences between undergraduate and graduate students on perceived usefulness, F (1, 225) = 7.746, p= .006, 2 =.033. Second, there were no significant differences between undergraduate and graduate students on spatial presence.

These differences were primarily driven by the possible action self-location (PASL), F

(1, 225) = 4.750, p = .030, 2 =.021. On the other hand, there were no significant differences between undergraduate and graduate on either behavioral intention, F (1, 225)

= .853, p= .357, 2=.004 or PEU F (1, 225) = .000, p= .991, 2 =.000.

Table 14

Descriptive Information for Educational Level

N BI PEU PU PASL

Undergraduate 84 4.50 (.61) 4.17 (.66) 4.56 (.57) 4.14 (.75)

Graduate 143 4.58 (.67) 4.17 (.64) 4.76 (.76) 4.35 (66)

To approach any VR content, it is necessary to use of VR hardware. For this study, “The last Tropical glacier” video used the Oculus Platform and YouTube platform.

However, the hardware plays an essential role in that the VR experience. For this study,

Oculus Go, Smartphone, and Laptop were the primary devices used by participants. 140

Table 15

Descriptive Information for Device Users

N BI PEU PU PASL

Oculus Users 62 4.83 (.35) 3.96 (.38) 4.91 (.22) 4.81 (.31)

Smartphone Users 119 4.47 (.75) 4.17 (.64) 4.64 (.57) 4.13 (.64)

Laptop Users 26 4.37 (.61) 4.25 (.72) 4.59 (.52) 3.91 (.76)

In order to investigate what factors drive the most while using some VR devices, the one-way ANOVA was conducted to compare the main effects type of technology devices that was used for watching the video and interaction effect between variables.

Post hoc comparisons utilizing the Games Howell test show that the mean scores were significantly different for technology hardware, spatial presence, and ease of use. The most significant main effect at the .05 for the technology devices that students used in this experiment. The main effect for students type of technology yielded an F ratio F(2,

204) = 33.952, p=.000, indicating a significant difference between Oculus users (M =

4.81, SD = 0.310), laptop users (M = 3.91, SD = 0.767) and smartphone users (M = 4.13,

SD = 0.647 ) on spatial presence factor (PASL). On the other hand, PEU Oculus users (M

= 3.96, SD = 0.383), laptop users (M = 4.25, SD = 0.726), and smartphone users (M =

4.30, SD = 0.643) on perceived ease of use, F (2, 204) = 7.042, p=.001.

As shown in the Figure 15, based on canonical scores Oculus users tended to have to highest spatial presence but on the other hand for them the use of VR device was not 141 easy as much as for students that used smartphone or laptop (see structure of the Figure

15).

Figure 15

Canonical scores and the structure for the device users

Summary

The elicitation study results were used to guide the development of items in the instrument used to collect data in the second phase of the study, as well as in creating a video for the final stage. Students think that VR can be a useful learning tool to learn about climate change and tropical glaciers. Students identified that VR can be a great 142 exposure device to experience environmental issues. As the environment where the glaciers are located might not be safe to access or the distance might impede students’ ability to visit, VR can provide an alternative to travel in experiencing climate change firsthand. Students identified that VR could be utilized to 'tour' a place to simulate actual walking around in the real place; therefore, the use of VR can change students’ perspective. It evokes people’s empathy which could lead to collective actions. Using

VR, students could directly observe the change in glaciers that could have an emotional impact on the viewers and learners. However, the participants also disclosed some disadvantages that impeded their ability to use VR, including the availability, the cost, and the negative effects that the devices can have, such as motion sickness.

The Phase 2 began with presenting descriptive statistics results such as demographic profile of the participants and previous experience of using VR. Reliability and validity were examined with a Cronbach’s alpha, an exploratory factor analysis and confirmatory factor analysis with comparing 2 models. For the both models the was found to be statistically significant. However, in model 2 the chi-square and RMSEA values reduced and the IFI, CFI, and TLI scores were a little closer to 0.95.

In order to answer second research question, it was necessary to identify a regression equation and examine path analysis that determined the extent to which variables predicted intentions. In doing so this analysis answered all the hypotheses statements. The chi-square statistic for path analysis performed not statistically significant what indicating that the model fit the data adequately. The best predictors of behavioral intentions were perceived usefulness, as well as attitude toward use and were 143 shown to be strong predictors of behavioral intention. Overall, directly measured

VRTAM variables accounted for 48.9% of the variance in college students’ intention (R2

=.489, F (5, 221) = 42.285, p <.001) to use VR. Furthermore, all seven hypotheses in this study were supported except for third hypotheses (PEU-AT).

For the third research question, structural equation model was constructed using

RStudio, mainly lavaan, semPlot packages, and robust maximum likelihood procedures to estimate paths in a latent model. The estimation results of three models, that the last model (Model 3) showed as the best. The results for Model 3 indicated Chi-Square

휒2(147) = 259.311, p=.000; GFI= .895, NFI= .912, IFI= .960, TLI=.951, CFI=.960,

RMSEA = .059, 90% CI [.046, .069]). Finally, this chapter was concluded with supplemental analysis.

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Chapter 5

In the end, we will conserve only what we love; we will love only what we understand, and we will understand only what we are taught.

—Baba Douim, Senegalese Environmentalist, 1968

In this study I examined virtual reality (VR) as an educational technology with the potential to be used for learning about climate change and disappearance of tropical glaciers in educational settings engaging young adults to act and conserve natural resources. This study aimed also to inspire the students to reconnect with nature, give them a certain human perspective on climate change, and a sense of respect for women and men fighting to study and preserve such fragile ecosystems. It also aimed to help the students to become passionate problem-solvers and moreover give them a certain mental flexibility to tackle major challenges in various settings.

Distance education is a process that focuses on personal growth through interaction among a group of students and an instructor with the use of technology in an environment where face to face is impossible. Typically, the type of environment that climate change and global warming impact the most occurs in areas that are far removed from urban settings. These natural areas are obscured and difficult for students to visit and learn from directly. Educating students in a non-traditional, more-experienced based setting is crucial in order to see and better understand current issues that the world is facing these days, such as glacial shrinkage, loss of sea ice, and accelerated sea level rise.

The use of technology in education, especially learning about climate change has been an important topic for many educators, as well as professionals in the field. This 145 study showed that VR technology has the ability to engage students as well as provide them with meaningful information and experience about climate change.

This chapter will review findings and it is divided into few segments. First, I began this chapter by looking back on the summary of the study followed by the significant findings of Phase 1 and Phase 2. Second, I moved to discuss how deeply VR technology can be integrated into our educational system. Third, limitations and challenges pursuing this study presented and finally I concluded this study with recommendations for future research that can help to integrate technology into both our society and educational settings to learn about climate change and disappearance of the tropical glaciers.

Summary of the Study

This study examined college students’ salient beliefs and intentions of using VR in order to use and to learn about climate change and tropical glaciers such as Santa

Isabel a Colombian glacier. Our planet has been warming steadily for over a century and the preponderance of evidence points to human action as the main contributor to this change (Hansen et al., 2010). Many glaciers in the coming decades are likely to completely disappear especially smaller ones (Rabatel et al., 2018a). In order to initiate, change, find solutions and slow the process of global warming students need to be as aware of the problem as possible. The continuous improvement of technology has brought remarkable change and 360-degree videos also known as Virtual Reality (VR) have potential to bring the environment to the students, since it can provide a close to real-life situation. 146

For this study a VR - 360 video educational experience of one of the last tropical glaciers in Colombia was created in order to investigate students’ intention and acceptance of this modern technological information delivery system. In the video, Dr.

Heïdi Sevestre is telling a story about one of the last glaciers in Colombia, in the same time, educating the person who is watching the video to understand that glaciers in the tropical regions that are so rare, so unique and what we can potentially do to preserve them from extinction. However, these glaciers should not disappear in silence. The tropical glaciers of Colombia still hold precious scientific information that could help us better understand the retreat of other tropical glaciers in the rest of Latin America, Africa, and Indonesia.

As time moves on it will become more and more critical for educators and facilitators to decide how to provide experience for the students to see that we are that are fighting the last battle against climate change. Students should see that the last tropical glacier of Colombia will fully disappear in the next few years. For example, the glacier that I filmed and used for educational VR experience lost its battle against global warming and is no longer a glacier, during the time of concluding this chapter (see Figure

16).

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Figure 16

Nevado Santa Isabel, sector Conejeras

Note: Photos made by Jorge Luis Ceballos

Such unforgettable experiences should instantly connect anyone with the most remote, extreme, and fast-changing environments on Earth. These transformational journeys could also deeply change a person’s perspectives about humanity and planet

Earth and inspire them to act.

Many studies have confirmed the capability that VR can carry in educational settings. As Chen et al. (2012) suggested, TAM should be a useful model in virtual reality studies, in the same time it may be a useful theoretical framework for examining the 148 factors driving college students’ use of virtual reality for better understanding of climate change and effect on glaciers in a tropical area and this study fully supported that argument. A study by Zogheib et al. (2015) demonstrated that gender does not play any role on PU, AT and BI. Conversely, the study finding appeared contrary to the study by

Zogheib et al. (2015) which reported a statistically significate difference among female and male VR users on behavioral intention.

According to Slavova and Mu (2018), students who used VR to learn in required subjects such as the history, demonstrated better performance over those who listened to content and watched slides. However, in this study students reported lack of peer communications as a disadvantage of the use of VR and that it was difficult to take notes while using VR headsets. Phase 1 of the study fully supported the findings from Slavova and Mu (2018), where students reported as one of disadvantages the lack of human connection when using of VR.

Ma, et al. (2016) created an Augmented Reality (AR) anatomy education tool for students to explore human body from a different perspective and intersection.

The authors hypothesized that the immersion, personalisation, and novelty of an AR system would help students to learn and be more motivated to learn. Lee and Moscardo (2005) supported the use of Augmented Reality (AR) as an educational tool that could be effective in schools. However, this study supports these statements because students think that VR is beneficial in learning and students intend to use VR in the future for educational purposes.

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Purpose Statement

The purpose of this study was to investigate the learning effectiveness of a pedagogical approach involving virtual reality (VR) technology in higher education to raise awareness of climate change in high mountain tropical region. It also examined students’ perceptions of the benefits of virtual reality to apprehend climate change. This study explored the ways that students reacted to this technology through salient beliefs as well as intention to use VR for educational purposes.

The following research questions guided the study:

1. Do college students think the use of technology as virtual reality will impact students’ learning outcomes related to climate change and tropical glaciers?

2. Do college students intend to use virtual reality application for their future learning and understanding climate change in tropical regions?

3. Does the VRTAM model predict an intention to use virtual reality among college students?

Review of the Methodology

This study used a correlational research design in order to examine the relationships among the variables, to identify predictors that impact students’ acceptance of virtual reality , and to investigate the use of the Technology Acceptance Model,

(Davis, 1989) among college students for a better understanding about climate change in the tropical mountain region. Based on the original TAM (Davis, 1986), the proposed research model was modified with additional external variables identified in the literature 150 using the spatial presence experience scale (Hartmann et al. 2015). The model that was used in this study was called VRTAM.

In order to predict the behavioral intention to use VR for learning about climate change, this study identified significant path coefficients between variables (possible action, self-location, prescribed usability, perceived ease of use, attitude toward use, and behavioral intention). Path analysis, a regression-based approach, determined the extent to which variables predicted intentions and answered all 8 hypotheses statements. A structural equation model was constructed to estimate paths in a latent model and to propose the best model fit among all factors.

Major Findings

Phase 1 & Overview of Research Question 1

Elicitation study (Phase 1) was conducted to identify students’ beliefs as predictors for using and not using VR in an educational setting. Students’ experience was analyzed to explore how VR can be used in educational settings for students to learn issues related to climate change and tropical glaciers. Students’ salient beliefs were ascertained through behavioral outcomes, normative, and control factors that revealed the advantages and disadvantages of VR use. The findings indicated that the majority of students believed that VR is a useful tool for education. Most students expressed that they intend to use VR to learn about climate change and the impact of global warming during the next school year.

Students identified several benefits of VR as an educational device. VR can be used as an effective tool to learn environmental education and to experience virtual 151 travel. VR can be a fun tool for gaming and for exploring different subjects. VR can be a unique solution for class field trips, particularly to learn about subjects that are located at a great distance. Students expressed that learning about climate change through VR can change students' perspectives. By being exposed directly to such experiences students seemed to develop empathy that may encourage them to partake in a change in their society.

Students recognized that VR can have some disadvantages that affect students' intention to use the device in the next school year including high price, loss of human connection, issues related to technical issues (difficulties), and motion sickness. Students also identified factors that enable them to use VR in the next school year. The school should integrate VR into the curriculum supported with relevant content knowledge. As

VR was costly especially with a specific application, the school should ensure the availability of the device and provide adequate training on how to use VR to avoid technical issues and motion sickness.

In addition to the advantages and disadvantages of VR, students shared potential groups who might be reluctant to use the devices. The groups included individuals who believe that real-world environments can help students learn better, individuals who by nature may be resistant to change (traditional instructors, religious groups, and conservative political parties), an elder group who didn’t grow up with computer technology, individuals who are afraid of leaving their comfort zone (teacher-oriented paradigm), individuals who are afraid about the negative impact of technology on 152 students, and individuals who are skeptical that technology can improve teaching- learning quality.

Phase 2 & Overview of Research Questions 2 and 3

After conducting Phase 1 and creating the VR - 360 experience, Phase 2 occurred among 227 students from around the globe. Furthermore, the technology in Phase 2 study was manipulated, in a sense, because participants (in this case, students) chose their own technology devices to watch VR content about the last tropical glaciers, so this study got the connotation of pseudo-experimental study. In order to achieve better consistency for this study I collapsed all SPES items in one internally consistent total scale variable called PASL because the correlation between the PA and SL variables showed a very high relationship (r = .81).

Confirmatory factor analysis (CFA) was conducted to ensure adequate measurement models. The hypothesized and respecified models were observed to determine the better model. However, the respecified model/second model after combining two variables into the PASL variable showed as a better fit, but still leaving room for improvement: χ2 (219) = 432.102, p < .05. The Chi-Square value decreased a bit, but not significantly, to make model fit acceptable (CFI =.94, TLI = .930, RMSEA =

.065, 90% CI [.065, .076]).

Multiple regression was carried out to investigate whether attitudes, perceived usefulness, self-location, and possible action are good predictors for students’ intentions to use virtual reality in educational settings for learning about climate change and at the same time provided an answer to research question 2. In the first analysis with all 153 predictors, attitude toward use and perceived usefulness were shown to be strong predictors of behavioral intention to use VR for educational purposes. Overall, for directly measured VRTAM variables, the results of the regression indicated that the model explained 48.9% of the variance in intentions of college students (R2 =.489, F (5,

221) = 42.285, p <.001) to use virtual reality in educational settings. However, perceived ease of use is close to being a good predictor of behavioral intention but not statistically significant. In order to test the hypotheses for this study, path analysis was used. The results for the model chi-square 휒2(4) = 9.121, p=.058, was not statistically significant, which indicated good fit for the path model (GFI) 0.987, (RMESA= .075, 90% CI [.000,

.141], CFI = .993, TLI = .974).

All eight hypotheses in this study were supported except for hypothesis 3 (i.e., the

PEU-AT relationship (see Table 10). In perceived attitude toward use, the study findings revealed that perceived ease of use had no effect, so hypothesis was not rejected.

Perceived usefulness explains 22.5% of the variation for behavioral intention and has positive influence on it (Venkatesh & Davis, 2000). This indicated that students plan to utilize VR because they recognize that it will help them to see and understand better influence of global warming on tropical glaciers. Additionally, perceived usefulness explains 12.3% of the variation for attitude toward use, while perceived ease of use explains 14.1% of the variation for perceived usefulness (see Figure 17).

However, this study found that students’ attitudes and perceived usefulness played an important part and can have positive relationships in describing their intention to use VR (H2, H5). 154

Figure 17

Hypothesis Diagram among all Variables for VRTAM

Note: Red line represent non-significant path between PEU and AT

Furthermore, PEU operated through PU and had positive indirect effect on BI.

Many previous studies also confirmed this (Davis, 1989; Davis et. al., 1989; Yusoff et. al

2009). This means that students accept to use VR to learn about environment, not just because they know it is beneficial for them but also because its functional and practical.

To answer the study’s third question, structural equation model (SEM) was constructed to examine the goodness of fit of the hypothesized structural model by attempting to improve TAM model in 3 different examinations. Hypothesized model-first model contained six latent variables. PEU was proposed to bring into play both a direct effect on variable AT and PU, an indirect effect on BI through AT. There were two mediation variables (AT and PU) to impact BI. However, the hypothesized model did not achieve satisfactory model fit (p value = .000, p <.001).

To reach improved model, AT was removed from a model, since modification indices (MI) indicated high value. Many authors such as Davis et al. (1996) reported that 155 attitude should be excluded from the parsimonious TAM, since it only partially mediated the effect of perceived usefulness and perceived ease of use on behavioral intention, while some authors (Agarwal & Prasad, 1999; Kim et al., 2009) on the other hand, argued that attitude did not mediate the effect or other variables in TAM model. In order to find better model-fit AT was removed from a model and entire model as David et al.

(1996) recommended and it showed better overall fit compared with model 1 and model 2

Chi-Square 휒2(147) = 259.311, p=.000. Furthermore, the results for Model 3 indicated

GFI= .895, NFI= .912, IFI= .960, TLI=.951, CFI=.960, RMSEA = .059, 90% CI [.046,

.069]. According to Arbuckle (1997), sample size will often cause inflation of chi-square, making a statistically significant index. Generally, the third model is the best model and it explained students’ intention with 53% (R2) of the variability to use VR for learning about climate change.

Different devices among college students played an important role on students’ presence of “being there”. Oculus users tended to have to highest spatial presence, but on the other hand, for them the use of this VR device was not easy as other students described using a smartphone or laptop.

Practical and Theoretical Implications

The established framework in this study, combined from two different scales

(TAM and SPES) which allowed me to discern students’ intention to use VR in order to learn about climate change and endangered environment in high mountain regions.

VRTAM final model with two variables PA and SL marginalized into one, proved a better tool for measuring immersive technology acceptance among students. However, 156 attitude toward use was not as good a fit in this model. Remodeling questions that measure attitude could better explain this variable or perhaps fully excluding attitude from the measurement model is the better option. Otherwise, measurement value would not be good and accurate in the way we usually expect.

From a practical standpoint, I believe that VR will continue to become part of students’ educational resources to understand climate change. Hence, it is important for educators and designers/developers to understand students’ beliefs and intention of using for learning purposes. VR headsets such as Oculus provided the best experience of virtual word but on the other hand it was not easy device to be operated, especially for those students with less experience and interest in technology. When considering VR technology in curriculums from an educational standpoint, the concern is that students will have difficulty reaching the same outcomes in the same way they would have if they had done the field trip. Cost of owning VR device was one of the main apprehensions and barriers to full implementation in educational system as well. Despite these drawbacks, in addition to making educational programs better, integrating VR technology into educational programs also has the potential to increase learning. With recent VR technological advancements, it is possible for programs to carry large quantities of information into the VR environment where it can be accessed by students and educators. This technology should be used to help students connect with the environment in the backcountry, rather than escape from it as some suggested.

This also suggests that with the use of technology, educators could use videos and pictures to teach difficult skills that are taught in advanced programs. Safety would be 157 increased also with using VR rather than actually going into the field, at the same time educators/instructors could easily evaluate the effectiveness of virtual trips through archives of information about each and every virtual experience or event and easily obtain feedback from users. For example, tracking how long a student stayed in a virtual experience, may determine that was the most interesting for them and many other questions can be answered.

The Challenge of VR Design for Education

One of the crucial components using VR for educational purposes is to consider the design of the virtual environment and storytelling for an instructional lesson. For this study I created the VR - 360 educational video and the main question that I asked myself was how to create and deliver an environment and tell the story that students can learn and get the experience of an environment that is losing a battle against global warming, in other words how VR experience could a make difference versus normal video.

Media production is the way educators and instructors can support efficient and creative use of technology in order to establish an effective and engaged learning environment for their students. Even though I had some experience, I found a challenge in post-production editing in the virtual reality and 360-video, especially in establishing high quality from different footage, stitching, stabilizing and color grading. In this process patience and organization have been most important, since chaotic file management can occur even before the video production had started. Making 360 - VR content is an extremely technical job, but the main point of this project, that is even more important, is 158 that the story we want to tell is impactful and how to tell a story in a short form and still have a learning and crafted story in the baseline.

As educators we can only seek to influence students’ feelings towards technology in the learning about climate change, not control them by condemning certain types of

“punishment”. If students feel comfortable entering into VR experience due to the fact that there is technology present, perhaps in the course of the class students’ mindsets about what they wish to accomplish will change to a more traditional view simply by coming in contact with these ideas. In order to succeed it is crucial to implement storytelling. In VR - 360 environment, two the most important components are the story and what is happening behind a student in peripheral vision. This is important because VR

- 360 video shifts a viewer to a participant since they are free to look in any direction they want.

To conclude this section, I would highly recommend prior to implementing VR -

360 video in an educational program it is important to learn about video production and to discover potential areas of impact and the value of the message that needs to be delivered.

Furthermore, for students to operate new equipment and to manipulate video files, it takes time, so it is important to include the time of a “test drive” into curriculum. In this process some students might struggle; on the other hand, some students quickly develop familiarity with the technology and should be leveraged as resources for other students still grappling with new technology. 159

Limitations

In consideration of the limitations surrounding the use of VR for learning about climate change context the complexity of VRTAM as a construct should first be noted.

TAM model proposed by Davis (1989) has been implemented in many existing studies which aimed to measure technology acceptance have fallen short by attitude that didn’t capture in this study proposed outcome, that attitude is good predictor of behavioral intention. However, construct without attitude would be a better fit for measuring students’ acceptance of VR for learning about climate change or improved measurement of attitude.

Another limitation for this study was that the data collection happened in the time that COVID - 19 pandemic made face to face interaction impossible to occur. Thus, I could not be present when the students used devices nor could another trained person who planned to provide VR headsets. Students who participated in this study, used VR devices without any observation from my side nor to participate in a controlled environment such as a lab how was proposed in chapter 3. Different students experience the interaction with VR in different ways; especially those that used VR for the first time.

On the other hand, students who have difficulty relinquishing technology cannot be forced to do so even if it can help them. However, this study only reached students with access to social media, or I knew personally, but not other groups of students who may not have been as familiar with technology. Thus, this also impacted sample size that should be higher for SEM. 160

Third, for this study a 5-point, the Likert scale was used, although some other studies have used and suggested a 7-point scale in order to provide wider options.

According to Lewis (1993), 7-point scales showed better and stronger correlations with t- test results. On the other hand, a 5-point scale is simple (Dawes, 2008), comprehensible for participants, and can increase the response rate (Babakus & Mangold, 1992).

Finally, it was possible that a few response biases occurred in this study from a participant's side and may have influenced survey responses since both surveys were self- reported. Climate change is a current issue and, in some ways, is a trend to talk, discuss, and to act to protect and preserve nature. There exists a possibility that social desirability bias occurred in a way where students may act as a responsible human being, to look good, even though they may act and believe differently. Acquiescence bias may have ensued, since I knew some of the participants, there was a possibility that they responded that they agree with statements, regardless of their beliefs, in order to fulfill my expectations.

Recommendations for Future Research

This study provides many ideas for future directions for research. From construct’s perspective it would be beneficial to include Phase 1 factors into Phase 2 such as to include normative belief and identify direct and indirect paths of all 3 salient beliefs.

On the other hand, pursuing a study only on participants that use VR headset and measure knowledge outcome can be constrictive. It is critical for educators to do more research into what types of VR technology effects students’ outcomes and experiences of understanding climate change. Furthermore, VR technology also has the ability to create 161 safer environment (the inherent risk that can occurred in the field) and from that perspective to include safeness as an external variable in VRTAM model to determine if it is a good predictor for behavior intention.

Despite many the many studies that have recognized the potential of VR in education, more research is necessary to determine the potential of using VR enhanced storytelling as a method of teaching and learning. Storytelling has been proven to be an effective method of teaching in various subjects such as Art, History, Social Studies and others. This study applies the ancient art of storytelling with the newest technological method of presenting information for learning about the current disappearance of tropical glaciers in Colombia.

This study used students as target population for understanding VR acceptance and intention to use for learning about climate change. However, future research could be conducted to observe and understand instructors/educator’s intention to use VR.

Furthermore, the data collected from educators could be used to compare with the data from students, as well as, for longitudinal studies among students and instructors.

The VRTAM model should be replicated in order to revise and validate the model, without attitude or review the questions and improve for the future survey. Since for this study outliers were not excluded, for the future research removing outliers can provide different outcome.

Conclusion

Juxtaposed between the insufficient education resources and knowledge about climate change and tropical high mountain regions, VR education could serve as the 162 fulcrum which balances the needs to learn, understand and preserve natural sources that are losing the battle against global warming. VR technology has the ability to change education about climate change in a positive way and in virtue of this, I believe it would be foolish for educational system to resist this technology. However, this must be done slowly utilizing more research that proves undeniable evidence that this integration of VR technology is positive. Various programs and educators can then use these standards to better facilitate learning experiences.

Undoubtedly, getting young adults to gain experience in environments that are not easily accessible is essential so that educators can influence them in the right direction to act, conserve and love our environment. However, I do believe that if introduced to our world in even a minimal way, we could change student’s future perspectives about the environment. Utilizing VR in education could potentially entice students into an environment that they would not otherwise experience and can create immersive and interactive learning experiences accessible to all. VR has the potential to revolutionize the way we teach, learn, and bridge the knowledge-action gap on climate change. This is a large part of the battle in creating advocates for the protecting glaciers around the globe.

However, technology has been both a destructive force in the world but in the same time it can be a powerful force in solving the current issues that humanity is facing.

163

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Appendix A: Phase 1 Elicitation Study

Students use of a video devices and Climate Change - Survey Design

Elicitation Study Instructions: Please take a few minutes to tell us what you think about the possibility of using a video device during your next school year for better understanding of climate change. There are no correct responses; we are simply interested in your opinions. When answering the following questions, please list the thoughts that come immediately to mind and be as detailed as possible. Please write each response on a separate line under the related question.

Demographics (1) What is your major? (2) Have you ever used Virtual Reality headset and in which purposes? (3) What is your home country? (4) What is your gender? (5) What is your age? (6) Are you interested to learn about Climate change and glaciers that are disappearing?

Device Use (1) What kind of video device do you intend to use during your next school year to learn about climate change in some area? Please circle as many as apply. a. YouTube b. VR c. Interactive smartphone application d. Online internet reading e. PowerPoints f. Broadcast g. Other ______.

(2) What are all the ways in which you use each of the devices you selected in the previous question? The series of questions that follow aim to better understand the use of VR in school settings. Use What are all the ways in which you use a VR during school year? Behavioral outcomes (1) What do you see as the advantages of using a VR during your next school year? (2) What do you see as the disadvantages of using a VR during your next school year? (3) What else comes to mind when you think about using a VR during your next school year? Normative referents 195

When it comes to using a VR during your next school year, there might be individuals or groups who would think you should or should not perform this behavior.

(1) What types of individuals or groups would approve or think you should use a VR during school year?

(2) What types of individuals or groups who would disapprove or think you should not use a VR during school year?

(3) Sometimes, when we are not sure what to do, we look to see what others are doing. Please list the individuals or groups who are most likely to use a VR during the school year.

(4) Please list the individuals or groups who are least likely to use a VR during their school year.

Control factors (1) Please list any factors or circumstances that would make it easy or enable you to use a VR during your next school year. (2) Please list any factors or circumstances that would make it difficult or prevent you from using a VR during your next school year.

196

Appendix B: Phase 2 Final Study

Demographics What is your major? Have you ever used Virtual Reality? What is your home country? What is your gender? What is your age? Are you interested to learn about Climate change and glaciers that are disappearing?

Circle the correct numeric response to each statement. Survey scale: 1 – Strongly disagree, 2 – Disagree, 3 – Neither agree or disagree, 4 – Agree, and 5 – Strongly agree. Item Self-location (Hartmann et al., 2016) SL1 I felt like I was actually there in the environment of 1 2 3 4 5 the tropical glacier. SL2 It seemed as though I actually took part in the action of 1 2 3 4 5 the presentation. SL3 It was as though my true location had shifted into the 1 2 3 4 5 environment of Santa Isabel glacier. SL4 I felt as though I was physically present near the 1 2 3 4 5 glacier. Possible Actions (Hartmann et al., 2016) PA1 The glacier and the snow in the video gave me the 1 2 3 4 5 feeling that I could do things with them. PA2 I had the impression that I could be active in the environment of the 1 2 3 4 5 video. PA3 I felt like I could move around with Dr. Sevestre in the video. 1 2 3 4 5

PA4 It seemed to me that I could do whatever I wanted in 1 2 3 4 5 the environment of the presentation. Perceived ease of use (adapted from Davis, 1989; Manis and Choi, 2019) PEU1 I believe that using the virtual device is easy. 1 2 3 4 5 PEU2 I found it easy to use immersive virtual field trips for 1 2 3 4 5 learning about climate change and glaciers. PEU3 The use of immersive virtual field trips does not 1 2 3 4 5 require much effort. PEU4 Learning to use the virtual reality device was a quick 1 2 3 4 5 process. Perceived Usefulness (adapted from Davis., 1999; Manis and Choi, 2019) PU1 I think virtual reality based environmental interpretation is useful for my learning about climate 1 2 3 4 5 change and glaciers. 197

PU2 Using virtual reality based environmental interpretation increases my productivity to learn about 1 2 3 4 5 the world that is despair because of global warming PU3 Using m virtual reality based environmental interpretation improves my performance to understand 1 2 3 4 5 better about glaciers and changes PU4 Using virtual reality based environmental 1 2 3 4 5 interpretation enhances my effectiveness Intention to use (adapted from Davis et al., 1989; Manis and Choi, 2019) BI1 If given the possibility, I would use immersive virtual 1 2 3 4 5 field trips for climate and glaciers learning. BI2 I intend to use immersive virtual field trips in the 1 2 3 4 5 future. BI3 There is a high likelihood that I will use virtual reality 1 2 3 4 5 devices for virtual field trips. Attitude towards immersive virtual field trip (Wallgrün et al., 2019) AT1 Virtual field trips can replace actual field trips. 1 2 3 4 5 AT2 I would like to see more use of virtual field trips in 1 2 3 4 5 university teaching. AT3 I can learn the same amount from a virtual field trip as 1 2 3 4 5 I can from an actual field trip. AT4 I think both virtual field trips and actual field trips can 1 2 3 4 5 be useful in learning about climate change.

198

Appendix C: Approval for the use of SPES questioner

199

Appendix D: Storyboard

200

Appendix E: Meaning “badass”

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