Personal Augmented Space: Mobile 3D Visualisation and Interaction Study with Microblogging
Julian M¨unster
a thesis submitted for the degree of Master of Science at the University of Otago, Dunedin, New Zealand.
27-03-2013 Abstract
Web 2.0 services such as Twitter or Facebook are all around us and with us every day through the introduction of smartphones and tablets alike. The ever increasing feature set, faster ways to connect to the Internet and larger screen real estate that mobile devices are equipped with, allow Web 2.0 services to flood users with more and more information. This avalanche of information becomes unmanageable in its complexity and quantity and turns into information overload. To counteract the users’ feeling of information overload a new 3D personalised augmented reality user space was designed and implemented. It employes the techniques such as augmented reality and information filtering in a 3D environment to reduce information complexity and information overload. This new application was developed for a tablet computer and focuses on the humans’ natural abilities of spatial awareness. To test the underlying assumptions a set of experiments was designed and user trials are conducted to investigate the usability and navigability as well as the perceived information load. Following the data gathering phase of the experiment, it was statistically analysed to compare two different approaches. For this purpose a 2D and a 3D version of the same application had been developed. Comparing the results of the user study, no statistically relevant difference in usability could be established. The results suggest that the users’ perception of information overload did not get better in the new 3D interface, and it did not get worse either. The results and observations analyses following the user experiment strongly suggest that information overload should be considered during the application development process of Web 2.0 applications. This research shows there is no usability loss when using the 3D interface over the 2D interface. Further research and development into the areas of spatial knowledge and awareness in 3D information systems may reduce the information load felt by users of current information rich systems.
ii Acknowledgements
I would like to thank my supervisor Dr. Holger Regenbrecht and Dr. Mariusz Nowostawski for their support and some timely advice on this project. Thanks to Constantin for his help when I was stuck on a programming problem, to Jonny for his support and help during the user study, to Cameron, Alan and Simon for their excellent help during the statistical analysis and thanks to all my proof readers. To my study participants, thank you for your time and enthusiasm when you were all busy with your own projects. And to all my friends in the lab, office and outside the university; I would not have made it without your support. Thank you, you guys are the best!
iii Contents
1 Introduction 2 1.1 Scope ...... 3 1.2 Motivation ...... 3 1.3 Outline ...... 4 1.4 Abbreviations and Terms Used ...... 5
2 Review of Related Work and Literature 7 2.1 Introduction ...... 7 2.2 Augmented Reality on Mobile Devices ...... 7 2.3 3D User Interfaces and 3D Environments ...... 10 2.4 Micro Blogging and Information Overload ...... 13 2.5 Hypotheses ...... 15
3 Developing a Prototype 16 3.1 Overview ...... 16 3.2 Devices and Tools ...... 16 3.2.1 The Mobile Devices ...... 16 3.2.2 Development Tools ...... 20 3.3 User Interface Design and Implementation ...... 22 3.3.1 The 3D Prototype ...... 23 3.3.2 The 2D Prototype ...... 27 3.3.3 The Warm Up UI ...... 27 3.4 Application Setup ...... 29
4 Investigating the 3D Browser 31 4.1 Overview ...... 31 4.2 Research Variables ...... 31 4.2.1 Independent and Dependent Variables ...... 31 4.2.2 Confounding Variables ...... 32 4.3 Methodology ...... 33 4.3.1 Participants ...... 33 4.3.2 Inclusion Criteria ...... 33 4.3.3 Tasks ...... 34 4.3.4 Questionnaires ...... 35 4.3.5 Materials and Apparatus ...... 36 4.3.6 Experiment Design ...... 37 4.3.7 Procedure ...... 37 4.4 Assumptions ...... 38 4.5 Data Collection ...... 38
iv 5 User Study Results 39 5.1 Overview ...... 39 5.2 User Interface Efficiency ...... 40 5.3 User Interface Effectiveness ...... 41 5.4 User Interface Satisfaction ...... 42 5.5 User Interface Information Overload ...... 44 5.6 Other Discoveries and Observations ...... 45 5.6.1 Post-Study Questionnaire ...... 45 5.6.2 Participant Behaviours ...... 45
6 Conclusions 48 6.1 Discussion ...... 48 6.1.1 Usability ...... 48 6.1.2 Information Overload ...... 49 6.1.3 Overall Performance ...... 49 6.1.4 Observations ...... 50 6.1.5 Summary ...... 50 6.2 Future Work ...... 50
References 52
v List of Tables
5.1 Results for task completion time...... 41 5.2 Results for correlations in efficiency data...... 41 5.3 Results for completeness and correctness of tasks...... 42 5.4 Results for correlations in effectiveness data...... 42 5.5 Results for user satisfaction...... 43 5.6 Results for information overload...... 45 5.7 Results for correlations in information overload data...... 45 5.8 Results from the Post-Study Questionnaire...... 46
vi List of Figures
2.1 Wikitude - Overview [Wikitude, 2012b] ...... 9 2.2 Wikitude - AR Browser [Wikitude, 2012a] ...... 9 2.3 Junaio - AR Browser [Junaio, 2012a] ...... 10 2.4 Junaio - AR Browser (Twitter) [Junaio, 2012b] ...... 10 2.5 Layar - AR Browser [Layar, 2012c,a] ...... 11
3.1 Possible component structure...... 17 3.2 The Samsung Galaxy Tab 7.7...... 18 3.3 The Motorola Xoom Gen.1...... 19 3.4 Unity 3D environment...... 20 3.5 Details on the cube construction...... 21 3.6 Hidden Twitter tabs for the scrolling effect...... 21 3.7 Mono Development environment...... 22 3.8 The Eclipse debug environment...... 23 3.9 The idea of a cube...... 23 3.10 The three main faces of the virtual cube...... 24 3.11 An illustration of the cube/room scenario...... 25 3.12 The settings screen...... 26 3.13 Scrolling individual panes...... 26 3.14 The first pane of the 2D Application...... 27 3.15 The second pane of the 2D Application...... 28 3.16 The third pane of the 2D Application...... 28 3.17 The warm up UI...... 29 3.18 The tablet setup...... 29
4.1 A participant using the prototype...... 36 4.2 Counterbalanced possibilities of order of presentation for the two independent UIs. . . 37
5.1 Normal distribution of collected information overload data indicating the use of the ANOVA method for variance analysis...... 40 5.2 Normal distribution of collected user satisfaction data indicating the use of the ANOVA method for variance analysis...... 40 5.3 Showing the difference in time between condition 1 and 2 including error bars. . . . . 41 5.4 Showing the difference of mean answers for every user satisfaction question between condition 1 and 2 including error bars...... 43 5.5 Showing the difference of mean answers for every information overload question between condition 1 and 2 including error bars...... 44 5.6 Showing the difference of mean answers for every question...... 46
vii Definitions
In order of appearance:
HCI - Human Computer Interface • 2D UI - 2 Dimensional User Interface • 3D UI - 3 Dimensional User Interface • OS - Operating System • Android - A mobile operating system designed by Google • iOS - A mobile operating system designed by Apple • Windows Mobile - A mobile operating system designed by Microsoft • IDE - Integrated Development Environment • DDMS - Dalvik Debug Monitor Server •
1 Chapter 1
Introduction
Through the emergence of Web 2.0 and microblogging more user generated content is brought to the world wide web (WWW) [Honeycutt & Herring, 2009; Belin & Khachikian, 2007] and to users. These advances give the user the ability to write and read updates in real time. Users write status posts about their current situation or anything they would like to share with an ever growing user-base. Twitter, Facebook, Google+, RSS feeds and Skype are a few examples of such web services [Honeycutt & Herring, 2009; Belin & Khachikian, 2007; Curran et al., 2012]. At the same time mobile devices, in particular smartphones and tablet computers, have become more popular [Falaki et al., 2010]. They have given the ever growing Web 2.0 market a new platform and enabled users mobility with a constant stream of information never experienced before. These technological improvements also brought about a constantly increasing set of features for smartphones and tablets. These rich feature sets include a number of sensors like a gyroscope, an accelerometer and the ability to stream a video feed from a back facing camera among others. Those sensors and cameras make AR applications and 3D animated applications a reality on mobile devices. Combining the output of a number of these sensors and features on a mobile device like a smartphone or a tablet computer allows the developers to create mobile AR applications of great variety [M¨unster & Nowostawski, 2012]. With technology advancing rapidly every year and giving users the opportunity to access their virtual information in ever more ways, users are flooded with information on a daily basis. With the continued introduction of better devices, more services to use and a growing user-base, these Web 2.0 services created, with their own success, the problem of information overload. Information overload is experienced on the desktop or the mobile device by one or many applications bundled and comes with the additional challenges of todays information complexity. This research investigates if it is possible to use these technology advancement and reduce the effects of information overload to the user. Traditionally information overload has been defined as ”Information presented at a rate too fast for a person to process” by Sheridan & Ferrell [1974]. A modern definition of this problem comes from Hiltz & Turoff [1985], who suggested that individuals might:
1. fail to respond to certain inputs,
2. responds less accurately than they would otherwise,
3. responds incorrectly,
2 4. store inputs and then responds to them as time permitted,
5. systematically ignore some features of the input,
6. recode the inputs in a more compact or effective form,
7. quits.
The idea of mobile AR using 2D and 3D visualisation is not new [Mixare, 2012; Metaio, 2012; Layar, 2012b; Karpischek et al., 2009; Wikitude, 2012b; Schmalstieg et al., 2002], but the combination of using mobile AR to visualise a social media service like microblogging in a personalised augmented space is. The spatial arrangement of information in a meaningful way with regard to the user and the usability of such an application are the two core concepts discussed in the following pages. The design process of a usable interface for a personalised 3D workspace using augmented reality and 3D as a visualisation method is illustrated. A user study is performed to compare the newly developed user interface for a 3D personalised augmented reality space and an average 2D mobile application. The results of that user study will either prove or refute the hypotheses established in the next chapter. It will measure and compare the usability and the information overload felt by the partici- pants of the experiment.
1.1 Scope
The investigation and presentation of a possible solution to the problem of information overload and information complexity as well as the usability of such an information system on a mobile device is the main focus of this thesis. The solution that is further looked into and discussed, is a context-aware, personalised, augmented mobile information system in 3D space. There are several steps to achieve the above, namely: a prototype design stage, an implementation stage, an experimentation, data collection and finally data analysis. To facilitate the experimentation, a mobile AR system prototype with a 3D personalised space is implemented on a tablet computer. Usability, information load and information complexity reduction are the principal factors during the interface development. The user experiment consists of a comparison of two different interfaces designs operating in 2D and 3D space. After all the data is gathered, the data analysis focuses on the two main problems, usability and information overload, which includes information complexity. It is the aim of this prototype to lessen the feeling of information overload and complexity a user may experience without allowing the usability of the system to suffer. The user study and the analysed results are discussed and are put in the context of the research.
1.2 Motivation
The field of Human Computer Interaction (HCI) presents itself in our every day life. Some of the interactions with computers are subtle others are more obvious. Smartphones and tablets are ubiq- uitous in our life and come with a variety of user interfaces including applications particular to each OS. Social media applications increase in demand and are tailored to mobile devices. Micro blogging and augmented reality are one representation of this evolution.
3 As mobile AR increases in popularity with mobile devices both hardware and software support needs to evolve. User interfaces present a number of challenges on mobile devices compared to the desktop computer. An example is the touch interface that replaces the mouse and keyboard of a personal computer and the limited screen sizes on smartphones and on tablets [Satyanarayanan, 1996]. Another difficulty is the inability to upgrade their hardware. After a device is purchased there is usually no way to upgrade its components, only software upgrades are possible. Smartphones come in a range of different screen sizes, but are essentially always limited by the fact the average smartphone needs to fit inside the user’s pocket and should be able to fit in or be dealt with by one hand, although those distinctions are getting blurred. This is not the same for a tablet. They usually have bigger screens, more comparable to the size of a netbook computer (small laptop). It still has a weight constraint and needs to be a handy device. Too heavy or too bulky leads the user to rejecting the tablet [UMPCPortal, 2012]. The screen size difference leads to the need to redesign the user interfaces for tablets. User interface design is an essential part of mobile development. Tapping into the user’s spatial awareness when designing user interfaces in a 3D environment is of importance to usability and navigability. In a 3D space like a room, the user has spatial awareness and therefore a natural awareness of where objects such as the door, desks, windows or anything else are placed. For example, when the user is not facing the door he has entered through, usually, it would not be a problem to point in the direction of the door’s whereabouts without having to search for it, even when it is obstructed by other objects. The main motivations of this research come from the need to address the information overload issues when dealing with news feeds of any kind, micro-blogging and any other type of modern social media. Similar to Cockburn & McKenzie [2001] we are interested in the difference between the performance of a two-dimensional user interfaces (2D UI) compared to a spatial, three-dimensional user interfaces (3D UI), where users can use their spatial perceptions and orientations skills.
1.3 Outline
This research and its report is split into three major subcategories: the investigation into the relevant research areas, the creation of a prototype and the resulting user study, and the collection and analysis of data. The following section summarises the following chapters.
Chapter 2: This chapter investigates all major branches relating to this thesis: augmented reality on mobile devices, 3D systems and environments, and information overload and micro blogging. It supplies the background information needed for further reading and also references the examined literature. It will conclude in a set of hypotheses launching into the prototype chapter.
Chapter 3: This chapter details the design and implementation process of the prototype resulting from the previous chapters investigation.
Chapter 4: This chapter provides detailed explanation of the user study that was run to investigate the success of the 3D prototype developed in the previous chapter. It compares the 3D UI with the standard 2D UI in terms of information overload and usability.
4 Chapter 5: This chapter displays the results and analysis accomplished with the data collected during the study described in the previous chapter.
Chapter 6: This chapter discusses and concludes on the information gathered and analysed in all previous chapters. It notes the contributions and limitations of this work. It highlights the parts of this project that may profit from future development and research.
1.4 Abbreviations and Terms Used
Augmented Reality (AR): Azuma et al. [2001] defines AR as a system that supplements the real world with virtual objects and for the purpose of this report we follow this definition.
Information Overload: is defined as follows [Hiltz & Turoff, 1985]: ”Individuals might
1. fail to respond to certain inputs,
2. responds less accurately than they would otherwise,
3. responds incorrectly,
4. store inputs and then responds to them as time permitted,
5. systematically ignore some features of the input,
6. recode the inputs in a more compact or effective form,
7. quits.”
Usability: can be split into three subcategories which define it: efficiency, effectiveness, satisfaction [ISO, 2010, 1998].
Efficiency: describes the time use to complete a certain task [ISO, 2010, 1998].
Effectiveness: describes the completeness and correctness with which one finishes a certain task [ISO, 2010, 1998].
Satisfaction: refers to the state of mind (contentment) of an individual using an application to complete a certain task [ISO, 2010, 1998].
Human Computer Interaction (HCI): is the study of interaction between people and computer.
2D UI and 3D UI: refer to the 2D User Interface and the 3D User Interface designed as part of this research.
Integrated Development Environment (IDE): is commonly used to develop software applica- tions.
5 Dalvik Debug Monitor Server (DDMS): is the debug monitor used with Android and is a helpful development tool.
Client: refers to twitter client in the context of this report, unless otherwise stated.
MMO: means Massively Multiplayer Online and refers to a type of online multiplayer game systems.
6 Chapter 2
Review of Related Work and Literature
2.1 Introduction
This review of related work and literature examines a summation of the work done in the relevant fields, related to this project. There are several areas of research that must be included. Mobile Augmented Reality combines two research areas in one, the research and development of augmented reality application on mobile devices. It is an integral part of this project. 3D User Interface and 3D Environments are investigated and explored with regards to usability and navigability and frame the first part of the hypotheses. When 3D environments are discussed, they are not to be confused with 3D perspective screens. Micro Blogging and Information Overload, in particular social media and Web 2.0 on mobile devices with respect to the problem of information overload, are reviewed. That examined material delivers the basis for the second part of the hypotheses. The last ten years of all major conferences and journal articles in this field of study were covered. Among the topics are ‘Wearable Computing’, ‘Handheld Devices’, ‘Mobile HCI’, ‘Mobile Devices’, ‘Pervasive Computing’, ‘CHI’, ‘OZCHI’, ‘NORDCHI’, ‘ISMAR’, ‘UIST’ and several less known venues.
2.2 Augmented Reality on Mobile Devices
Augmented reality has been around since the late 1990’s and has matured from being run on big heavy personal computers to mobile devices, some of them are wearable computing devices, Smartphones or tablet computers [Wagner & Schmalstieg, 2009; Yuen et al., 2011]. For the purpose of this research we will rely on the definition of AR from Azuma [1997]; Azuma et al. [2001]. It is a definition widely used and accepted [see Haller et al., 2006, chap. 14] and [M¨unster & Nowostawski, 2012]. Azuma defines AR as follows: ”We define an AR system to have the following properties:
Combines real and virtual objects in a real environment; •
7 Runs interactively, and in real time; and • Registers (aligns) real and virtual object with each other. [Azuma, 1997]” • It can be said that mobile augmented reality is a live video stream with virtual annotations on a layer above. Those annotations can vary from 3D objects, images, audio snippets to videos or any other digital format a mobile device such as a tablet or smartphone can handle. It is the goal to enrich the user experience by annotating real world objects by adding virtual content [M¨unster & Nowostawski, 2012]. There are several different forms of mobile AR, texture tracking, 3D feature tracking and sensor based tracking, which is also called location based tracking [Chimienti et al., 2010]. The later one is of interest to this project, because it is focused on the device’s location and orientation. This means if we are in a particular place and pointing the device in a particular direction it shows only the virtual annotations particular to that place and direction [M¨unster & Nowostawski, 2012]. Sensor based tracking works by the fusion of several different sensors like GPS, accelerometer or gyroscope and the magnetic field sensor. The GPS provides the current location of the mobile device. Then in real time a combination of gyroscope or accelerometer and magnetic field sensors calculate the direction the device is facing [M¨unster & Nowostawski, 2012; Raper et al., 2007]. Mobile AR development has been an ever growing niche in the AR market and has established itself with the inflation of functionality delivered with mobile devices. It started with the advances made by Piekarski & Thomas [2002], which developed an innovative procedure to program mobile AR systems. Many changes in hardware and software have been made since then and lead to a wealth of AR applications and software development kits to use to create AR applications [Wagner & Schmalstieg, 2009, 2003; Azuma et al., 2001]. Currently, there are a number of resources in form a AR SDKs freely available on the Internet. Well known products such as Metaio [Metaio, 2012], Layar [Layar, 2012b], Wikitude [Karpischek et al., 2009; Wikitude, 2012b] or StudierstubeES [Schmalstieg et al., 2002] offer SKDs and some also have an online AR browser. Qualcomm also developed its own version of the StudierstubeES software with more focus on hardware acceleration with their chipsets [Schmalstieg & Wagner, 2008]. This SDK is also available free on the Internet, but works on a server client model. In this case the server sits with Qualcomm and can not be run on an internal network. Mobile AR also is represented in the open source community. There are two open source projects, developing free to use SDKs, such as Mixare [Mixare, 2012] and ARToolkit [Piekarski & Thomas, 2002] as well as a number of University projects. On top of the above mentioned resources are a great number of mobile AR applications. Those range from browser applications, which augment the real world by telling you were the next bus station or restaurant is from your current location [3DAR, 2013; ARApplications, 2013], others work by pointing at a certain image or building and revealing extra information about that structure or item [ARApplications, 2013; Mercedes, 2013; MetaioRetail, 2013]. The combination of social media services and AR has also been exploited by several browsers. Wikitude, Junaio and Layar are all AR browsers and let you incorporate social networks into your AR world. The following images illustrate how the social media components and the browser interact. Figure 2.1 and 2.2 show how Wikitude handles social media, Figure 2.3 and Figure 2.4 demonstrate
8 Figure 2.1: Wikitude - Overview [Wikitude, 2012b]
Figure 2.2: Wikitude - AR Browser [Wikitude, 2012a] the Junaio browser working with Twitter and Figure 2.5 shows the Layar browser in action again using Twitter as a social media service.
9 Figure 2.3: Junaio - AR Browser [Junaio, 2012a]
Figure 2.4: Junaio - AR Browser (Twitter) [Junaio, 2012b]
2.3 3D User Interfaces and 3D Environments
Azuma et al. [2001] describe several applications in their survey that use 3D models in a real world 3D environment. They discuss bigger stationary systems, but also acknowledge that mobile applications are becoming better and more suitable for everyday use. The exploration into 3D user interfaces and 3D environments as well as the idea to increase the productivity of users using such interfaces has been around for a while [Robertson et al., 1998]. During the early stages improving the effectiveness of document management, which has been a problem in
10 Figure 2.5: Layar - AR Browser [Layar, 2012c,a]
HCI for over forty years, was a priority. This research also introduces and illustrates the idea of spatial memory or spatial knowledge. To have any spatial memory you need to have spatial knowledge. A paper by Darken & Sibert [1996] discusses the possibility that the experiences picked up in the real world can be transferred to the virtual world. It divides spatial knowledge into the following:
1. ‘Landmark knowledge is information about the visual details of specific locations in the envi- ronment. It is memory for notable perceptual features such as a unique building.
2. Procedural knowledge (also known as route knowledge) is information about the sequence of actions required to follow a particular route. Procedural knowledge is built by connecting isolated bits of landmark knowledge into larger, more complex structures.
3. Survey knowledge is configural or topological information. Object locations and inter-object distances are encoded in terms of a geocentric, fixed, frame of reference. A geocentric frame of reference is a global, map-like view while an egocentric frame of reference is a first-person, ground-view relative to the observer. Survey knowledge has been found to be essential for skillful wayfinding.’
The research done by Robertson et al. [1998] proves that spatial memory is accessible in a 3D virtual environment in the context of efficient document management. Burigat & Chittaro [2007] also discuss the importance of spatial processes, such as directional knowledge and assessing spatial abilities as part of navigating a 3D virtual environment. Navigation of these environments is defined as follows: ‘Navigation can be defined as the process whereby people determine where they are, where everything else is and how to get to particular objects or places.’ by Jul & Furnas [1997].
11 Andy Cockburn and Bruce McKenzie [Cockburn & McKenzie, 2001] re-evaluated the ‘Data Moun- tain’ article and investigated if participants were faster or more efficient at retrieving documents using a 2D or 3D interface. They found that there was no significant difference in the results, although the participants had a preference for the 3D interface.
Mobile 3D Engine
While considering platform specific 3D engines and development tools the following were investigated: jPCT-AE [jPCT AE, 2012], Ardor3d [Ardor3D, 2012], jMonkeyEngine [jMonkeyEngine, 2012], Linder- daum Engine [Linderdaum, 2012], Ogre [Ogre, 2012], Libgdx [LibGDX, 2012], MootDroid [MootDroid, 2012], Marmalade [Marmalade, 2012], Shiva3D [Shiva3D, 2012] and Unity 3D [Unity3D, 2012]. jPCT-AE is a free 3D engine which has been ported from Java to Android. It has been optimised for the Android platform supports OpenGL ES 1.x and 2.0 [jPCT AE, 2012]. The engine has all the necessary features, but is solely based on Android and if there is a bug or a feature missing it is questionable how good the support would be. On the project website there was only mention of old projects. Ardor3d is an open source Java based 3D engine and is in its early stages of development. It has a version running on Android, but there seems to be little support available [Ardor3D, 2012]. Some sections of the website are missing or have not yet been filled out and it only runs on Android so far. jMonkeyEngine is Java based open source 3D game engine. There is some special installation needed to get this engine running on Android, but it has almost the same feature set as the original Java engine. It converts touch inputs into mouse events in order to handle them properly. It also has a built in asset system and uses jBullet as its physics library [jMonkeyEngine, 2012]. Linderdaum Engine is an open source 3D gaming engine. It is purely object oriented and written in C++ for Windows and Android. It has Android support up until SDK 16 and has had some major bug fixes in January 2012 [Linderdaum, 2012]. At the time we made the decision it was not as accomplished as it is now and there is no cross mobile platform compilation yet. Ogre is not compatible with Android and would have to be ported before use. It is not just a 3D game engine, it also has features like sound, networking, AI, collision detection and a physics engine. Support for Android is sparse, but the source code is released under the MIT license [Ogre, 2012]. Libgdx is a game development framework written in Java. It is cross platform with some limita- tions. It does not support iOS, but has a number of good features like built in gesture detection and several other input handlers [LibGDX, 2012]. MootDroid is a discontinued open source project. There is not much information on it on the website and with no current support, but it is written for Android [MootDroid, 2012]. Marmalade is a fully featured 3D game engine with cross platform development capability. It is written in HTML5 and C++, which gives the freedom to run on any mobile platform and gives the option to program in HTML5 or C++. It also has an extension for iOS and Android to directly use their APIs [Marmalade, 2012]. Shiva 3D is another cross platform 3D engine with a complete 3D game editor attached. It has also build in support for PhysX, Fmod and ARToolkit and comes with a server tool to create MMOs with VOIP. A server tool is an application that allows the creation of a server like an MMO game
12 server. It is mainly C++ based programming [Shiva3D, 2012]. Platform independency is very important in todays development world, because being able to release a product on several different platforms at the same time gives you an advantage. 3D Engines like Unity [Unity3D, 2012], Marmalade [Marmalade, 2012] or ShiVa 3D [Shiva3D, 2012] allow this feature and also have professional support as well as a stream of continues updates fixing issues reported by users. When deciding on what tool to use we took several conditions under review. First, the quickest way to get help with an unknown development tool is to have colleagues that are using it or have used it before, in other words experience in the department. Second, do we already own a license of any 3D engine product if it is necessary. Third, is it a cross-platform tool allowing the development for Android and iOS. Unity 3D fulfills all our requirements and was chosen as development environment. Unity 3D generates its own difficulties such as the link between the Unity 3D engine and Android. Unity 3D is an engine designed with cross-platform development in mind, which requires it to have an abstraction layer handling all communication between the engine and the underlying OS. For this bottleneck it was not possible to reach the sensors exposed to the Android layer without the help of a plugin at the time of development. Designed for game development, Unity adds a level of obstruction to the development of a normal application. It is a challenge to display text in the right spot rendered to satisfaction, where as with the native Android framework this is a trivial task.
2.4 Micro Blogging and Information Overload
Micro Blogging can be defined as a form of blogging that lets you share short elements of content, such as text, links, images (via link) or videos (via link) [Java et al., 2007; Wikipedia, 2012]. A few well known examples of these kind of services are Twitter [Twitter, 2012], Facebook [Facebook, 2012] and Google+ [Google, 2013]. Granted, Facebook and Google+ offer services far beyond the short update function, but this is still a major part. As described by Java et al. [2007] their can be many reasons a user may want to employ such social networking tools, but for the most part it is to discuss personal events or information at all hours of the day or simply to have a conversation. Regardless of the use of these social networking portals, the gain in popularity in the past few years is undeniable [Kim et al., 2010; Ebner & Schiefner, 2008; Java et al., 2007; Mathioudakis & Koudas, 2010]. Twitter is currently the major micro blogging platform and has more than 50 million subscribers [Math- ioudakis & Koudas, 2010]. It has about 58 million tweets a day, around 9,100 tweets happen every second and has about 40% of people just watching other people tweet [Statisticbrain, 2012; Medi- abistro, 2012]. The purpose of Twitter as described by the service itself is to answer the question: ”What are you doing?” [Twitter, 2012; Honey & Herring, 2009]. Looking at a study by Mischaud [2007] with 5,767 tweets, 58% of those did not address that question. Twitter has an ever growing user base, of which a large percentage is mostly interested in reading or consuming the information presented. The usage of Twitter has changed so much that users have invented additional special characters like the @ symbol to indicate their tweet is directed at another user [Honey & Herring, 2009]. The community of Twitter users has matured over the years of its existence. Twitter is now a days considered as tool to help people with the communication of
13 information during disaster scenarios like an earthquake or a flooding river [Vieweg et al., 2010]. This is another example of the vast growth of this micro blogging service and as long as information flow is controlled, it is a good tool to reach people in emergency situations. One other example of Twitter usage is as a marketing tool. Its ability to produce the word of mouth effect and reach millions of people make it a great choice [Jansen et al., 2009]. Given the evidence described above, it is obvious why problems like information overload arise when using a micro blogging tool such as Twitter. With the evolution of those discussed Web 2.0 services and the constant additions of more features over the years of their existence, they have become powerful tools to reach people everywhere. Some did not start as blogging tools and others transformed to include multimedia input. All these opportunities to add user content leads to something called information overload. Information overload is defined by Hiltz and Turoff [Hiltz & Turoff, 1985] to be a person that suffers from the following when processing and comprehending information: ”fails to respond to certain input; responds less accurately than they would otherwise; responds incorrectly; store inputs and then responds to them as time permitted; systematically ignore some features of the input; recode the inputs in a more compact or effective form; or quits.” Information overload is a problem that has been plaguing humans for a long time and is connected with incidents such as Chernobyl and the Three-Mile Island. Those were extreme accidents and an example of the worst case scenario. They happened as a result of information overload and mismanagement [Billinghurst & Starner, 1999]. Billinghurst & Starner [1999] recognised the struggles and problems that follow the evolution of computer hardware to wearable and/or mobile devices. Addressing the problem of information overload is not something that can be solved once. With progressing technology and hardware options, mobile devices will change and solutions devised for previous systems may not suit the new ones. The enormous volumes of data throughput in combination with processing and display limitations needs to be addressed on mobile devices [Yin & Carswell, 2012]. AR browsers, like the ones previously mentioned, are not in common usage in todays households, because of technical limitations. As described by Grubert et al. [2011] and Feiner, the poor registration, a paucity of relevant content, and a lack of information structure to help the user navigate the visualization are problems yet to be solved. Humans build cognitive maps of their surroundings and later use those maps to navigate and understand the real world. Anchoring signs and consistent spatial organisation can assist users to create their own cognitive maps [Passini, 1984]. As long as there are no overlapping points of interest, this approach may work with the loss of information and facilitate an environment with usable navigation. Reducing information overload can have adverse affects on the ability of users to learn to navigate the UI or increase UI complexity. There is a balancing act to be handled between the reduction of information overload to the user and the user ability to be able to deal with the complexity of the displayed information Wilson & Schraefel [2008]. The authors suggest a method called Cognitive Load Theory (CLT) to identify methods for reducing the complexity of information. A paper by Mu [2004] supports the position that cognitives loads are closely related to the complexity of a task, the system used to operate the task, and the operators characteristics. CLT says that the users ability to gain knowledge is affected by the complexity of a learning task and the learning material [Chandler
14 & Sweller, 1991]. Wilson & Schraefel [2008] also identify three methods of improvement: the split- attention effect, the modality effect and the redundancy effect. Split attention effect refers to user having to collect information from different sources, such as text and a picture, to complete their learning experience. Modality effect refers to using the different modalities of working memory and distribute the learning between them to reduce the cognitive load. Redundancy effect refers to the state where information is displayed multiple times in different locations. Then the user would be required to check both and to recognise the changes [Wilson & Schraefel, 2008; Schwartz, 2004].
2.5 Hypotheses
As described in Chapter 1, we are interested in a comparison of level of information overload experi- enced by the user when using a 3D UI over a 2D UI. The research into related work and literature supports a user study with the following hypotheses. The combination of hypotheses asserts that this 3D application is capable of enhancing users’ percep- tion of information and reduce information overload, while retaining usability.
Hypothesis 1: The 3D prototype will allow users to perform tasks as quickly as the 2D prototype.
Hypothesis 2: The 3D prototype will have the same number of correct answers as the 2D prototype, when performing a set of tasks.
Hypothesis 3: The 3D prototype will perform as well as the 2D prototype during a satisfaction questionnaire.
Hypothesis 4: The 3D prototype will reduce information overload compared to the standard 2D application.
Hypothesis 5: The 3D prototype will overall outperform the 2D prototype.
15 Chapter 3
Developing a Prototype
3.1 Overview
This chapter gives a detailed description of the prototype design and implementation. It is based on the preceding investigation of literature and relevant material. We discuss the technologies, devices and the implementation process involved in the creation procedure. As part of this experiment scope we only dealt with information from Twitter, also called tweets. In order to conduct the study and compare a standard 2D UI with a 3D UI, we needed to develop a 3D twitter client, which incorporates similar feature as the 2D twitter client to make the comparison possible. Late in the development phase we discovered that the most commonly used 2D Twitter clients were not capable of producing the output needed for the experiment. A 2D client needed to be developed as well. Further issues arose with the tablet originally used for development, the Motorola Xoom (1st Generation). Figure 3.1 illustrates a top level view of the possible 3D application structure.
3.2 Devices and Tools
3.2.1 The Mobile Devices
By the nature of this project we are limited to mobile device platforms and we need to worry about the confining factors such as the screen size and resolution, weight of the device and slimness or handling. If the screen is too small the user might not be able to read or identify the information delivered to the user, too big the mobile device may become to cumbersome to use or too heavy to hold over longer periods of time. At no time should the user feel burdened by or uncomfortable with the device. One such a mobile device that qualifies is a tablet. Its specifications allow for a big enough screen, light weight, handiness and are programmable. No matter how light and handy the devices will get, this type of application will always require the user to move from left to right and right to left. This is an obvious inconvenience and requires physical effort. This situation can be compared to a group discussion. Every time another person gets a turn to speak, once head moves and focuses on that person. There are many different manufacturers for tablets and several different mainstream mobile OSs.
16 Figure 3.1: Possible component structure.
Android [Google, 2012a], Blackberry [Blackberry, 2012], iOS [Apple, 2012], MeeGo [MeeGo, 2012], WebOS [HP, 2012] and Windows Mobile [Microsoft, 2012] are a few of those platforms, but it must be mentioned at this point this is not a complete list. Within the department at the University several staff, including myself, have already gathered experience with Android and also have a number of devices ready for testing and development, it was therefore chosen for the development process. For mobile devices the OS and the device manufacturer are tightly coupled i.e. the iPad is the only device running iOS and the iPad only operates with iOS. This is not the case with Android. The Android OS can be found on many different devices all running different hardware underneath it. This is at the same time an advantage and disadvantage. After investigating several tablets, we have decided to use the Samsung Galaxy Tab 7.7. The Motorola Xoom 10 inch tablet was also a contender among different sizes of the tablet range. All tablets were running the Android OS and made a generally good impression. The Motorola Xoom was endorsed by Google for Android development and as such we thought it to be a good choice. However, due to its bad sensory output it was unusable for us. We only tested the gyroscope sensor and the magnetic field sensors for the error rate. The extreme variations, i.e. error rate, of the device were noticed during development and further tested. For further investigation of sensory output we used an application GyroDroid [GyroDroid, 2012]. This application has a function that lets you print the values collected by every sensor built into the device on the tablets screen.The tablet was lying on a table and the virtual items in the scene were drifting off to the side. The applications developed for this project use a number of sensors, especially important is the gyroscope sensor for determining the orientation of the device. It relies on an accurate output from this sensor at all times. The Xoom’s sensors have a high error rate, which made it impossible to create a satisfactory stable 3D environment. It is also one of the heavier tablets of its size as shown in the device features list of both devices. Point 6 in the Motorola feature list and point 6 in the Samsung feature list.
17 For its great sensor accuracy and light weight, we chose to explore the Samsung Galaxy Tab range. After testing the Galaxy Tab 10.1, we discovered a superior range of sensors. To further reduce weight and increase slimness, we decided settle on the Samsung Galaxy Tab 7.7 for development and testing.
Figure 3.2: The Samsung Galaxy Tab 7.7.
Device Descriptions and Features
The Samsung Galaxy Tab 7.7, as seen in Figure 3.2, has the following key features:
1. OS: Android 3.2 (Honeycomb)
2. Screen Size: 7.7 inches diagonal
3. Wireless: 3G and Wifi support
4. Camera: 3.15MP
5. Relevant Sensors: Good quality Gyroscope, Magnetic Field Sensor
6. Weight: 340g
The Motorola Xoom, as seen in Figure 3.3, has the following key features:
1. OS: Android 3.0 (Honeycomb)
2. Screen Size: 10.1 inches diagonal
3. Wireless: Wifi support
4. Camera: 5MP
5. Relevant Sensors: Proven bad quality Gyroscope, Magnetic Field Sensor (reference)
6. Weight: 730g
18 Figure 3.3: The Motorola Xoom Gen.1.
Tested Devices
Keeping the development process simple and highly adaptable to other mobile platforms was of highest priority. This makes the developed applications reusable on different platforms and with different devices. We have tested the prototype on several Android devices, some tablets and some smartphones with varying success. The test included running the application, checking if all the features like the camera feed and the movement detection was working. Display size especially with smartphones made it harder to read the information presented. The following devices were tested:
1. Motorola Xoom (tablet) - no success (bad gyro)
2. Samsung Galaxy Tab 10.1 (tablet) - success
3. Samsung Galaxy Tab 7.7 (tablet) - success
4. Galaxy Nexus (phone) - no success (issues with the camera)
5. Samsung SII (phone) - partial success (see below)
It is noteworthy that there is a difference between phone and tablet and not just the obvious size difference. The tablets gyroscope sensors are mounted in a different direction to the phones sensors. This is because a phone is usually in an upright, portrait position i.e. short edges bottom and top, where as a tablet is usually in a landscape position. At this stage we do not have an iPad available for testing, but due to the cross-platform development tool used for this project, the software can be compiled for iOS without big changes. Only some section in the source code needed to be changed in order to compile and run the application on another platform successfully.
19 It is obvious that the devices used during the testing of this prototype are not an ideal match for this type of application with regards to the weight and inconvenience using the devices, but in the future there with more advanced technology there will be more suitable devices.
3.2.2 Development Tools
The development environment Unity 3D
Figure 3.4: Unity 3D environment.
As discussed in Chapter 2 Unity 3D was chosen as 3D engine and development tool. It is a powerful game development tool and supports development on several different platforms like PC, Mac, Web, Xbox, Playstation, iOS and Android [Unity3D, 2012]. At its heart sits a 3D engine capable of running on mobile devices. Figure 3.4 shows the unity environment with the 3D modeling / scene screen on the left, the next section to the right displaying a directory tree of all my files, then a tree of all the 3D models in the current scene and the inspector, which exposes all the details of an object like the position and rotation, on the far right. The Unity 3D development environment lets us create a 3D scene as demonstrated in Figure 3.4. In our case we have constructed a cube as the top hierarchical model and then every face of the cube is part of the main cube. In Figure 3.5 the left image shows the visual representation of the cube and a preview of the cameras view, the image on the right is the textural model of the hierarchical structure. It reveals all the cubes faces, which each have models for the Twitter panes attached to them. Underneath the cube model is a tab hierarchy. To enable the ability to scroll through a tweet when the application is running we use camera projections for each of the Twitter panes. This means we have a list of all the tweets out of sight in the 3D environment and the cameras project the image
20 Figure 3.5: Details on the cube construction. of those tweets onto the actual Twitter panes inside the cube. Figure 3.6 illustrates those tabs.
Figure 3.6: Hidden Twitter tabs for the scrolling effect.
Mono Development is the scripting IDE used in combination with Unity 3D and is shown in Figure 3.7. Unity allows three different scripting languages, C#, Javascript and Boo script. This project is developed entirely in C# and Javascript, the two more common scripting languages.
Plugins used with Unity 3D
Because Unity 3D allows development for a lot of different platforms and every one is based on a different OS, Unity 3D lets developers create plugins to expand the original engine code. These plugins bridge the base OS and expose certain features to the Unity environment. Without a plugin of this sort, there is no access to the gyroscope or the magnetic field sensor. It is possible to build those plugins yourself, but we decided it was not worth the time, because they already exist. After some research into those plugins, we decided to use the ‘Sensor Plugin’ developed by Prime31 [Prime31,
21 Figure 3.7: Mono Development environment.
2012]. It gave us full access to the entire array of the devices sensors and has an simple api to work with.
Eclipse and DDMS
The Eclipse IDE was mainly used for debugging purposes, in particular the ‘Log Cat’ window. A similar experience can also be come by using the Android built ‘DDMS’, Dalvik Debug Monitor Server. In the bottom right hand corner of the image you can see what the output from Unity might look like. This is a most useful debugging tool for Android and is the only way to identify what happens when things don’t go as planned. From within the application we can send status updates or messages to this monitor and help identify most run time failures. It is also used to create screenshots of the tablet or phone connected.
3.3 User Interface Design and Implementation
As already discussed earlier one prototype was not enough. To run a comparison the study needed to have two, a 2D and a 3D client. Both are build for the micro blogging tool called Twitter and for the time of the study display identical tweets. It was also found necessary to develop a Warm-Up application, which gives the user an opportunity to learn the movements and functionality of both the 2D and 3D user interface. All the code for these applications can be found on github [M¨unster, 2012].
22 Figure 3.8: The Eclipse debug environment.
3.3.1 The 3D Prototype
Figure 3.9: The idea of a cube.
There was a lot of discussion about the shape of the basic model. Should it be a cylinder, a sphere, a
23 cube or nothing at all. The criteria for finding the right design are inherent in the task it is supposed to do. This design is supposed to simplify 3D spatial navigation for the user and orientate on real life feature to do so. It was decided a cube would give the user the feeling of being inside a room, which is an easy to understand spatial representation taken from the real world. Everyone decorates their office with posters or a calendar, some information useful to themselves. To the user our 3D scene appears like a room with windows and it has its information spatially organised in those windows like posters on the wall. Figure 3.9 illustrates what the environment looks like. Behind the semi-transparent cube model the video live stream is shown as a blank or white rectangle with the same aspect ratio as the screen of the tablet. The original design idea for this prototype included an information bubble to a specific GPS location. This means, if the user would move several meters to any direction, she/he would see different information. An example could be a user moving from one room to another, or from his home to his office. This prototype is not designed for use while moving on foot or in any other way.
The Main Cube-Faces
Figure 3.10: The three main faces of the virtual cube.
To give the user some perspective of where her/his tweets are placed in the scene we decided to use the shape of a cube. Other shapes like a cylinder or sphere are also possible. The cube represents a square room with the user placed right in the middle. Each side of the cube faces one of the cardinal points, north, east, south or west. We decided to use the shape of a cube and not a sphere, a cylinder or any other shape, because it made it easier to give directional aid to the user and underline the illusion of having certain information related to a specific wall. All vertical faces of the virtual cube, except the back plane, have information on them. During some informal testing, we discovered that the application cannot be used comfortably much past 90 ◦ degrees to each side. This led us to put the exit button for the application on the back plan or 180 ◦ degrees from the user’s perspective. In this spot it is unlikely to be triggered by accident. There is also another exit button on the ‘Setting Screen’. Figure 3.11 shows what such a room scenario may look like. The coloured items are the virtual objects and could be associated with the different items in that place in the real world.
The Bottom Cube-Face
The bottom of the cube is the control panel of the application, also referred to as the ‘Setting Screen’. When the user turns the device flat, faces the camera straight down, or places the device on a table,
24 Figure 3.11: An illustration of the cube/room scenario.
the application realises the angle of the tablet has changed to a value near 90 ◦ degrees. If this happens the application changes from normal mode to settings mode as seen in Figure 3.12. That means the camera gets frozen at 90 ◦ degrees and allows the user alter any settings in the control panel without fearing the slightest move will shift her/him out of the panel. If we do not freeze the screen the application will react to every move and will distract the user. This control panel has the second exit button, opposite to the ‘unfreeze’ button, which changes the application back into normal viewing mode. Additionally it has 2D sliders to regulate features like the transparency and the brightness of the cube. One can also adjust the rate of updates for the information displayed.
The Top Cube-Face
The top panel of the cube has no information on it and is not used at this stage. It could be used as a secondary control panel to change the look and feel for the application or to show the sky according to season and/or time of day, maybe even the weather conditions from outside. It gives the user the opportunity to receive more information without the hassle of switching to another application.
Navigation
Navigation is the heart of this project. When navigating through a 2D program it usually involves using some sort of pointing device or a touch screen which lets you change the view of the application.
25 Figure 3.12: The settings screen.
Figure 3.13: Scrolling individual panes.
This application is about navigating through information in a 3D space. No switching of tabs or other means to change images. It is like standing in a room and turning to see different wall. 3D navigation is accomplished by moving the tablet in space revealing the virtual world on top of the live camera stream. This means to look at the wall to the left, the user must turn his gaze and the tablet to the left in the real world. Every motion exerted on the tablet is picked up by the gyroscope and triggers an action in the application to move the onscreen applications view appropriately. Each Twitter feed pane can be scrolled up or down by dragging your finger over them as is with
26 most mobile applications. You can look at two different sides of the cube ie. a corner of a room and scroll each side individually as seen in Figure 3.13. The left hand pane has been scrolled down.
3.3.2 The 2D Prototype
Figure 3.14: The first pane of the 2D Application.
The 2D prototype has a similar look and feel to the 3D application, but is flat. That means instead of having floating panes aligned with walls, those panes are lined up like tabs with no augmentation in the background. Navigation between the different tabs is achieved through the push of a button. The scrolling of the Twitter feed panes themselves behaves the same way as in the 3D prototype. Figures 3.14, 3.15, 3.16 give an overview of what the 2D interface looks like. Each pane holds the same information as the equivalent ones in the 3D prototype. The first pane mirrors the left side, the second one mirrors the front side and the third pane mirrors the right side of the virtual cube.
3.3.3 The Warm Up UI
When planning the user study and running through the planed process it became obvious that we needed a warm up exercise for the 3D application. To be impartial to either 2D or 3D, we prepared two warm up exercises, one for the 2D application and one for the 3D application. They include the same features as the 2D and the 3D prototypes, but not the same information. We chose to use poems instead of the Twitter feeds. They are scrollable and can be found either by using the buttons like in the 2D version or facing the correct wall like the 3D application. This will allow the participants
27 Figure 3.15: The second pane of the 2D Application.
Figure 3.16: The third pane of the 2D Application.
28 Figure 3.17: The warm up UI. to practice scrolling and moving around the environment without giving away where the information might be during the experiment.
3.4 Application Setup
Figure 3.18: The tablet setup.
Figure 3.18 shows how we set up the screen from which we loaded each application. On the right we had the 3D applications and the 3D warm up, on the left we had the 2D applications and the 2D warm up. To make it easier and to not have the participant choose the wrong application, we started the relevant application for each session for the participants. Confusion may arise, because there are 2 2D applications and 2 3D applications, one for each conversation. Throughout several informal testing sessions we discovered a number of issues with the prototype.
29 Among those was the way to interact with the Twitter feed panes. Initially the user needed to push buttons to move the feed up or down. This was not found intuitive enough and was then replaced by a touch scroll mechanism. This touch scroll mechanism was then tested again by us and we adjusted it to make it feel comparable to other mobile applications. In order to set up the scrolling mechanism there are a few floating point values that need to be set up, by trial and error. Those values limit the comfort zone for example or set a minimum swiping distance for a scroll. Another sets the minimum swipe time, which means how long a swipe has to take. The current values for scrolling a pane are ‘70.0f’ as comfort Zone, ‘14.0f’ as minimum swiping distance, and ‘0.5f’ minimum swipe time. These values can be changed to adjust to fit any situation. To ensure a user does not scroll endlessly through a Twitter feed pane each pane is manually restricted. This was only necessary for the study setup, because the Twitter feeds were not downloaded on the spot, but were pre prepared textures. We decided to use textures instead of live tweets, because we were in full control of the flow of information and every participant would see the same tweets. This method was preferred over creating our own Twitter like server.
30 Chapter 4
Investigating the 3D Browser
4.1 Overview
This study is designed to validate the new UI design introduced in Chapter 3 and was run in 2012. During the investigation we collected quantitive and qualitative data to measure the difference of the user’s perception of information overload between the new 3D UI and the standard 2D UI. We also collected data of the UIs usability, in detail the efficiency, effectiveness and satisfaction of both applications were compared. This user study used a within participants experimental design.
4.2 Research Variables
4.2.1 Independent and Dependent Variables
The independent variable in this study is the ‘UI design’. It has the following two values:
Standard 2D UI: This is standard mobile phone application with tab functionality to allow • the user to scroll through the presented information horizontally and vertically. There are no 3D effects in this user interface.
New 3D UI: This is the 3D environment in which the user is emerged. The user needs to • explore this environment to find all the information that it holds. For this study, its a room like environment and every wall has some pre-categorised information on it.
Both of these variables are implemented separately as applications on the tablet, which is described in detail in Chapter 3. The dependent variables in this study are information overload, efficiency, effectiveness and satisfac- tion. These variables have the following descriptions:
Information Overload: is when a user perceives any of the following responses stated by Hiltz • & Turoff [1985]:
– ”fails to respond to certain inputs,
31 – responds less accurately than they would otherwise, – responds incorrectly, – store inputs and then respond to them as time permitted, – systematically ignore some features of the input, – recode the inputs in a more compact or effective form or – quit in extreme cases.”
For this study we designed a number of questions to follow up on this phenomenon. Those questioned are explained in a later section of this chapter.
Efficiency: is the measured time it takes to complete all the tasks associated with a task sheet • and related to an application, with either the 2D UI or the 3D UI. The most efficient UI is the one that takes the least time to complete the task sheet.
Effectiveness: is the accuracy and completeness of the given tasks. For the purpose of this • experiment the answers to the tasks are checked and evaluated. There are three measurements, no answer, incomplete and complete.
Satisfaction: is the user’s subjective measure of what feels comfortable or not with regards to • one of the UIs. This is being measured by a questionnaire in this study.
4.2.2 Confounding Variables
We have identified a number of confounding variables in this study and have taken steps to alleviate their effects. This study compares a new UI with a standard UI and with any innovative products there may be bias toward the standard UI. It is possible participants may reject the idea of the new UI and vote toward the familiar product. It was not in the best interest of this study to involve participants with no previous knowledge of Twitter or mobile device participate. The usage pattern and familiarity with Twitter and mobile devices is being documented and evaluated in a demographic survey. It is also possible that a participant’s lack of knowledge or lack of familiarity could adversely affect the outcome of this study. This is why we decided to introduce ‘Warm Up Exercises’ for each UI. It gives the participants the opportunity to study the different UIs to their satisfaction. There was no time limit for the exercise sessions, instead participants were encouraged to practice as long as they needed to feel comfortable handling the UI. There was no need to switch devices, which equalises the conditions for both UIs. Cockburn & McKenzie [2001] describe a similar experiment to the one done here. The experimental design deals with similar confounding variables for example the risk of the learning effect. It also uses a within participant design to counteract those confounding variables. It lists variables like 3D Fidelity, meaning the quality of the 3D interface presentation and familiarity and subject pool, meaning the users are used to the 2D not the 3D. Because we chose a within participant design for this comparative test, we had the advantage of requiring fewer participants, which were each subject to both independent variables. This reduced the difference between participants. The disadvantage using this procedure is that every participant is so
32 called ‘contaminated’ after being subject to one independent variable. Learning and weariness are two common effects found under these circumstances. To minimise the data contamination the order of appearance is counterbalanced, which means the effect of each level of independent variable is equally distributed. To achieve this counterbalance the UI given to the participants first, was alternated. Spatial orientation, specifically navigation in a 3D space, is an important factor in this study. Participants may not be aware of the availability of of a swivel chair or even be aware that it is to their advantage to use it. We therefore make it clear during the warm up exercise, that they are meant to swivel i.e. rotate to both sides to view the information given by the application. Other confounding variables that may come to mind are gender and age. Gender should not make a difference on the ability to complete the tasks for this study. There are no gender specific tasks given to the participants. Age only creates a problem, if you consider older participants may not know Twitter or microblogging in general, which is alleviated by the inclusion criteria documented in the next section. Lastly we discussed the possibility of the preferred hand being a confounding variable, but came to the conclusion that it is not in this case. This is because there are no interactions with the application, which require the user to use a particular hand. For full motion a tablet is usually held in both hands and when a participant needs to write as well as read they are expected to either put down the tablet or hold it in one hand and write with the other.
4.3 Methodology
4.3.1 Participants
For this study 32 participants, of whom 22 are male and 10 are female, were recruited from the University of Otago Campus. Because it is necessary to be familiar with the social media and Twitter client and with mobile devices, most participants were recruited with its help, the rest were enlisted by word of mouth and flyers around the university campus. All participants are aged between 20 and 56 years old (M=28.69, SD=6.99), with the following age groups: most participant were in the group of 20-29 year olds (21 participants), of those there were 4 females and 17 males, 10 participants were in the 30-39 year olds group with 6 females and 4 males and one male participant was over 40. None of the participants had ever used either of the prototypes before, but have had various experience with mobile devices with touch screens and with the microblogging application Twitter.
4.3.2 Inclusion Criteria
There are two criteria that every participant had to comply with:
Every participant must have a Twitter account and must have used it before (i.e. follow some- • one/have someone follow her/him).
Every participant must have had some experience with a mobile device with a touch screen, • either a smartphone or a tablet computer.
33 4.3.3 Tasks
The scenario designed for this study is that of a person missing a few hours of tweets on a random day. That person then goes along and uses either one of the prototypes to discover what has happened in her/his absence. A group of the participant’s friends on Twitter are trying to organise a party and also talk about some other events during their Twitter conversation. The tasks that each participant has to complete are of an information retrieval nature and do not require any text input into the device. The participant is however required to fill in the answers to the tasks on the task sheet for effectiveness measures. As already discussed earlier the measurements for effectiveness are no answer at all or incorrect answers, incomplete answers with some correct answers and complete and correct answers. No participant was forced to answer all tasks, only encouraged to do so. The time it takes to complete one task sheet using either the 2D or 3D UI is also noted as measurement for efficiency. Participants are not rushed to finish the tasks and no participant has been forced to finish before they were satisfied with their answers. Every participant receives one task sheet per application. Because we cannot have the same Twitter feed for both the 2D and the 3D application we have made up two separate conversation streams, which have each a different task sheet. This will reduce the ability of the participants to try and recall answers from the first task sheet, when working with the second. The tasks for both sheets are similar to the point that only names and events which are asked for are different.
The following two lists represent the questions asked on each task sheet.
Task Sheet A - Conversation 1
1. Search for a tweet with a ‘#Dunedin’ attached and mentioning @alice2012OU.
2. Party at Evan’s! Who showed up? If not, what did they do?
3. What events are happening this coming weekend in Dunedin?
Task Sheet B - Conversation 2
1. Search for a tweet with a ‘#Dunedin’ attached and mentioning @alice2012OU.
2. Party at Evan’s! Who showed up? If not, what did they do?
3. What events are happening this coming weekend in Dunedin?
The complete conversations and task sheets are attached in Appendix E.
There are three tasks on each task sheet. The tasks on sheet A differ slightly from sheet B to fit to the corresponding conversation. The first task on each sheet is a little easier to give participants a little encouragement when the start up. The second task is asking about the organisation of a party and who is participating, which is a big task requiring the user to go through the entire timeline of tweets. It can be shortcut by using the pre categorised Twitter feed panes. The third and last task asks a
34 more general question, which relates to what events are happening in Dunedin the coming weekend. That information can also be found in pre categorised Twitter panes. The warm up exercise was done in the same environment as the actual tasks, only the Twitter panes from the real prototype were replaced by scrollable poems. The participants were supposed to read those and practice the scrolling and when practicing on the 3D client also get comfortable with the 3D environment and the rotation movements to explore it.
4.3.4 Questionnaires
Participant are asked to fill out a series of questionnaires as measurements for information overload and user satisfaction. The questionnaires handed out after each session, also called post-application questionnaires, are independent ratings assessment of the participant’s perception and feelings of each UI. At the end of the study the participants also were handed a summarising questionnaire for a comparative assessment of the two UIs. A demographic questionnaire gauged participant’s experience with Twitter and collected data on what tools they used in the past to tweet.
Post-Application Questionnaire
The post-application questionnaire is made up of two parts. The first part asks the participants questions to measure the user’s level of information overload and about their interaction with the UI. The first question asked how difficult it was to get an overview of all the tweets listed, then participants were asked if they were confused by the user interface, if it was easy to find the relevant tweets and if it was easy to navigate the tweets. The last question inquired if they had the feeling there was too much information to handle. These questions were specifically designed for this user study. (Appendix A) The second part of this questionnaire focuses on the overall satisfaction of the participants using the prototype. These questions were slightly adapted from Teoh et al. [2011]. It start with asking how easy it is to use the system, then if the participant could correctly complete the tasks using the system, if the user was able to complete the tasks quickly using the system, if the participant was able to complete the tasks using this system with little effort, felt comfortable using the system, if it was easy to learn to use the system and if the user believes to become productive using the system. A reliability check or internal validation was done first as part of the analysis phase of the user study. Because this questionnaire had two sections of questions the internal validation was done for each section. The participants were also encouraged to leave comments on the last page of the questionnaire. Those did not factor into this analysis.
Summarising Questionnaire
The summarising questionnaire does a comparison between the two user interfaces, 2D and 3D. The questionnaire inquires the following of the participants: what interface the overall preferred, using which interface did they feel more information overload, when it was easier to navigate the tweets,
35 when they could more easily remember the tweets and which user interface was easier to use. All these questions were specifically designed for this experiment. (Appendix B)
Demographic Questionnaire
The demographic questionnaire collects the following data: age and gender, how many people do they follow on Twitter and then to split those people into friends, companies, celebrities, news organisations and promotions, how important it is to them to read the Twitter timeline, how frequently they read it and how frequently they post on Twitter, which type of client interface they use and which one they use most when reading tweets. The data gathered with the questionnaire is to determine participants not suited for this study, to control for the confounding variables and possibly to help clarify some unusual behaviour by participants.
4.3.5 Materials and Apparatus
The experiment was conducted in a room of the MSRL lab, which was only used by us for duration of this study. The room was properly heated and had several large desks in it. It also had several swivel chairs, one at least is necessary for the participant’s chair. The large desks allowed the experimenter to organise all the information for the participants and gave the participants plenty of room to write on. To avoid outside distraction we closed the curtains of all the windows and made sure no one entered during the experimentation. Figure 4.1 shows a participant in action. We thought it best to have the two experimenters facing the user and not have them sit behind the participant. This may have irritated them and/or make them feel uncomfortable. One of the experimenters was responsible for all the interactions and help if needed and the other was making notes and observations. The tablet computer used during this study was the Samsung Galaxy Tab 7.7
Figure 4.1: A participant using the prototype. tablet running the Android 3.2 OS. For the duration of the experiment the tablet had 6 applications installed and visible on the desktop of the device as can be seen in Figure 3.18. Those are the two 2D applications and two 3D applications, one for each conversation, as well as the warm up exercises for the 2D and 3D UIs. Apart from that the tablet was left in its original configuration.
36 4.3.6 Experiment Design
This experiment had thirty-two participants partake in a within subjects tests. Each participant completed the information retrieval tasks for both UIs. Table 4.2 shows how we counterbalanced in which order the two different task sheets and applications were executed by the participants. Since we needed to have a different set of conversations for the second session, we decided it is also necessary to randomise those as is also shown in Figure 4.2.
Figure 4.2: Counterbalanced possibilities of order of presentation for the two independent UIs.
To compensate for the difference in makeup of the test group, we decided to use a within subject design discussed in Chandrasekaran et al. [2003]. A between subjects design would yield the opposite effect and lead to skewed results.
4.3.7 Procedure
During recruitment of the participants for this study, we informally screened them when possible for suitability. Then they were booked into sessions of an interval of 1 hour over several weeks. During the pilot study we estimated that it takes about 30-45 minutes to complete experiment. Apart from a few participants that was the case. Upon the participant’s arrival both experimenter introduced themselves and the participant was guided to a swivel chair next a desk. They were then ask to make themselves comfortable and make sure the chair is set up right for them. Then we asked the participants to read the ‘Information Sheet’ (Appendix D) and ask any questions as they may come up. Attached to the information sheet was a consent form explaining the participant’s rights and anonymity. Before beginning with the ac- tual experiment the participants were asked to complete the ‘Demographic Questionnaire’ (Appendix C). After that the participants were handed the ‘Task Description’ (Appendix E) and had another opportunity to ask questions. Every participant received the same set of instructions during their warm up exercise, detailed toward the 2D application or the 3D application. They then had the chance to get used to either UI and if needed ask questions about any technical aspect such as how to scroll. It is important the participant feels comfortable with the UI and her/his chair and is able to navigate the application. To make sure the same information was passed to each participant a script was written from which the experimenters could follow the steps and read off. The timed sessions start with the experimenter writing down the start time and starts the stop-
37 watch to get the exact time. From then on it is important the experimenter watches the participant closely to note any observable behaviour in the previously prepared notebook. This notebook has the participant number and all the timing information and any observations in it. If the participants have any comments during or after the study, those also got written in this notebook. When the session is over the finish time and the stopwatch time are noted. After both session have been completed the study concluded with an informal debriefing and the presentation of a choice of chocolate bars as a thank-you gesture.
4.4 Assumptions
There are a number of assumption we have made in order for this study to yield usable results. The following assumptions apply to the devices and software testing of the hypotheses:
The 2D UI is implemented to give the best possible experience of a comparable mainstream • application to the participant. This would mean that we assume the results of this study are significant to real world tasks.
The questionnaires are an appropriate measure of information overload and user satisfaction. • There will be observations during the experiments to support the results from the questionnaires.
For this user study we assume that the group of participants is a representation of common Twitter users. Another assumption is that we can observe a balanced transfer of learning effect, produced by the chosen experiment design. If the results of this study are to add to the pool of knowledge in this field, it is important to keep the context of this study as close as possible to the real world.
4.5 Data Collection
To compare the 2D UI with the 3D UI we collected a number of different types of data, all related to information overload or usability. Measuring the efficiency of a participant completing a set of tasks for one UI was done by hand. The second experimenter was in charge of timing the participants. He had a stop watch to note down the time it took and also wrote down start and end time. We report the time in minutes. To measure the effectiveness of the participants we collected their answer sheets at the end of a session and evaluated their answers. The evaluation of those sheets was done by one of the experi- menters and was a simple procedure with three possible outcomes: no answer, incomplete, complete and correct. The rest of the data was collected via the questionnaires in the form of a 7-point Likert scale or a ranking scale for the preferred UI [Gliem & Gliem, 2003]. This data is used to analyse the participants information overload and satisfaction. The participants were also encouraged to leave open ended comments where ever they felt appropriate either in writing on the questionnaire or verbally.
38 Chapter 5
User Study Results
5.1 Overview
It is the purpose of this study to investigate the usability and the information overload experienced by the user. To do this we compare the two independent variables, the 2D UI with the 3D UI, measuring the usability, in detail the efficiency, effectiveness and satisfaction of a user as well as the information overload they may experience when completing the set of tasks explained earlier. In this chapter we summarise the results of the study divided into the following sections: UI efficiency, UI Effectiveness, UI satisfaction and UI information Overload. To perform the data analysis we used SPSS version 20 and all the significance testing was done at the 95% confidence interval. We used a one-way repeated measures analysis of variance, called ANOVA, to test for significance of the effect of the independent variable, UI. A 7-point Likert scale, which allowed the participants to answer questions between 1 and 7 was used for the post-application questionnaire. The distribution of the 7-point Likert scale data collected is approximately normally distributed and treated as interval data. Figures 5.1 and 5.2 depict the distribution for the data collected. During this analysis the data from all 32 participants was used and no outliers were excluded (See Appendix F).
39 Figure 5.1: Normal distribution of collected information overload data indicating the use of the ANOVA method for variance analysis.
Figure 5.2: Normal distribution of collected user satisfaction data indicating the use of the ANOVA method for variance analysis.
5.2 User Interface Efficiency
To measure the user interface efficiency of each participant we timed every one for the completion of each task sheet. This gave us the individual time for the 2D and the 3D conditions of every participant. In this case we want to know if there is a significant difference between the two conditions or not. The average across all participants for condition one or 2D is 5.78 minutes and the average across all participants for condition two or 3D is 6.5 minutes. Because this was just a time measurement and no questionnaire was involved, we do not have an alpha value for reliability. As shown in Table 5.1 and in Figure 5.3 the 3D UI task completion (M = 6.5, SD = 4.06) is a little slower than the 2D UI task completion (M = 5.78, SD = 2.49). There is no evidence that those means have a statically significant difference as determined by one-way ANOVA (F(1,62) = 1.712, P = .2). However this was highly and significantly correlated as shown in Table 5.2 with a value of r =
40 Figure 5.3: Showing the difference in time between condition 1 and 2 including error bars.
UI Efficiency (Task Time) 2D UI 3D UI Mean 5.78 6.5 Std. Deviation 2.49 4.06 Std. Error 0.44 0.72
Table 5.1: Results for task completion time.
0.639.
Correlations 2D UI 3D UI 2D UI Pearson Correlation 1 0.639 Sig. (1-tailed) 0.0 N 32 32 3D UI Pearson Correlation 0.639 1 Sig. (1-tailed) 0.0 N 32 32
Table 5.2: Results for correlations in efficiency data.
5.3 User Interface Effectiveness
As part of the user interface effectiveness measurement each participant filled out the task sheet with answers to the given questions. Those questions are than graded from 0 - 2. 0 is the lowest grade representing no correct answer or no answers given, 1 represents incomplete answers and 2 represents correct and complete answers. Each task sheet got one of those ratings assigned to it.
41 The average across all participants for condition one or 2D is 1.22 and the average across all participants for condition two or 3D is 1.22 . For these measurements we do not have an alpha value because no questionnaires were involved.
UI Effectiveness (Completeness / Correctness) 2D UI 3D UI Mean 1.22 1.22 Std. Deviation 0.42 0.42 Std. Error 0.07 0.07
Table 5.3: Results for completeness and correctness of tasks.
As shown in Table 5.3 the questions from the task sheet answered correctly for the 3D UI (M = 1.22, SD = 0.42) are even with that of the 2D UI (M = 1.22, SD = 0.42). There is no statical evidence that those means have any significant difference as determined by one-way ANOVA (F(1,62) = 1.712, P = .2). However this was highly and significantly correlated as shown in Table 5.4 with a value r = 0.634.
Correlations 2D UI 3D UI 2D UI Pearson Correlation 1 0.634 Sig. (1-tailed) 0.0 N 32 32 3D UI Pearson Correlation 0.634 1 Sig. (1-tailed) 0.0 N 32 32
Table 5.4: Results for correlations in effectiveness data.
5.4 User Interface Satisfaction
Measuring user interface satisfaction for each participant was done by a questionnaire after each application for the 2D and the 3D UI (Appendix A). Each question had a 7-point Likert scale, which allowed the participant to answer between 1 and 7. The higher the user answered each questions the higher was the user satisfaction with the user interface. This is the list of questions 6 to 12 relevant to user satisfaction:
Question 6: Overall, I am satisfied with how easy it is to use this system. • Question 7: I could correctly complete the tasks using this system. • Question 8: I was able to complete the tasks quickly using this system. •
42 Question 9: I was able to complete the tasks using this system with little effort. • Question 10: I felt comfortable using this system. • Question 11: It was easy to learn to use this system. • Question 12: I believe I could become productive quickly using this system. • The average across all participants for condition one or 2D is 4.94 and the average across all partic- ipants for condition two or 3D is 4.73. To make sure we can rely on the asked questions, we did a reliability analysis to determine the ‘Cronbach’s Alpha’ values. The Cronbach’s alpha for these sets of questions is 0.911 condition 1 and 2 combined as can be seen in Table 5.5.
Figure 5.4: Showing the difference of mean answers for every user satisfaction question between condition 1 and 2 including error bars.
UI Satisfaction 2D UI 3D UI Combined Mean 4.94 4.73 Std. Deviation 1.24 1.09 Reliability 0.936 0.883 0.911
Table 5.5: Results for user satisfaction.
As shown in Table 5.5 and Figure 5.4 the mean of the questions answered by the participants for the 3D UI (M = 4.94, SD = 1.24) are pretty close to the ones from the 2D UI (M = 4.73, SD = 1.09). There is also no statistical significance as found by one-way ANOVA (F(1,62) = .62, P = .437) and no correlation.
43 5.5 User Interface Information Overload
A questionnaire was used to measure information overload for each participant and given to them after each application session, the 2D and the the 3D UI, was finished (Appendix A). Each question had a 7-point Likert scale, which allowed the participant to answer between 1 and 7. The higher the user answered each question the higher was the participants perception of information overload while using the user interface. This is the list of questions 1 to 5 relevant to user satisfaction:
Question 1: It was difficult to get an overview by scanning the tweets. • Question 2: I was confused by the user interface. • Question 3: It was easy to find the relevant tweets. • Question 4: It was easy to navigate the tweets. • Question 5: I had the feeling there was too much information to handle. • The average across all participants for condition one or 2D is 4.71 and the average across all partic- ipants for condition two or 3D is 4.73. To make sure we can rely on the asked questions, we did a reliability analysis to determine the ‘Cronbach’s Alpha’ values. The Cronbach’s alpha for these sets of questions is 0.772 condition 1 and 2 combined as can be seen in Table 5.6.
Figure 5.5: Showing the difference of mean answers for every information overload question between condition 1 and 2 including error bars.
As shown in Table 5.6 and Figure 5.5 the mean of the questions answered by the participants for the 3D UI (M = 4.73, SD = .98) are pretty close to the ones from the 2D UI (M = 4.71, SD = 1.23). There is also no statistical significance as found by one-way ANOVA (F(1,62) = .013, P = .911) and has high correlation shown in Table 5.7.
44 UI Information Overload 2D UI 3D UI Combined Mean 4.71 4.73 Std. Deviation 1.23 0.98 Reliability 0.834 0.678 0.772
Table 5.6: Results for information overload.
Correlations 2D UI 3D UI 2D UI Pearson Correlation 1 0.37 Sig. (1-tailed) 0.019 N 32 32 3D UI Pearson Correlation 0.37 1 Sig. (1-tailed) 0.019 N 32 32
Table 5.7: Results for correlations in information overload data.
5.6 Other Discoveries and Observations
This section describes other findings made by the post application questionnaire, the post study questionnaire, comments made by the participants and general observations made by the experimenter. The observations made, provide further information for the usability and information overload analysis and point out possible limitations of this study.
5.6.1 Post-Study Questionnaire
The post-study questionnaire as the post-application questionnaire uses a 7-point Likert scale to measure the participants overall perception of the two user interfaces. Generally a positive answer means the 3D UI is preferred and a negative response indicates the preference for the 2D UI. This is not so with question 2. This question must be thought of as reversed, a positive outcome is good for the 2D UI and a negative outcome is good for the 3D UI. Table 5.8 and Figure 5.6 both display the results from this questionnaire. As you can see in Table 5.8 most questions results point to the preference of the 2D UI, except question 4. Participants preferred the 3D UI when asked which UI allows one to remember where tweets were more easily.
5.6.2 Participant Behaviours
We noted the following participant behaviours during the testing phase of the user study. The following comments and behaviours are about the 3D UI unless otherwise stated. Only 6 out of 32 participants stopped to orientate themselves in the 3D environment and get a mental map of where tweets can be
45 Figure 5.6: Showing the difference of mean answers for every question.
Overall Performance Mean Preferred UI Question 1 -0.1875 2D Question 2 0.09375 2D Question 3 -0.28125 2D Question 4 0.3125 3D Question 5 -0.59375 2D
Table 5.8: Results from the Post-Study Questionnaire. found by the pre-categorised filtering. Such a small number suggests that the majority of users take 2D interfaces for granted and naturally do not take advantage of the cognitive spatial orientation help that 3D interfaces can offer. Because participants had to write down the answers to the questions on the given task sheet, a lot of them had issues or awkwardness doing this especially with the 3D UI. The most preferred solution by the participants was to hold the tablet in one hand and write with the other. Only 2 participants put down the tablet and let it fall into the settings screen and then had both hands free to write. Better emphasis on the possibilities and option of the 3D environment, like suggesting the settings screen as a pause functionality to have hers/his hands free, may have benefited the participants. Following this observation we saw that most people struggled with the weight of the tablet in one hand, which was not intended. A small number of participants also struggled with holding the tablet up in the air in general. This is obviously a problem we have already talked about and felt we adequately addressed by choosing one of the lighter tablets, but still remains an issue. Some
46 participant went as far as putting their elbow and arm on the table with tablet in hand to relieve some weight. Future tablets may become lighter and render this issue void. With a few exceptions most participants struggled the most with the second task on the task sheet. This may have been related with the general twitter ability of the participant as well as with the difficulty of the question. We also noted that several participants were really excited about the 3D prototype application and felt something called the ‘WoW’ effect. Participants affected by this were commenting like Awesome!, Fun!, Very Cool!, When will it be in the Google market?.
47 Chapter 6
Conclusions
6.1 Discussion
Based on our results and informal observations and discussions with participants it is justified to assume that there is a difference between a 2D UI and a 3D UI. With the overwhelming number of of mobile application available on all the different platforms, usability and information presentation are important factors in the evaluation of such user interfaces. This study shows, that a new 3D user interface approach for mobile development does not reduce the usability of the developed application and may have further advantages. In our study the developed 3D prototype did not outperform the established 2D user interface, however the following sections demonstrate in more detail under what hypotheses the developed user interface shows promise and how it may succeed in the future. It will outline a number of ideas and proposals on how to continue the research into 3D user interface with focus on spatial awareness.
6.1.1 Usability
For the purpose of this user study, we decided to split up the factor usability into three parts. This created three separate hypotheses for efficiency, effectiveness and satisfaction. As Chapter 5 showed the usability of the 3D UI as measured by these three separate factors is as usable as the 2D UI. All three hypotheses have been statically supported.
Efficiency
Hypothesis 1: The 3D prototype will allow users to perform tasks as quickly as the 2D prototype. This hypothesis is supported. Although there is a small difference between the two results for the 2D UI and the 3D UI in Figure 5.3, there was no statistical evidence supporting that the times vary. The difference is not big enough to be a significant difference. This means even though the 2D UI yielded slightly faster times for the task completion the 3D UI performed competitively and the results are statistically even, which proves this hypothesis is supported.
48 Effectiveness
Hypothesis 2: The 3D prototype will have the same number of correct answers as the 2D prototype, when performing a set of tasks. This hypothesis is supported. As unlikely as it might seem the results for the 2D UI and the 3D UI are identical. The collected data is not identical, but the means and the standard deviations are. Statistically there is also no significant difference between both and hence this hypothesis is also supported. In addition it was discovered that both data sets from the 2D UI and the 3D UI session have a high correlation and therefore are directly connected.
Satisfaction
Hypothesis 3: The 3D prototype will perform as well as the 2D prototype during a satisfactory questionnaire. This hypothesis is supported. As the results in Chapter 5, Table 5.5 and Figure 5.4 showed, there is always a slight difference between the 3D UI and the 2D UI, generally better for the 2D UI. The exception is when the participants are asked, which system they thought they could correctly complete the task with. That question is slightly better for the 3D UI, which indicates the participants felt the 3D UI offers more support for the given tasks. Overall 2D seems to perform better, but it cannot be statistically proven, which leads to the conclusion that this hypothesis has been found supported as well.
6.1.2 Information Overload
Hypothesis 4: The 3D prototype will reduce information overload compared to the standard 2D application. This hypothesis is not supported. As discussed previously this research project looked for ways to reduce the information overload a user would experience when using a Twitter application as presented in Chapter 3. As explained in Chapter 5 with the help of Table 5.6 and Figure 5.5 there is no statistical relevant difference for the data. This is not bad result, but it is not what was expected. Questions 1, 2 and 5 have higher values for the 3D UI, but question 3 is almost even and question 4 leaves the 2D UI higher. Although this hypothesis cannot be statistically supported, it indicates this research topic has relevance and deserves further investigation.
6.1.3 Overall Performance
Hypothesis 5: The 3D prototype will overall outperform the 2D prototype. This hypothesis is not supported. Measuring the overall performance the 3D did not outperform the the 2D. Although the usability for the 3D interface was statistically not worse then the of the 2D user interface, the analysed data states that information overload was not reduced. Despite that fact, the data also showed that it was easier to navigate the tweets using the 3D user interface. The direct comparison between 2D and 3D
49 interface also revealed, that it was easier to remember where tweets are in the 3D user interface as shown by Figure 5.6 and Table 5.8.
6.1.4 Observations
From the behaviours and the comments made by participants one can deduce that there is a future for this type application, but a lot of work is needed to make it appealing to the user. Several hardware and software issues have been raised, some of which may be solved just by the gradual improvement of the technologies used to develop these prototypes. A few prominent issues are the weight of the tablet and awkwardness to hold it in one of more hands. Following the current trend the weight issues will solve itself with the evolution in computing devices, but the problems associated with handiness of the device may only be solved by replacing the tablet or adding in another device such as AR goggles or glasses. For further user tests with a similar or equal setup the task questions need to be revised and may require adjustment to be more clear and easier understood by the participants. It may also be good to revise and extend what a participant is told/explained at the start of each testing session to make sure they all have the same knowledge in regards to how to approach the application and complete the tasks to their best ability.
6.1.5 Summary
It is difficult to outperform an already well-established user interface with something completely new. Users are usually comfortable with the existing systems and do not want to spend time learning new systems, unless they have had problems or bad experiences with the old interface. It is therefore of great importance, when designing a new user interface, to pay attention to usability. This research set out to investigate a novel approach to solve the problem of information overload created by Web 2.0 social media applications on mobile devices.
6.2 Future Work
The results from this study give us the indication that there is more to be investigated in this domain, and further studies and development are currently being considered. Our user study as it is detailed in Chapter 4 was limited by the time and scope of the entire project. A deeper analysis of the already collected data may surface more interesting and surprising information, such as if males or females have had more success with the 2D UI or the 3D UI. Further exploration of this prototype in terms of user studies might bring more useful data to help comprehend the issues and successes with regard to usability and information overload. Those may involve a clear separation of beginner to advanced Twitter users or beginner to advanced touch UI users. Again the moderate scope of this project limited the development time that was put into the prototype applications presented in Chapter 3. There are several hardware and software improvements which could increase the interface’s usability and increase the sense of spatial awareness of the users. One of the areas to improve on is the scrolling mechanism currently implemented, i.e. for the scrolling
50 to take affect you need to lift the finger of the tablet and scroll in a different direction. Adding the additional features of location based information filtering or location based desktop changes may be a great improvement for this particular Twitter application. In general the entire information filtering should be adjustable by the user. Every user feels comfortable with a different arrangement and should be able to choose the way s/he filters or displays the Twitter panes. With user centric adjustment capability s/he can have the information arranged in a meaningful fashion to her/him. Adding AR goggles or glasses as recently demonstrated by Google Google [2012b] can enhance user emergence for the interface again and give the user more freedom to move and may make the use of a tablet redundant. Although some sort of control mechanism would still be needed.
51 References
3DAR (2013). 3DAR - apps. 3DAR. URL http://3dar.us/apps/
Apple (2012). iOS dev center - apple developer. iOS Developers Center. URL https://developer.apple.com/devcenter/ios/index.action
ARApplications (2013). The 10 coolest augmented reality apps complex. 10 Coolest AR Apps. | URL http://goo.gl/hXLN5
Ardor3D (2012). Ardor3D. Java-based 3D engine. URL http://www.ardor3d.com/
Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001). Recent advances in augmented reality. Computer Graphics and Applications, IEEE, 21 (6), 3447. URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=963459
Azuma, R. T. (1997). A survey of augmented reality. Presence-Teleoperators and Virtual Environ- ments,6 (4), 355385.
Belin, M. W., & Khachikian, S. S. (2007). Keratoconus: it is hard to define, but. American journal of ophthalmology, 143 (3), 500503. URL http://omnisrl.com.ar/descargas/belin_khakian_keratoconus.pdf
Billinghurst, M., & Starner, T. (1999). Wearable devices: new ways to manage information. Computer, 32 (1), 5764. URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=738305
Blackberry (2012). BlackBerry. BlackBerry Developers Web portal. URL https://developer.blackberry.com/
Burigat, S., & Chittaro, L. (2007). Navigation in 3D virtual environments: Effects of user experience and location-pointing navigation aids. International Journal of Human-Computer Studies, 65 (11), 945–958. URL http://linkinghub.elsevier.com/retrieve/pii/S1071581907000985
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction.
52 Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M. J., Hellerstein, J. M., Hong, W., Krish- namurthy, S., Madden, S. R., Reiss, F., & Shah, M. A. (2003). TelegraphCQ: continuous dataflow processing. In Proceedings of the 2003 ACM SIGMOD international conference on Management of data, (p. 668668). URL http://dl.acm.org/citation.cfm?id=872857
Chimienti, V., Iliano, S., Dassisti, M., Dini, G., & Failli, F. (2010). Guidelines for implementing augmented reality procedures in assisting assembly operations. In S. Ratchev (Ed.) Precision As- sembly Technologies and Systems, vol. 315 of IFIP Advances in Information and Communication Technology, (pp. 174–179). Springer Berlin Heidelberg. URL http://dx.doi.org/10.1007/978-3-642-11598-1_20
Cockburn, A., & McKenzie, B. (2001). 3D or not 3D?: evaluating the effect of the third dimension in a document management system. In Proceedings of the SIGCHI conference on Human factors in computing systems, (p. 434441). URL http://dl.acm.org/citation.cfm?id=365309
Curran, K., Morrison, S., & Mc Cauley, S. (2012). Google+ vs facebook: The comparison. Telekom- nika, 42 (2), 379388.
Darken, R. P., & Sibert, J. L. (1996). Navigating large virtual spaces. Philosophical Transactions of the Royal Society of London. B, Biological Sciences.
Ebner, M., & Schiefner, M. (2008). Microblogging-more than fun. In Proceedings of IADIS mobile learning conference, vol. 2008, (p. 155Y159). URL http://lamp.tu-graz.ac.at/~i203/ebner/publication/08_mobillearn.pdf
Facebook (2012). Welcome to facebook - log in, sign up or learn more. Facebook. URL https://www.facebook.com/
Falaki, H., Mahajan, R., Kandula, S., Lymberopoulos, D., Govindan, R., & Estrin, D. (2010). Diversity in smartphone usage. MobiSys ’10.
Feiner, N. J. D. S. K. (????). Addressing information overload in urban augmented reality applications. URL http://www-users.cs.umn.edu/~bhecht/geohci2013ps/paper_60.pdf
Gliem, J. A., & Gliem, R. R. (2003). Calculating, interpreting, and reporting cronbachs alpha relia- bility coefficient for likert-type scales. URL https://scholarworks.iupui.edu/handle/1805/344
Google (2012a). Android. Android Developers Web portal. URL http://developer.android.com/
Google (2012b). Google begins testing its augmented-reality glasses - NYTimes.com. http://goo.gl/eOCFU.
Google (2013). Google+. Web portal. URL https://plus.google.com/
53 Grubert, J., Langlotz, T., & Grasset, R. (2011). Augmented reality browser survey. Tehnical report, Institute for Computer Graphics and Vision, Graz University of Technology, Austria. URL http://www.icg.tu-graz.ac.at/publications/augmented-reality-browser-survey-1
GyroDroid (2012). GyroDroid 2.0 - access each and every sensor on android devices. Gyro Droid. URL http://goo.gl/z9xNe
Haller, M., Billinghurst, M., & Thomas, B. H. (2006). Emerging Technologies of Augmented Reality. Hershey, PA, USA: IGI Publishing.
Hiltz, S. R., & Turoff, M. (1985). Structuring computer-mediated communication systems to avoid information overload. Communications of the ACM, 28 (7), 680689. URL http://dl.acm.org/citation.cfm?id=3895
Honey, C., & Herring, S. C. (2009). Beyond microblogging: Conversation and collaboration via twitter. In System Sciences, 2009. HICSS’09. 42nd Hawaii International Conference on, (p. 110). URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4755499
Honeycutt, C., & Herring, S. C. (2009). Beyond microblogging: Conversation and collaboration via twitter. Proceedings of the Forty-Second Hawai’i International Conference on System Science IEEE, 10.
HP (2012). Home - HP webOS developer center. HP Developer Center. URL https://developer.palm.com/
ISO (1998). Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability. Geneva, Switzerland: International Organization for Standardization. URL http://goo.gl/XmhZk
ISO (2010). Ergonomics of human-system interaction – Part 210: Human-centred design for interac- tive systems. Geneva, Switzerland: International Organization for Standardization. URL http://goo.gl/qdVKU
Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 60 (11), 2169–2188. URL http://doi.wiley.com/10.1002/asi.21149
Java, A., Finin, T., Song, X., & Tseng, B. (2007). Why we twitter: Understanding microblogging usage and communities. In Joint 9th WEBKDD and 1st SNA-KDD Workshop 0. URL http://dl.acm.org/citation.cfm?id=872857 jMonkeyEngine (2012). jMonkeyEngine.org jMonkeyEngine community. jMonkey Engine. | URL http://jmonkeyengine.org/ jPCT AE (2012). jPCT-AE - a free 3D engine for android. jPCT-AE. URL http://www.jpct.net/jpct-ae/
54 Jul, S., & Furnas, G. W. (1997). Navigation in electronic worlds: a chi 97 workshop. SIGCHI Bull., 29 (4), 44–49. URL http://doi.acm.org/10.1145/270950.270979
Junaio (2012a). Junaio augmented tomorrow. Junaio AR. | URL http://augmentedtomorrow.com/tag/junaio/
Junaio (2012b). junaio blog all the news that’s fit to junaio page 18. Junaio AR Blog. | | URL http://goo.gl/GjESy
Karpischek, S., Magagna, F., Michahelles, F., Sutanto, J., & Fleisch, E. (2009). Towards location- aware mobile web browsers. In Proceedings of the 8th International Conference on Mobile and Ubiquitous Multimedia, MUM ’09, (pp. 18:1–18:4). New York, NY, USA: ACM. URL http://doi.acm.org/10.1145/1658550.1658568
Kim, T., Jeong, H. Y., Chew, Y. C., Bonner, M., & Stasko, J. (2010). Social visualization for micro- blogging analysis.
Layar (2012a). Layar for android leads the way in augmented reality apps. http://goo.gl/IDE2c.
Layar (2012b). Layar player layar. Layar. URL http://www.layar.com/player/
Layar (2012c). Make your own layar screen shot with the dreamcatcher layar blog. URL http://goo.gl/rROLu
LibGDX (2012). libGDX - 2D & 3D game development framework written in java for desktop and android. Lib GDX. URL http://libgdx.badlogicgames.com/
Linderdaum (2012). Linderdaum engine. Linderdaum Engine. URL http://goo.gl/ds9UW
Marmalade (2012). Marmalade: Mobile applications development, iPhone & android app development. Marmalade. URL http://www.madewithmarmalade.com/
Mathioudakis, M., & Koudas, N. (2010). Twittermonitor: trend detection over the twitter stream. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, (p. 11551158). URL http://dl.acm.org/citation.cfm?id=1807306
Mediabistro (2012). Twitter stats. http://goo.gl/xZeti.
MeeGo (2012). MeeGo. URL https://meego.com/
55 Mercedes (2013). Get inside new mercedes models with 3D AR app - PSFK - PSFK. Mecerdes with AR. URL http://goo.gl/O8Oux
Metaio (2012). metaio augmented reality products & solutions. Metaio AR. | URL http://www.metaio.com/
MetaioRetail (2013). metaio retail augmented reality products & solutions. Metaio AR Retail. | | URL http://www.metaio.com/retail/
Microsoft (2012). Windows phone cell phones, mobile downloads, mobile apps, and more windows | | phone 7. Windows Phone. URL http://www.microsoft.com/windowsphone/en-us/default.aspx
Mischaud, E. (2007). Twitter: Expressions of the whole self. An in. URL http://www.enterprise20.centrestage.de/pdf/Mischaud_final.pdf
Mixare (2012). mixare free open source augmented reality engine. Mixare. | URL http://www.mixare.org/
MootDroid (2012). MootDroid: android-3d-engine - 3D engine for android- google project hosting. MootDroid. URL http://code.google.com/p/android-3d-engine/
Mu, X. (2004). Smartlinks in a video-based collaborative distance learning system: a cognitive model and evaluation study. Ph.D. thesis, Chapel Hill, NC, USA. AAI3156185.
M¨unster, J. (2012). My code project on github. Project Code - 3D-TWAPP. URL https://github.com/munju/3D-TWAPP
M¨unster, J., & Nowostawski, M. (2012). Virtual spatial-temporal annotation system: An augmented reality study (accepted). In A. Moore, & I. Drecki (Eds.) Geospatial Visualisation. Heidelberg: Springer.
Ogre (2012). OGRE open source 3D graphics engine. Ogre. URL http://www.ogre3d.org/
Passini, R. (1984). Spatial representations, a wayfinding perspective. Journal of environmental psy- chology,4 (2), 153164. URL http://www.sciencedirect.com/science/article/pii/S0272494484800316
Piekarski, W., & Thomas, B. (2002). Using artoolkit for 3d hand position tracking in mobile outdoor environments.
Prime31 (2012). Unity 3d plugin development. http://www.prime31.com/.
Raper, J., Gartner, G., Karimi, H., & Rizos, C. (2007). Applications of location-based services: a selected review. J. Locat. Based Serv.,1 (2), 89–111. URL http://dx.doi.org/10.1080/17489720701862184
56 Robertson, G., Czerwinski, M., Larson, K., Robbins, D. C., Thiel, D., & Van Dantzich, M. (1998). Data mountain: using spatial memory for document management. In Proceedings of the 11th annual ACM symposium on User interface software and technology, (p. 153162). URL http://dl.acm.org/citation.cfm?id=288596
Satyanarayanan, M. (1996). Fundamental challenges in mobile computing. In Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing, (p. 17). URL http://dl.acm.org/citation.cfm?id=248053
Schmalstieg, D., Fuhrmann, A., Hesina, G., Szalav´ari, Z., Encarna¸c¨ao,L. M., Gervautz, M., & Pur- gathofer, W. (2002). The studierstube augmented reality project. Presence: Teleoper. Virtual Environ., 11 (1), 33–54. URL http://dx.doi.org/10.1162/105474602317343640
Schmalstieg, D., & Wagner, D. (2008). Experiences with handheld augmented reality. ISMAR 2007, (pp. 3–18).
Schwartz, B. (2004). The paradox of choice: Why less is more. New York: Ecco.
Sheridan, T., & Ferrell, W. (1974). Man-machine systems: information, control, and decision models of human performance. Cambridge, Mass.: MIT Press.
Shiva3D (2012). Shiva3D: Cross-Platform 3D game engine with all-in-one visual editor. Shiva3D. URL http://goo.gl/hKzGL
Statisticbrain (2012). Twitter stats. http://goo.gl/wZLGT.
Teoh, C., Regenbrecht, H., & O’Hare, D. (2011). The transmission of self: body language availability and gender in videoconferencing. In Proceedings of the 23rd Australian Computer-Human Interac- tion Conference, (p. 273280). URL http://dl.acm.org/citation.cfm?id=2071581
Twitter (2012). Twitter. Twitter. URL https://twitter.com/
UMPCPortal (2012). Top 12 tablet weights compared at 595 grams, sonys tablet s is the second lightest 10 tablet on the market UMPCPortal portable, mobile and handheld computers. | URL http://goo.gl/JzOxw
Unity3D (2012). UNITY: game development tool. Unity 3D. URL http://unity3d.com/unity/
Vieweg, S., Hughes, A. L., Starbird, K., & Palen, L. (2010). Microblogging during two natural hazards events: what twitter may contribute to situational awareness. In Proceedings of the 28th international conference on Human factors in computing systems, (p. 10791088). URL http://dl.acm.org/citation.cfm?id=1753486
57 Wagner, D., & Schmalstieg, D. (2003). First steps towards handheld augmented reality. In Proceedings of the 7th International Symposium on Wearable Computers (ISWC’2003), (p. 127137). URL http://goo.gl/kP3ib
Wagner, D., & Schmalstieg, D. (2009). History and future of tracking for mobile phone augmented reality. In Ubiquitous Virtual Reality, 2009. ISUVR’09. International Symposium on, (p. 710). URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5232244
Wikipedia (2012). Microblogging - wikipedia, the free encyclopedia. Microblogging. URL http://en.wikipedia.org/wiki/Micro-blogging
Wikitude (2012a). Wikitude augmented reality browser now offers android honeycomb tablet support geeky gadgets. URL http://goo.gl/dBwQQ
Wikitude (2012b). Wikitude SDK - add AR to your app. Wikitude AR. URL http://www.wikitude.com/developer/sdk
Wilson, M. L., & Schraefel, M. (2008). Improving exploratory search interfaces: Adding value or information overload? URL http://eprints.soton.ac.uk/266604/
Yin, J., & Carswell, J. D. (2012). Effects of variations in 3d spatial search techniques on mobile query speed vs. accuracy. In Web and Wireless Geographical Information Systems, (p. 116). Springer. URL http://link.springer.com/chapter/10.1007/978-3-642-29247-7_1
Yuen, S., Yaoyuneyong, G., & Johnson, E. (2011). Augmented reality: An overview and five directions for AR in education. Journal of Educational Technology Development and Exchange,4 (1), 119140. URL http://www.sfuedreview.org/wp-content/uploads/2012/08/AREducation-steve.pdf
58 Appendix A - Post-Application Questionnaire
59 participant #: date/time:
User Experiment: This user study is part of Julian Munster’s MSc work
Post-‐Application Questionnaire
Please read each statement and indicate how strongly you agree or disagree withthe statement by circling a number on the scale.
Please write comments to elaborate on your answers.
1. It was difficult to get an overview by scanning thetweets.
1 2 3 4 5 6 7 Strongly Disagree Strongly Agree
Comments:
2. I was confused by the user interface.
1 2 3 4 5 6 7 Strongly Disagree Strongly Agree
Comments:
3. It was easy to find the relevant tweets.
1 2 3 4 5 6 7 Strongly Disagree Strongly Agree
Comments:
60 4. It!was easy to navigate the tweets.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
5. I!had!the!feeling!there!was!too!much!information!to!handle.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
6. Overall, I am satisfied with how!easy it is to use this system.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
7. I!could correctly complete!the!tasks using this system.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
61 8. I!was!able!to!complete!the!tasks!quickly!using!this!system.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
9. I!was!able!to!complete!the!tasks!using!this!system with little effort.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
10. I!felt!comfortable!using!this!system.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
11. It!was!easy!to!learn!to!use!this!system.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
62 12. I!believe!I!could!become!productive quickly!using!this system.
1 2 3 4 5 6 7 Strongly!Disagree Strongly!Agree
Comments:
Comments on study:
Comments on system (hardware, software, other ...):
63 Appendix B - Post-Study Questionnaire
64 participant #: date/time:
User Experiment: This user study is part of Julian Munster’s MSc work
Post-‐Study Questionnaire
Please read each statement and indicate your preference by circling a number onthescale.
Please write comments to elaborate on your answers.
1. Overall I preferred:
3 2 1 0 1 2 3 2D Application 3D Application
Comments:
2. I felt more information overload in the:
3 2 1 0 1 2 3 2D Application 3D Application
Comments:
3. It was easier to navigate the tweets inthe:
3 2 1 0 1 2 3 2D Application 3D Application
Comments:
4. I could more easily remember the tweets inthe:
3 2 1 0 1 2 3 2D Application 3D Application
Comments:
65 5. It!was easier to use the:
3 2 1 0 1 2 3 2D Application 3D Application
Comments:
Comments on study:
Comments on system (hardware, software, other ...):
66 Appendix C - Demographic Questionnaire
67 participant #: date/time:
User Experiment: This user study is part of Julian Munster’s MSc work
Participant Demographic Survey
1. How old are you?
_____ years ○ Rather not say
2. What is your gender? ○ Female ○ Male
3. How many people do you follow on twitter? (include everyone youfollow)
_____ people (estimate)
4. How many of those are?
_____ friends (estimate)
_____ companies (estimate)
_____ celebrities (estimate)
_____ news organisations (estimate)
_____ promotions (estimate)
5. How important is it to you to read your twitter timeline? (not any tweet in particular)
Not at all 1 2 3 4 5 6 7 Extremely
68 6. How(frequently do(you(read(your twitter timeline? (((( ○ Not(at(all ○ Once a(week ○ Several times a(week ○ Every day ○ Several times a(day
7. How(frequently do(you(write a message on(twitter? (((( ○ Not(at(all ○ Once a(week ○ Several times a(week ○ Every day ○ Several times a(day
8. What client do(you(use(twitter on?((you(may choose more than one) (((( ○ Web application ○ Desktop application ○ Mobile application ○ Other ______
9. What application do you use most for(reading tweets with regards to your answer from above?((choose one) (((( ○ Web application ○ Desktop application ○ Mobile application ○ Other ______
69 Appendix D - Information Sheet and Consent Form
70 User Experiment: This user study is part of Julian Munster’s MSc work
Participant Information
Thank you for showing interest in this project managed by the department of Information Science. Please read this information sheet carefully before deciding whether or not to participate. If you decide to participate we thank you.Ifyou decide not to participate there will not be any disadvantage to you ofanykindand we thank you for considering our request.
What is the aim of this project? The aim of this project is to test for information overload and usability ofa new spatially designed user interface. Our prototype system creates a 3D world which gives an application use of more desktop space. This prototype enables us to investigate users’ perception of information and usability.
What will the participants be asked to do? Should you agree to take part of this experiment, you will be asked to use the tablet computer in front of you to complete several tasks. You are asked to dothesame tasks with two different interfaces and write down the answers on the task sheet (approx. 5 minutes each). At the end, you will be asked to fill in a questionnaire about your experience with and perception of the system.
Can participants change their minds and withdraw from theproject? You may withdraw from participation in the project without any disadvantage to yourself of any kind.
What data or information will be collected and what use will be made of it? The responses to the questionnaires will be recorded. Only the researchers Holger Regenbrecht, Mariusz Nowostawski, Julian Muenster and Jonny Collins willhave access to the data. Results of this project may be published but any data included will in no way be linked to any specific participant (anonymous).
What if participants have any questions? If you have any questions about this project, either now or in the future, please feel free to contact
Assoc. Prof. Holger Regenbrecht, Project supervisor University of Otago, New Zealand, Department of Information Science E-‐mail: [email protected] Tel. +64 3 4798322
Please keep this sheet if you like.
71 User Experiment : This user study is part of Julian%Munster’s MSc work
Consent Form For Participants
I, ______(please print your name)
� I%have read the Information Sheet%concerning this project%and understand what% it% is about. All my questions have been answered to my satisfaction. I% understand that%I%am free to request%further information at%any stage.
� My participation in the project%is entirely voluntary.
� I%understand that%I%may withdraw from the experiment%at%any time without%any disadvantage, including the withdrawal of any information I%have provided.
� All data%will be destroyed at%the conclusion of the project%but%any raw data%on which the results of the project%depend may be retained in secure storage for five years, after which it%will be destroyed.
� The results of the project% may be published and available in the library,% but every attempt%will be made by the researcher to preserve my anonymity.
Furthermore:
� I%may / may not%(please circle one) be quoted directly.
� If quoted directly, I%wish to remain anonymous / use%a pseudonym (please circle%one).
� If quoted directly, I%hereby grant%copyright%permission to the researcher for the purpose of publication: yes / no (please circle one).
� The researcher will confirm my consent% for individual quotes.
On this basis I%agree to participate as a%subject%in this project.
Signature:______% Date:______
72 Appendix E - Task Description, Task Sheets and Conversations
73 Julian Muenster Master of Science – User Study
Task Description
In this study you are using a tablet running the Android operating system. This tablet has two different applications installed, which both display a twitter timeline. You are asked to go through this timeline and answer a number of questions during the experiment. At no point during the study should you write a tweet yourself, delete any tweets or unfollow / follow any twitter user. After finishing the set of tasks you will be asked to fill in a questionnaire about your experience with and perception of the system. This will be repeated for both applications. There will be final survey at the end of the study.
The experimenter will now explain the details of this study and allow you to get familiar with the tablet and its functionality.
If you have any questions related to the tasks or study please feel free to ask them now.
Thank you Julian Muenster
74 participant #: date/time:
User Experiment: This user study is part of Julian Muenster’s MSc work
Participant Task Sheet A
1. Search for a tweet sent to `@david2012OU’ with a `#Dunedin’attached. What is it?
______
2. Party at Evan’s. Who showed up (a)? If not, what did they do instead(b)?
a)______
b)______
3. What events are happening this weekend in Dunedin?
______
______
75 participant #: date/time:
User Experiment: This user study is part of Julian Muenster’s MSc work
Participant Task Sheet B
1. Search for a tweet sent to `@frank2012OU’ with a `#Dunedin’ attached. What is it?
______
2. Party at Hugo’s. Who showed up (a)? If not, what did they do instead(b)?
a)______
b)______
3. What events are happening this weekend in Dunedin?
______
______
76 Twitter Conversations for the Study
Julian M¨unster
Conversation – 1
–––– around 9 am––––––––––––––––––––––
@alice2012OU Good Morning Dunedin! :) –––– around 10 am––––––––––––––––––––––
@charlie2012OU in reply to – Good Morning Dunedin! :) @alice2012OU Welcome back! How are you? Long time no see... @alice2012OU in reply to – Welcome back! How are you? Long time no see... @charlie2012OU Yeah I know, just back for the weekend. Living in Sydney now, but couldn’t miss graduation. –––– around 10:30 am––––––––––––––––––––––
@charlie2012OU in reply to – Yeah I know, just back for the weekend. Living in Sydney now, but couldn’t miss graduation. @alice2012OU Oh yeah very cool. Do the others know you are in town? @alice2012OU @charlie2012OU @bob2012OU @participant2012 @david2012OU @evan2012OU et al... I’m back in town... ;) @alice2012OU in reply to – Oh yeah very cool. Do the others know you are in town? @charlie2012OU Now they do!!! :P –––– around 11 am––––––––––––––––––––––
@bob2012OU in reply to – et al... I’m back in town... ;) @alice2012OU Awesome... Party time!!! @charlie2012OU in reply to – Now they do!!! :P @alice2012OU Sure do.... :P @bob2012OU –––– around 11:30 am––––––––––––––––––––––
1
77 @david2012OU in reply to – et al... I’m back in town... ;) @alice2012OU Great!!! What do you have planed? @alice2012OU in reply to – Great!!! What do you have planed? @david2012OU Well it’s my graduation and then party time... #Dunedin –––– around 12 am––––––––––––––––––––––
@evan2012OU in reply to – et al... I’m back in town... ;) @alice2012OU About time you come and visit us.... ;) @evan2012OU in reply to – Well it’s my graduation and then party time... @alice2012OU I see you want to party.... ;) in that case I say my flat as a venue!!! @david2012OU @charlie2012 @bob2012OU @participant2012 @alice2012OU in reply to – I see you want to party.... ;) in that case I say my flat as a venue!!! @evan2012OU That sounds like a great idea!!! Are you still living right in town? –––– around 1 pm––––––––––––––––––––––
@david2012OU in reply to – Well it’s my graduation and then party time... @alice2012OU What time are you planing to start, because unfortunately I have to work tonight... @alice2012OU in reply to – What time are you planing to start, because unfortunately I have to work tonight... @david2012OU oh nooo... well maybe you can make it into town later on and we catch up then! @david2012OU in reply to – oh nooo... well maybe you can make it into town later on and we catch up then! @alice2012OU brilliant :)... I will see you later. You still got the same mobile no? @alice2012OU in reply to – brilliant :)... I will see you later. You still got the same mobile no? @david2012OU Yes I do... catch you later! –––– around 2 pm––––––––––––––––––––––
@evan2012OU in reply to – That sounds like a great idea!!! Are you still living right in town? @alice2012OU sweet as all set up here & yes same place as before :) c u all here... @david2012OU @charlie2012 @bob2012OU @participant2012 @evan2012OU in reply to – oh nooo... well maybe you can make it into town later on and we catch up then! @david2012OU sorry to hear you got to work but as @alice2012OU said, will see you in town!!! :)
2
78 @bob2012OU @charlie2012OU @alice2012OU @participant2012 @david2012OU @evan2012OU will have to take it slow tonight, got a competition on Sunday... –––– around 3 pm––––––––––––––––––––––
@charlie2012OU in reply to – will have to take it slow tonight got a competition on Sunday... @bob2012OU awww come on!!!! It can’t be that big... what is it? @bob2012OU in reply to – awww come on!!!! It can’t be that big... what is it? @charlie2012OU actually it’s the ‘National IRB BP Surf Championships’ ... I’m a wildcard entry ;) @charlie2012OU in reply to – actually it’s the ‘National IRB BP Surf Championships’ ... I’m a wildcard entry ;) @bob2012OU That’s sweet as... we should all come and watch! @bob2012OU @charlie2012OU @alice2012OU @participant2012 @david2012OU @evan2012OU National IRB BP Surf Championships on Sunday Come & watch me #Dunedin @alice2012OU in reply to – National IRB BP Surf Championships on Sunday Come & watch me #Dunedin @charlie2012OU @bob2012OU @participant2012 @david2012OU @evan2012OU Let’s all party hard tonight and go support our man tomorrow @charlie2012OU in reply to – Let’s all party hard tonight and go support our man tomorrow @alice2012OU I’m in... Let’s do it! –––– around 4 pm––––––––––––––––––––––
@david2012OU in reply to – Let’s all party hard tonight and go support our man tomorrow @alice2012OU I’m in! Although I will see you guys in town... @evan2012OU in reply to – Let’s all party hard tonight and go support our man tomorrow @alice2012OU @bob2012OU @charlie2012OU @david2012OU @participant2012 I’ll show u guys how it’s done... :P (the partying, not surfing ;) ) –––– around 5 pm––––––––––––––––––––––
@alice2012OU Finally Party Time!!! Graduation Night..... :P @participant2012 @charlie2012OU @alice2012OU @participant2012 @david2012OU @evan2012OU Sorry, I had a late flight in, so see you all in a bit.
3
79 Conversation – 2
–––– around 9 am––––––––––––––––––––––
@julian2012OU Good Morning Dunedin! :) –––– around 10 am––––––––––––––––––––––
@issie2012OU in reply to – Good Morning Dunedin! :) @julian2012OU Welcome back! How are you? Long time no see... @julian2012OU in reply to – Welcome back! How are you? Long time no see... @issie2012OU Yeah I know, just back for a week. Living in Germany now, but couldn’t miss the wedding. –––– around 10:30 am––––––––––––––––––––––
@issie2012OU in reply to – Yeah I know, just back for a week. Living in Germany now, but couldn’t miss the wedding. @julian2012OU Oh yeah I heard about that. Do the others know you are in town? @julian2012OU @frank2012OU @geo↵2012OU @hugo2012OU @issie2012OU @participant2012b et al... I’m back in town... ;) @julian2012OU in reply to – Oh yeah I heard about that. Do the others know you are in town? @issie2012OU I hope I didn’t miss anyone!!! :) –––– around 11 am––––––––––––––––––––––
@frank2012OU in reply to – et al... I’m back in town... ;) @julian2012OU Awesome... We need to have a welcome back party!!! @issie2012OU in reply to – I hope I didn’t miss anyone!!! :) @julian2012OU I’m sure the right people will hear about it.... :P @frank2012OU #Dunedin –––– around 11:30 am––––––––––––––––––––––
@geo↵2012OU in reply to – et al... I’m back in town... ;) @julian2012OU Great!!! Do you have anything planed? @julian2012OU in reply to – Great!!! Do you have anything planed? @geo↵2012OU Well I thought maybe we can all catch up tonight... –––– around 12 am––––––––––––––––––––––
4
80 @hugo2012OU in reply to – et al... I’m back in town... ;) @julian2012OU About time you come and visit us.... ;) @hugo2012OU in reply to – Well I thought maybe we can all catch up tonight... @julian2012OU I see you want to party.... ;) in that case I say my flat as a venue!!! @frank2012OU @geo↵2012 @issie2012OU @participant2012b @julian2012OU in reply to – I see you want to party.... ;) in that case I say my flat as a venue!!! @hugo2012OU That sounds like a great idea!!! Are you still living right in town? –––– around 1 pm––––––––––––––––––––––
@geo↵2012OU in reply to – Well I thought maybe we can all catch up tonight... @julian2012OU What time are you starting, because unfortunately I have an exam later tonight... @julian2012OU in reply to – What time are you starting, because unfortunately I have an exam later tonight... @geo↵2012OU oh nooo... well maybe you can make it make after that! @geo↵2012OU in reply to – oh nooo... well maybe you can make it make after that! @julian2012OU yeah I will definitely make it into town. You still got the same mobile no? @julian2012OU in reply to – yeah I will definitely make it into town. You still got the same mobile no? @geo↵2012OU Yes I do... catch you later! –––– around 2 pm––––––––––––––––––––––
@hugo2012OU in reply to – That sounds like a great idea!!! Are you still living right in town? @julian2012OU all set up here & yes same place as before :) c u all here at 6ish... @frank2012OU @geo↵2012 @issie2012OU @participantb2012 @hugo2012OU in reply to – oh nooo... well maybe you can make it after that! @geo↵2012OU sorry to hear you have an exam but you can party even harder after! @issie2012OU @julian2012OU @frank2012OU @participantb2012 @geo↵2012OU @hugo2012OU I have an Ice Hockey game tonight, so won’t make it to the party! –––– around 3 pm––––––––––––––––––––––
frank@2012OU in reply to – I have an Ice Hockey game tonight, so won’t make it to the party! @issie2012OU awww come on!!!! Just hurry up and find us after your game! @issie2012OU in reply to – awww come on!!!! Just hurry up and find us! @frank2012OU actually tomorrow there is a one day international cricket match between NZ and Australia, can’t miss that.#Dunedin
5
81 @frank2012OU in reply to – actually tomorrow there is a one day international cricket match between NZ and Australia, can’t miss that.#Dunedin @issie2012OU Sweet as... we should all go down and support the Blackcaps!#Dunedin @frank2012OU @issie2012OU @julian2012OU @participantb2012 @geo↵2012OU @hugo2012OU one day international cricket; NZ vs Australia #Dunedin @julian2012OU in reply to – one day international cricket; NZ vs Australia #Dunedin @frank2012OU @issie2012OU @participantb2012 @geo↵2012OU @hugo2012OU Let’s all party hard tonight and go support our team tomorrow @issie2012OU in reply to – Let’s all party hard tonight and go support our team tomorrow @julian2012OU I’m in... Let’s do it! See you in town... –––– around 4 pm––––––––––––––––––––––
@geo↵2012OU in reply to – Let’s all party hard tonight and go support our team tomorrow @julian2012OU I’m in! Will see you in town... @julian2012OU in reply to – @frank2012OU @geo↵2012OU @issie2012OU @hugo2012OU @Participantb Also Elton John is giving a concert tomorrow #Dunedin @frank2012OU in reply to – Also Elton John is giving a concert tomorrow #Dunedin @julian2012OU Yeah, but tickets are sooo expensive! @hugo2012OU in reply to – Also Elton John is giving a concert tomorrow #Dunedin @julian2012OU Yeah too expensive as a student... –––– around 5 pm––––––––––––––––––––––
@julian2012OU Maybe you guys, @hugo2012OU and @frank2012OU are right... Time to party!!! Having an early start... :P @participant2012b @fronk2012OU @je↵2012OU @hugo2012OU @issie2012OU @julian2012OU Sorry, I had a late flight in, so see you all in a bit.
6
82 Appendix F - Statistical Analysis Data
83
Reliability IO Overall
Notes Output Created 07-SEP-2012 10:21:49 Comments Input Data
Active Dataset DataSet1 Filter
Matrix Input Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time 00:00:00.00 Elapsed Time 00:00:00.00 [DataSet1] /Users/jmuenster/Desktop/PostApp.sav Scale: ALL VARIABLES
Case Processing Summary
N % Cases Valid 6 4 98.5 Excludeda 1 1.5 Total 6 5 100.0
a.
Reliability Statistics
N of Items .772 5
DATASET ACTIVATE DataSet1. SAVE OUTFILE='/Users/jmuenster/Desktop/PostApp.sav' /COMPRESSED. DATASET ACTIVATE DataSet1. SAVE OUTFILE='/Users/jmuenster/Desktop/PostApp.sav' /COMPRESSED. RELIABILITY /VARIABLES=VAR00011 VAR00012 VAR00013 VAR00014 VAR00015 /SCALE('ALL VARIABLES') ALL Page 1
84 ��������������� ��
�����������������
����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������������ ���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� ����������������������������������������������� ��������������������
�����������������������
� � ����� ����� � � ���� ��������� � � ���� ����� � � �����
���
����������������������
���������� ���� � ��
����������� ��������������������������������������������������������� ����������������������������� ��������������� ��
������
85 �����������������
����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������������ ���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� ����������������������������������������������� ��������������������
�����������������������
� � ����� ����� � � ���� ��������� � � ���� ����� � � �����
���
����������������������
���������� ���� � ��
�������������������������� ��������������������������������������������������� ������������� ����������� ��������������������������������������������������������������������������� ����������������������������� ��������������� ��
�������������������������������� ������
86 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������������ ���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� ����������������������������������������������� ��������������������
�����������������������
� � ����� ����� � � ���� ��������� � ��� ����� � � �����
���
����������������������
���������� ���� � ��
����������� ��������������������������������������������������������������������������� ����������������������������� ��������������� ��
���������������������������
������
87 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������������ ���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� ����������������������������������������������� ��������������������
�����������������������
� � ����� ����� � � ���� ��������� � � ���� ����� � � �����
���
����������������������
���������� ���� � ��
�������������������������� ��������������������������������������������������� ������������� ����������� ��������������������������������������������������������������������������� ����������������������������� ��������������� ��
���������������������������
������
88 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������������ ���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� ����������������������������������������������� ��������������������
�����������������������
� � ����� ����� � � ���� ��������� � � ���� ����� � � �����
���
����������������������
���������� ���� �
������
89
EXAMINE VARIABLES=IO_CON1 IO_CON2 /PLOT BOXPLOT STEMLEAF /COMPARE GROUPS /STATISTICS NONE /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL.
EXAMINE VARIABLES=IO_CON1 BY CON /PLOT BOXPLOT STEMLEAF /COMPARE GROUPS /STATISTICS NONE /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore
Notes Output Created 11-SEP-2012 13:17:38 Comments Input Data
Active Dataset DataSet1 Filter
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time 00:00:00.17 Elapsed Time 00:00:00.00 [DataSet1] /Users/jmuenster/Desktop/PostApp.sav CON
Page 1
90 �����������������������
����� ����� ������� ����� ��� � ������� � ������� � ������� ������� � � � ������ � ���� �� ������ � � � ������ � ���� �� ������ ������� ������������������� ������������������������������ ������
��������������������������
������������������������� �������������������� ������������������������ ������������������������ ���������������������������� ������������������������� ��������������������������� ��������������������������� ����������������������������
���������������������� ���������������������������
������������������������������ ������
��������������������������
����������������������� ������������������������� ������������������������� ��������������������������� ���������������������������� ��������������������������� ��������������������������� ��������������������������
���������������������� ���������������������������
������
91 ����������������������������
����
����
����
���� ��������������������
����
����
�� �� ���������
��
�������������������������� ��������������������������������������������������� ������������� �������������������������� ��������������������������������������������������� ������������� �������������������������� ��������������������������������������������������� ������������� ������������������������������������������� ������������������������ ����������������� ������������������ ��������������� ������������������� ����������� �������
������
92 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� ����������������������������������������������� ���
�����������������������
����� ����� ������� ����� ��� � ������� � ������� � ������� ������� � � � ������ � ���� �� ������ � � � ������ � ���� �� ������ ����� � � � ������ � ���� �� ������ � � � ������ � ���� �� ������ ���� � � � ������ � ���� �� ������ � � � ������ � ���� �� ������ ������� ������������������� ������������������������������ ������
��������������������������
������������������������ ����������������������� ������������������������� ����������������������� ������������������������ ������������������������ ������
93 ������������������������������� ���������������������������� �������������������������� ������������������������
���������������������� ���������������������������
������������������������������ ������
��������������������������
����������������������� ������������������������ ����������������������� ������������������������� �������������������������� ����������������������������� ��������������������������� ��������������������������� ������������������������� �����������������������
���������������������� ���������������������������
��������������������
����
����
����
���� ����������������
����
����
�� �� ���������
������
94 ����� ������������������� ���������������������������� ������
��������������������������
�������������������� ������������������������������� ���������������������������� �������������������������������� ��������������������������� ����������������������� �����������������������
���������������������� ���������������������������
���������������������������� ������
��������������������������
����������������������� ���������������������������� ������������������������� ������������������������� ������������������������������� ������������������������� ������������������������ ������������������������� ������������������������������
���������������������� ���������������������������
������
95 ������������
� � �����
�����
�����
� � ����
�����
����
���
�� �� ���������
���� ������������������� ��������������������������� ������
��������������������������
����������������������������������������������� �����������������������������
���������������������� ���������������������������
��������������������������� ������
��������������������������
����������������������������������������������� �����������������������������
���������������������� ���������������������������
������
96 ����������������
� � � � � � � � ���� � � � �
����
���� �������� ����
����
����
�� �� ���������
������
97
DATASET ACTIVATE DataSet1. SAVE OUTFILE='/Users/jmuenster/Desktop/PostApp.sav' /COMPRESSED. GRAPH /SCATTERPLOT(BIVAR)=IO_CON2 WITH IO_CON1 /MISSING=LISTWISE.
IO Scatter Graph
Notes Output Created 11-SEP-2012 14:08:48 Comments Input Data
Active Dataset DataSet1 Filter
Syntax
Resources Processor Time 00:00:00.16 Elapsed Time 00:00:01.00 [DataSet1] /Users/jmuenster/Desktop/PostApp.sav
Page 1
98 ���������������������������������
����� ���� ��� ��� ��� ��� ��� ���� ���
�� ���������������
����
���������������
����
����
�������� �������� �������� �����������
��
������������ ���������������������������� ���������������������� �������������������������� �������������������� ������������
������
99 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� �����������������������������������������������
����������������������
���� � ������� ������ ������� �� ������� ������ ������ ��
������������
������� ������� ������� ������������������� � ����� ��������������� ���� � � � � � ������� ������������������� ����� � ��������������� ���� � � � � �
���
��
����� �������������������������������������� �������������������� ��
������������������
������
100 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������
��������� �������������� ����������� ������������ ����������� �����������������������������������������������
�����������������
����� � � � ����� � �
�� ���������������
�����
���� �����������
����
����
��� ��������� ����� ����� ����� �����������
��
������������ ������������������������ ���������������������� �������������������������� ��������������������
������
101 ������������
����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� �����������������������������������������������
����������������������
���� � ����� ������ ������� �� ����� ������ ������� ��
������������
����� ����� ����� ������������������� � ����� � ��������������� ���� � � � � � ����� ������������������� ����� � � ��������������� ���� � � � � �
����
��
����� ������������������������������������ �������������������� �����
������
102 ����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
������
��������� �������������� ����������� ������������ ����������� �����������������������������������������������
���������������������
����� ���� � � � � � � � � � ���� �
�� ���������������
����
���������������
����
����
�������� �������� �������� �����������
��
������������ ���������������������� ���������������������� �������������������������� ��������������������
������
103 ������������
����� �������������� �������������������� �������� ����� ����
�������������� �������� ������ ������ ������ ������ ���������� ������ � �
���������������������� ���������������������
����������
������
��������� �������������� ����������� ������������ ����������� �����������������������������������������������
����������������������
���� � ���� ������ ������ �� ���� ������ ������ ��
������������
���� ���� ���� ������������������� � ����� � ��������������� ���� � � � � � ���� ������������������� ����� � � ��������������� ���� � � � � �
����
������
104
GET FILE='/Users/jmuenster/Desktop/PostApp.sav'. DATASET NAME DataSet1 WINDOW=FRONT. DATASET ACTIVATE DataSet1. SAVE OUTFILE='/Users/jmuenster/Desktop/PostApp.sav' /COMPRESSED. EXAMINE VARIABLES=IO_CON1 SA_CON1 TIME1 ACC1 BY CON /PLOT NPPLOT /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL.
EXAMINE VARIABLES=IO_CON1 SA_CON1 BY CON /PLOT HISTOGRAM NPPLOT /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore
Notes Output Created 11-SEP-2012 12:21:46 Comments Input Data
Active Dataset DataSet1 Filter
Missing Value Handling Definition of Missing
Cases Used
Syntax
Resources Processor Time 00:00:01.69 Elapsed Time 00:00:02.00 [DataSet1] /Users/jmuenster/Desktop/PostApp.sav CON
Page 1
105 �����������������������
����� ����� ������� ����� ��� � ������� � ������� � ������� ������� � � � ������ � ���� �� ������ � � � ������ � ���� �� ������ ������� � � � ������ � ���� �� ������ � � � ������ � ���� �� ������
������������
��� ��������� ���������� ������� � ���� ������ ������ ����������� ������ ����������� ������ ��������������� ������ ������ ������ �������� ����� �������������� ������� ������� ���� ������� ���� ����� ���� ������������������� ���� �������� ����� ���� �������� ����� ���� � ���� ������ ������ ����������� ������ ����������� ������ ��������������� ������ ������ ������ �������� ���� �������������� ������ ������� ���� ������� ���� ����� ���� ������������������� ���� �������� ����� ���� �������� ����� ���� ������� � ���� ������ ������ ����������� ������ ����������� ������ ��������������� ������ ������ ������ �������� ����� �������������� ������� ������� ���� ������� ���� ����� ���� ������������������� ���� �������� ����� ���� �������� ���� ���� � ���� ������ ������ ����������� ������ ����������� ������
������
106 ������������
��� ��������� ���������� ��������������� ������ ������ ������ �������� ����� �������������� ������� ������� ���� ������� ���� ����� ���� ������������������� ���� �������� ����� ���� �������� ���� ����
������������������
������������������� ������������ ��� ��������� �� ���� ��������� �� ���� ������� � ���� � � ����� ���� � � ���� � ���� � � ����� ���� � � ���� ������� � ���� � � ���� ���� � � ���� � ���� � � ���� ���� � � ����
��� ���
������� ����������
��������� ����������
� ����������� ����������������� ����� �
�
�
� ���������
�
�
� ���� �������� �������� �������
������
107 ��������� ����������
� ����������� ���������������� ����� �
�
� ��������� �
�
� ���� ���� ���� ���� �������
����������������
������
108 �������������������������� ����������
�
�
�
� � ���������������
� �
� �
� �� �� �� ��������������
�������������������������� ����������
�
�
�
� � ���������������
� �
� �
� � � � � � ��������������
������
109 ��������������������������
������������������������������������ ����������
����
����
����� ���������������
�����
�����
�� �� �� ��������������
������
110 ������������������������������������ ����������
���
������ ��������������� � � � �
� � � �
�� �� �� ��������������
������� ����������
������
111 ��������� ����������
� � ����������� ����������������� ����� �
� �
�
� ���������
�
�
� �������� �������� �������� �������
��������� ����������
� � ����������� ���������������� ����� �
�
� ��������� �
�
� ���� �������� �������� �������
������
112 ����������������
�������������������������� ����������
�
�
�
� � ���������������
� �
� �
� � � � ��������������
������
113 �������������������������� ����������
�
�
�
� � ���������������
� �
� �
� �� �� �� ��������������
��������������������������
�������
114 ������������������������������������ ����������
����
����
����� ���������������
�����
�����
�� �� �� ��������������
������������������������������������ ����������
����
����
����� ���������������
�����
�����
�� �� �� ��������������
�������
115