DOCSLIB.ORG

A Bibliometric Study on Learning Analytics Bertha Adeniji

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Bibliometric Study on Learning Analytics Bertha Adeniji Long Island University Digital Commons @ LIU Selected Full Text Dissertations, 2011- LIU Post 2019 A Bibliometric Study on Learning Analytics Bertha Adeniji Follow this and additional works at: https://digitalcommons.liu.edu/post_fultext_dis A Bibliometric Study on Learning Analytics A Dissertation Submitted to the Faculty of The Palmer School of Library and Information Science at Long Island University by Bertha (Abby) Adeniji Advisor: Professor Qiping Zhang May 3, 2019 i Table of Contents List of Figures .................................................................................................................... iv List of Tables ..................................................................................................................... v Dedication ................................................................................................................... vii Acknowledgment ............................................................................................................. viii Abstract .................................................................................................................... ix Chapter 1: Introduction ..................................................................................................... 10 1.1 Theoretical Positioning of Learning Analytics (LA) .......................................... 10 1.2 Motivation and Objective ............................................................................................ 12 1.3 Significance ....................................................................................................................... 13 Chapter 2: Literature Review ............................................................................................ 14 2.1 Bibliometric Analysis .................................................................................................... 14 2.1.1 Bibliometric Laws .................................................................................. 14 2.1.2 Citation Analysis .................................................................................... 16 2.1.3 Co-occurrence Analysis (co-word, co-co citation) ................................ 18 2.2 Keyword Analysis ........................................................................................................... 19 2.2.1 Multi-Dimensional Scaling (MDS)........................................................ 19 2.2.2 Bibliometric Mapping ............................................................................ 20 2.3 Domain Analysis ............................................................................................................. 20 2.3.1 Definition of Domain Analysis .............................................................. 20 2.3.2 Techniques of Domain Analysis ............................................................ 21 2.3.3 Application of Domain Analysis to Different Disciplines ..................... 24 2.4 Conceptual Framework of Learning Analytics .................................................... 26 2.4.1 Data Collection Techniques of Learning Analytics ............................... 28 2.4.2 Data Analysis of Learning Analytics ..................................................... 30 2.4.3 Data Reporting of Learning Analytics ................................................... 31 2.5 Current Research on Learning Analytic................................................................. 32 2.5.1 Three Periods of Research on Learning Analytics ................................ 32 2.5.2 Research Factors in Learning Analytics ................................................ 33 2.5.3 Stakeholders of Research on Learning Analytics .................................. 36 Chapter 3: Research Questions ......................................................................................... 39 3.1 Statement of Research Problem ............................................................................... 39 3.2 Research Questions ....................................................................................................... 39 3.3 Concepts and Definitions............................................................................................. 40 Chapter 4: Methods ........................................................................................................... 43 4.1 Choice of Databases ....................................................................................................... 43 4.2 Search Query .................................................................................................................... 44 4.3 Dataset ................................................................................................................................ 44 4.4 Data Collection Procedures ........................................................................................ 44 4.5 Domain Analysis ............................................................................................................. 46 4.6 Validity and Reliability ................................................................................................. 47 ii Chapter 5: Results ............................................................................................................. 48 5.1 Results for RQ 1: What are the bibliometric features of research on LA? 48 5.1.1 Publication Counts Over Time............................................................... 48 5.1.2 Key Publication Types on Learning Analytics ...................................... 49 5.1.3 Key Publication Sources on LA ............................................................. 53 5.1.4 Key Authors and Affiliations by Three Periods .................................... 54 5.1.5 Key Subject Area by Three Periods ....................................................... 60 5.2 Results for RQ 2: What are the evolutions of research themes on LA? ..... 62 5.2.1 Results of Author Keyword Trend ......................................................... 62 5.2.2 Results of Keyword Trend-Period 1 (2004-2011) ................................. 69 5.2.3 Results of Keyword Trend-Period 2 (2012-2013) .................................. 70 5.2.4 Results of Keyword Trend-Period 3 (2014-2018) ................................. 71 5.3 Results for RQ 3: What are the domain features of research on LA? ......... 72 5.3.1 Taxonomy of Learning Analytics Research .......................................... 73 5.3.2 Results of Co-citation Analysis ............................................................. 74 5.3.3 Results of Co-author Analysis ............................................................... 76 5.3.4 Results of Coupling Analysis ................................................................ 80 Chapter 6: Discussion ....................................................................................................... 82 6.1 Bibliometric Profile and Trends of Learning Analytics ................................... 82 6.2 Domain Analysis ............................................................................................................. 84 6.3 Implications of This Study .......................................................................................... 85 6.4 Limitations ........................................................................................................................ 94 6.5 Recommendations for Future Research ................................................................ 95 6.6 Conclusions ....................................................................................................................... 96 Bibliography 97 Appendix A: Comparison of Five Academic Databases .............................................. 106 Appendix B: Top 100 Author Keywords by Alphabetical Order................................. 108 Appendix C: Top 100 Author Keywords by Frequency .............................................. 117 Appendix D: Frequency of Author Keywords by Three Periods ................................. 120 Appendix E: Comparison of Top Author Keywords for Three Periods ...................... 127 iii List of Figures Figure 1: Triadic - Epistemology - Pedagogy - Assessment (Knight, 2014) .................... 11 Figure 2: Traditional Hierarchy of Evidence (Grant, 2016) ............................................. 11 Figure 3: Arango and Prieto-Diaz Model of Domain Analysis ........................................ 24 Figure 4: Mapping LA and AA in Big Data Context (Prinsloo, 2015)............................. 27 Figure 5: Inclusion and Exclusion Process for LA Publications (2011-2018) ................. 45 Figure 6: Learning Analytics Publications by Year and Period ....................................... 49 Figure 7: Learning Analytics Affiliation by County - ALL ............................................. 57 Figure 8: Learning Analytics Affiliation by Institution ALL ........................................... 58 Figure 9: Learning Analytics Key Subject Areas – Period 1 ............................................ 60 Figure 10: Learning Analytics Key Subject Areas – Period 2 .......................................... 61 Figure 11: Learning Analytics Key Subject Areas – Period 3 .......................................... 62 Figure 12: Cluster Map of Author Keywords (VOSviewer) ............................................ 65 Figure 13: Learning Analytics -100 Keywords (2004-2018) ........................................... 69 Figure 14: Treemap – Learning Analytics 100 Keywords (2004-2011) –
Load more

Recommended publications
  • A Summary of Literature Pertaining to the Use of Concept Mapping Techniques and Technologies for Education and Performance Support
    A Summary of Literature Pertaining to the Use of Concept Mapping Techniques and Technologies for Education and Performance Support The Institute for Human and Machine Cognition 40 S. Alcaniz St. Pensacola FL 32502 www.ihmc.us prepared for The Chief of Naval Education and Training Pensacola FL 32500 July 2003 Principal Investigator: Alberto J. Cañas Research Team: John. W. Coffey Mary Jo Carnot Paul Feltovich Robert R. Hoffman Joan Feltovich Joseph D. Novak Table of Contents List of Figures 1. Executive Summary 1.1. Background and Theory Pertaining to Concept Maps 1.2. Educational, Business, and Governmental Uses of Concept Mapping 1.3. Limits on Our Ability to Report 1.4. Major Conclusions of this Report 2. Construction Methods and Styles for Concept Maps 2.1 Distinguishing Characteristics of Concept Maps 2.2 An Example Concept Map 2.3 A Basic Concept Map Construction Method 2.4. Variations on the Basic Method 2.5 Collaboration in the Construction of Concept Maps. 2.6 Facilitation in Map Construction: Human Facilitators and Computer Support 3. Applications in Educational Settings 3.1 Uses of Concept Maps as a Tool for Support of Learning 3.1.1 Identifying current understanding, misconceptions, conceptual change 3.1.2 Collaboration and Cooperative Learning 3.2 Assessment of Learning Using Concept Maps 3.2.1 The Utility of Using Concept Maps for Assessment 3.2.2. Methods of Scoring Concept Maps 3.2.3 Reliability and Validity of Concept Maps for Assessment 3.3 Uses of Concept Maps to Organize and Present Information 3.3.1 Concept Maps as
    [Show full text]
  • Concept Mapping As a Tool for Enhancing Self-Paced Learning in a Distance Scenario
    Walden University ScholarWorks Walden Dissertations and Doctoral Studies Walden Dissertations and Doctoral Studies Collection 2015 Concept Mapping as a Tool for Enhancing Self- Paced Learning in a Distance Scenario John Allen Richbourg Walden University Follow this and additional works at: https://scholarworks.waldenu.edu/dissertations Part of the Chemistry Commons, Elementary and Middle and Secondary Education Administration Commons, Instructional Media Design Commons, and the Secondary Education and Teaching Commons This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been accepted for inclusion in Walden Dissertations and Doctoral Studies by an authorized administrator of ScholarWorks. For more information, please contact [email protected]. Walden University College of Education This is to certify that the doctoral dissertation by John Richbourg has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Leslie Moller, Committee Chairperson, Education Faculty Dr. Wellesley Foshay, Committee Member, Education Faculty Dr. Christina Dawson, University Reviewer, Education Faculty Chief Academic Officer Eric Riedel, Ph.D. Walden University 2015 Concept Mapping as a Tool for Enhancing Self-Paced Learning in a Distance Scenario by John A. Richbourg, Jr. MA, University of Texas at San Antonio, 1991 BS, The Citadel, Charleston, SC, 1974 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Educational Technology Walden University May 2015 Abstract Researchers have determined that concept maps serve as effective tools in the traditional science classroom.
    [Show full text]
  • Synthesis: What We've Learned
    9 SYNTHESIS: WHAT distribute WE’VE LEARNED or n this chapter, we consider the exemplars described in Chapters 5 through 8, reflecting Ion their commonalities and the unique elements that each narrative presents. The con- versations offer insight into the thinking of the researchers as they consider design and implementation decisions related to group concept mapping (GCM).post, We link our obser- vations about the application of GCM in the examples with principles and characteristics that are central to GCM, as noted in the foundational literature (Kane & Trochim, 2007, Trochim, 1989). They are participation, utilization, and representation; and as an over- arching framework, integrated mixed methodology. Through the lens of mixed-methods methodology, we position the GCM approachcopy, in the larger context, highlighting the features of mixed methods that are standard in GCM. There are reasons why researchers choose this method, and understanding their rea- soning helps to ensure a strong alignment of the intent, the design, and the outcome of research using concept mapping. Innot the following sections, we explore each theme from the perspective of our conversation with the guest researchers and as it’s represented in the social science literature, illuminating the place of the GCM methodology in social science research and action.Do - PARTICIPATION Participation, or valuing the voices of those with knowledge, opinions, and experience, is a theme throughout the conversations, and indeed through the entire volume. Through conscientiousProof participation planning, we access communities of interest and create group wisdom that will lead to understanding and informed action. Kane and Trochim (2007) accentuate the collaborative group processes as fundamental to the approach, and describe the method as a participatory approach for stimulating learning and action among a group of individuals.
    [Show full text]
  • Mind Maps and Network Analysis to Evaluate Conceptualization of Complex T Issues: a Case Example Evaluating Systems Science Workshops for Childhood Obesity Prevention
    Mind maps and network analysis to evaluate conceptualization of complex T issues: A case example evaluating systems science workshops for childhood obesity prevention ⁎ Leah Frerichsa, ,Tiffany L. Younga, Gaurav Davea, Doris Stithb, Giselle Corbie-Smitha, Kristen Hassmiller Licha a University of North Carolina at Chapel Hill, NC, United States b Community Enrichment Organization, Tarboro, NC, United States ARTICLE INFO ABSTRACT Keywords: Across disciplines, it is common practice to bring together groups to solve complex problems. Facilitators are Concept mapping often asked to help groups organize information about and better understand the problem in order to develop Mental models and prioritize solutions. However, despite existence of several methods to elicit and characterize how individuals Network analysis and groups think about and conceptualize an issue, many are difficult to implement in practice-based settings Systems science where resources such as technology and participant time are limited and research questions shift over time. This paper describes an easy-to-implement diagramming technique for eliciting conceptualization and a flexible network analysis method for characterizing changes in both individual and group conceptualization. We use a case example to illustrate how we used the methods to evaluate African American adolescent’s conceptual un- derstanding of obesity before and after participating in a series of four systems thinking workshops. The methods produced results that were sensitive to changes in conceptualization that were likely driven by the specific activities employed during the workshop sessions. The methods appear strong for capturing salient levels of conceptualization at both individual and collective levels. The paper concludes with a critical examination of strengths and weaknesses of the methods and implications for future practice and research.
    [Show full text]
  • A Summary of Literature Pertaining to the Use of Concept Mapping Techniques and Technologies for Education and Performance Support
    A Summary of Literature Pertaining to the Use of Concept Mapping Techniques and Technologies for Education and Performance Support The Institute for Human and Machine Cognition 40 S. Alcaniz St. Pensacola FL 32502 www.ihmc.us prepared for The Chief of Naval Education and Training Pensacola FL 32500 July 2003 Principal Investigator: Alberto J. Cañas Research Team: John. W. Coffey Mary Jo Carnot Paul Feltovich Robert R. Hoffman Joan Feltovich Joseph D. Novak Table of Contents List of Figures 1. Executive Summary 1.1. Background and Theory Pertaining to Concept Maps 1.2. Educational, Business, and Governmental Uses of Concept Mapping 1.3. Limits on Our Ability to Report 1.4. Major Conclusions of this Report 2. Construction Methods and Styles for Concept Maps 2.1 Distinguishing Characteristics of Concept Maps 2.2 An Example Concept Map 2.3 A Basic Concept Map Construction Method 2.4. Variations on the Basic Method 2.5 Collaboration in the Construction of Concept Maps. 2.6 Facilitation in Map Construction: Human Facilitators and Computer Support 3. Applications in Educational Settings 3.1 Uses of Concept Maps as a Tool for Support of Learning 3.1.1 Identifying current understanding, misconceptions, conceptual change 3.1.2 Collaboration and Cooperative Learning 3.2 Assessment of Learning Using Concept Maps 3.2.1 The Utility of Using Concept Maps for Assessment 3.2.2. Methods of Scoring Concept Maps 3.2.3 Reliability and Validity of Concept Maps for Assessment 3.3 Uses of Concept Maps to Organize and Present Information 3.3.1 Concept Maps as
    [Show full text]