Trends and issues in student-facing learning analytics reporting systems research

We conducted a literature review on systems that track learning analytics data (e.g., resource use, time spent, assessment data, etc.) and provide a report back to students in the form of visualizations, feedback, or recommendations. This review included a rigorous article search process; 945 articles were identified in the initial search. After filtering out articles that did not meet the inclusion criteria, 94 articles were included in the final analysis. Articles were coded on five categories chosen based on previous work done in this area: functionality, data sources, design analysis, perceived effects, and actual effects. The purpose of this review is to identify trends in the current student-facing learning analytics reporting system literature and provide recommendations for learning analytics researchers and practitioners for future work.

[1]  Wu-Yuin Hwang,et al.  A Markov-based Recommendation Model for Exploring the Transfer of Learning on the Web , 2009, J. Educ. Technol. Soc..

[2]  Erik Duval,et al.  Learning Analytics Dashboard Applications , 2013 .

[3]  Anthony V. Robins,et al.  Illustrating performance indicators and course characteristics to support students’ self-regulated learning in CS1 , 2015, Comput. Sci. Educ..

[4]  Sebastián Ventura,et al.  Educational Data Mining: A Review of the State of the Art , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[5]  Paul S. Steif,et al.  Web-based Statics Course with Learning Dashboard for Instructors , 2012 .

[6]  References , 1971 .

[7]  Simon Buckingham Shum,et al.  Socially augmented argumentation tools: Rationale, design and evaluation of a debate dashboard , 2014, Int. J. Hum. Comput. Stud..

[8]  Feng-Hsu Wang,et al.  Content Recommendation Based on Education-Contextualized Browsing Events for Web-based Personalized Learning , 2008, J. Educ. Technol. Soc..

[9]  Yeonjeong Park,et al.  Development of the Learning Analytics Dashboard to Support Students' Learning Performance , 2015, J. Univers. Comput. Sci..

[10]  Matthew D. Pistilli,et al.  Course signals at Purdue: using learning analytics to increase student success , 2012, LAK.

[11]  Olga C. Santos,et al.  Extending web-based educational systems with personalised support through User Centred Designed recommendations along the e-learning life cycle , 2014, Sci. Comput. Program..

[12]  S. Kuhar,et al.  Taking Advantage of Education Data: Advanced Data Analysis and Reporting in Virtual Learning Environments , 2011 .

[13]  Kenneth R. Koedinger,et al.  Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work , 2007 .

[14]  María Jesús Rodríguez-Triana,et al.  Understanding learning at a glance: an overview of learning dashboard studies , 2016, LAK.

[15]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[16]  Colin Tattersall,et al.  Self-organising navigational support in lifelong learning: How predecessors can lead the way , 2007, Comput. Educ..

[17]  Zoran Budimac,et al.  Applying Recommender Systems and Adaptive Hypermedia for e-Learning Personalizatio , 2013, Comput. Informatics.

[18]  E. Deci,et al.  Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. , 2000, The American psychologist.

[19]  Claus Zinn,et al.  How did the e-learning session go? The Student Inspector , 2007, AIED.

[20]  Yeonjeong Park,et al.  Educational Dashboards for Smart Learning: Review of Case Studies , 2014, ICSLE.

[21]  Tristan Denley,et al.  How Predictive Analytics and Choice Architecture Can Improve Student Success. , 2014 .

[22]  Tanya Elias,et al.  Learning Analytics: Definitions, Processes and Potential , 2011 .

[23]  I. E. Allen,et al.  Grade Level: Tracking Online Education in the United States. , 2015 .

[24]  Jacqueline L. Feild Improving Student Performance Using Nudge Analytics , 2015, EDM.

[25]  Katrien Verbert,et al.  Panorama of Recommender Systems to Support Learning , 2015, Recommender Systems Handbook.

[26]  Christian Saul,et al.  Turning Learners into Effective Better Learners: The Use of the askMe! System for Learning Analytics , 2014, UMAP Workshops.

[27]  G. D. Chen,et al.  Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques , 2008, Comput. Educ..

[28]  Jeff Grann,et al.  Competency map: visualizing student learning to promote student success , 2014, LAK.

[29]  Bernie Dodge,et al.  Improving undergraduate student achievement in large blended courses through data-driven interventions , 2015, LAK.

[30]  James W. Altschuld,et al.  Needs Assessment: An Overview , 2010 .

[31]  Il-Hyun Jo,et al.  Effects of learning analytics dashboard: analyzing the relations among dashboard utilization, satisfaction, and learning achievement , 2015, Asia Pacific Education Review.

[32]  Erik Duval,et al.  Learning dashboards: an overview and future research opportunities , 2013, Personal and Ubiquitous Computing.

[33]  Marek Hatala,et al.  The role of achievement goal orientations when studying effect of learning analytics visualizations , 2016, LAK.