Technology Enhanced Learning Analytics Dashboard in Higher Education
DOI:
https://doi.org/10.34190/ejel.20.2.2189Keywords:
Learning Analytics, Information Visualization, Higher Education, Online Learning, Moodle PluginAbstract
During the COVID-19 pandemic period, all the Sri Lankan universities delivered lectures in fully online mode using Virtual Learning Environments. In fully online mode, students cannot track their performance level, their progress in the course, and their performances compared to the rest of the class. This paper presents research work conducted at the University of Colombo School of Computing (UCSC), Sri Lanka, to solve the above problems and facilitate students learning in fully online and blended learning environments using Learning Analytics. The research objective is to design and create a Technology Enhanced Learning Analytics (TELA) dashboard for improving students’ motivation, engagement, and grades. The Design Science research strategy was followed to achieve the objectives of the research. Initially, a literature survey was conducted analyzing features and limitations in current Learning Analytic dashboards. Then, current Learning Analytic plugins for Moodle were studied to identify their drawbacks. Two surveys with 136 undergraduate students and interviews with 12 lecturers were conducted to determine required features of the TELA system. The system was designed as a Moodle Plugin. Finally, an evaluation of the system was done with third-year undergraduate students of the UCSC. The results showed that the TELA dashboard can improve students' motivation, engagement, and grades. As a result of the system, students could track their current progress and performance compared to the peers, which helps to improve their motivation to engage more in the course. Also, the increased engagement in the course enhances the student’s self-confidence since the student can see continuous improvement of his/her progress and performance which in turn improves the student’s grades.
References
Arnold, K. E., and Pistilli, M. D.: “Course Signals at Purdue: Using Learning Analytics to Increase Student Success,” in In Proceedings of the 2nd international conference on learning analytics and knowledge (2012).
Benson, L., Elliott, D., Grant, M., Holschuh, D., Kim, B., Kim, H., et al.: Usability and Instructional Design Heuristics for E-Learning Evaluation. In Proceedings of World Conference on Educational Multimedia, Hypermedia & Telecommunications (ED-MEDIA 2002), p. 1615 – 1621 (2002).
Bugnet, E., Dvorovenko, V.: Statistics (Graph Stats) [Online]. Available at: https://moodle.org/plugins/block_graph_stats (Accessed: 24 January 2021).
Charleer, S., Moere, A. V., Klerkx J., Verbert, K. and Laet, T.: “Learning Analytics Dashboards to Support Adviser-Student Dialogue,” IEEE Transactions on Learning Technologies, pp. 389-399 (2018).
Chan, A., Forum Graph [Online]. Available at: https://moodle.org/plugins/report_forumgraph (Accessed: 24 January 2021).
Chatti M.A., Dyckhoff A.L., Schroeder U., Thüs H.: “A reference model for learning analytics, International Journal of Technology Enhanced Learning,” 4 (5), pp. 318--331 (2012).
First International Conference on Learning Analytics and Knowledge 2011 (LAK 2011) [Online]. Available at: https://tekri.athabascau.ca/analytics/about (Accessed: 24 March 2021).
Ferguson R.: Learning analytics: drivers, developments and challenges, International Journal of Technology Enhanced Learning, 4(5-6), pp. 304--317 (2012).
Frechtling, J., & Sharp, L.: User-Friendly Handbook for Mixed Method Evaluations. Directorate for Education and Human Resources Division of Research, Evaluation and Communication NSF., 97 – 153 (1997).
Fuente-Valent__n, L. De-la, Pardo, A., & Delgado Kloos, C.:Addressing Drop-out and Sustained E_ort Issues with Large Practical Groups using an Automated Delivery and Assessment System. Computers & Education, 61 , 33- 42. Retrieved from http://linkinghub.elsevier.com/retrieve/pii/S0360131512002084 (2013).
Goodwin, K.: Designing for the Digital Age: How to Create Human-Centered Products and Services. Wiley Publishing, Inc. (2009).
Graf, S., Ives, C., Rahman, N., and Ferri, A.: “AAT – A Tool for Accessing and Analysing Students’ Behaviour Data in Learning Systems,” in In Proceedings of the 1st international conference on learning analytics and knowledge (2011).
Ifenthaler, D., Widanapathirana, C., “Development and Validation of a Learning Analytics Framework: Two Case Studies Using Support Vector Machines,” Technology Knowledge and Learning, pp. 221-240 (2014).
Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z., and Wolff, A.: “OU Analyse: analysing at-risk students at The Open University,” in Learning Analytics and Knowledge conference (2015).
Lazar, J., Feng, J. H., & Hochheiser, H.: Research Methods in Human-Computer Interaction. Wiley Publishing, Inc. (2010).
Nielsen, J.: 10 Usability Heuristics for User Interface Design. Jakob Nielsen's Alertbox. Retrieved from http://www.nngroup.com/articles/ten-usability-heuristics/ (1995)
Oates, B.: Researching Information Systems and Computing. SAGE publications Ltd. (2006).
Raadt, M., Progress Bar [Online]. Available at: https://moodle.org/plugins/block_progress (Accessed: 24 January 2021)
Raadt, M., Heatmap [Online]. Available at: https://moodle.org/plugins/block_heatmap (Accessed: 24 January 2021)
Saltuk, O., Kosan, I., Design and Creation [Online].Available at: https://www.medien.ifi.lmu.de/lehre/ss14/swal/presentations/topic2-saltuk_kosan-DesignAndCreation.pdf (Accessed: 24 January 2021)
Schmitt, M., Analytics graphs [Online]. Available at: https://moodle.org/plugins/block_analytics_graphs (Accessed: 24 January 2021)
Shum, S., Ferguson R.: Social learning analytics, Educational Technology & Society, 15 (3), pp. 3—26 (2012).
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