Students’ sense-making of personalised feedback based on learning analytics

Authors

DOI:

https://doi.org/10.14742/ajet.6370

Keywords:

learning analytics, feedback, self-regulated learning, student perspectives, epistemic network analysis

Abstract

Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students’ sense-making of learning analytics–based personalised feedback across four courses. Results from a combination of thematic analysis and epistemic network analysis show an association between student perceptions of their personalised feedback and how these map to subsequent self-described self-regulated learning processes. Most notably, the results indicate that personalised feedback, elaborated by personal messages from course instructors, helps students refine or strengthen important forethought processes of goal-setting, as well as to reduce procrastination. The results highlight the need for instructors to increase the dialogic element in personalised feedback in order to reduce defensive reactions from students who hold to their own learning strategies. This approach may prompt reflection on the suitability of students’ current learning strategies and achievement of associated learning goals.

Implications for practice or policy:

  • Personalised feedback based on learning analytics should be informed by an understanding of students’ self-regulated learning.
  • Instructors implementing personalised feedback should align this closely with the course curriculum.
  • Instructors implementing personalised feedback in their courses should consider the relational element of feedback by using a positive tone.
  • Personalised feedback can be further enhanced by increasing the dialogic element and by including more information about learning strategies.

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Author Biographies

Lisa-Angelique Lim, University of South Australia

Lisa-Angelique Lim is a PhD candidate with Education Futures at the University of South Australia. Lisa’s research lies at the intersection of learning analytics and student learning. Of particular interest is the impact of student-facing learning analytics reporting systems on students’ self-regulated learning processes and academic performance. Lisa is especially interested in how students interact with these socio-technical systems, to make decisions about their learning.  Having had extensive experience as an academic developer, Lisa enjoys working closely with academic staff at the University to identify effective ways to implement learning analytics-based systems in their own teaching contexts.

Shane Dawson, University of South Australia

Professor Shane Dawson is the Executive Dean of Education Futures and Co-Director of the Centre for Change and Complexity in Learning (C3L) at the University of South Australia. Shane's research focuses on the application of learning analytics to inform student outcomes, personalisation, learning design, and benchmark teaching and learning quality. He has published widely on topics from creative capacity to social network analysis and more recently, on the application of complexity models in learning analytics. His current research interests relate to complex systems and academic leadership to aid adoption and application of learning analytics at scale. 

Dragan Gašević, Monash University

Dragan Gašević is Professor of Learning Analytics in the Faculty of Information Technology at Monash University and Professor of Learning Analytics (part-time) at the School of Informatics at the University of Edinburgh. Dragan’s research involves developing computational methods that can shape next-generation learning technologies and advance our understanding of information seeking, sense-making, and self-regulated and collaborative learning. Dragan is a (co-)author of numerous research papers and books and a frequent keynote speaker.

Srećko Joksimović, University of South Australia

Dr Srecko Joksimovic is a Research Fellow (Data Scientist) with Education Futures at the University of South Australia. Srecko’s research interest lies in evaluating the influence of contextual, social, cognitive, and affective factors on groups and individuals as they solve complex real-world problems. In so doing, he utilizes a wide range of methods from machine learning, artificial intelligence, and natural language processing, as well as data science and social computing in general. Srecko has a strong publication record in top journal and conference venues in the fields of learning analytics, educational data mining, and learning technologies. He has been actively involved in the development of the learning analytics research field.

Anthea Fudge, University of South Australia

Dr Anthea Fudge is an educator in the sciences and enabling education, with Education Futures at the University of South Australia. Anthea’s research lies in the use of digital tools and learning analytics to assist with supporting feedback, development of educative academic integrity practices and research into creative ways to support students in widening participation in higher education. In 2018 Anthea received a UniSA Citation for Outstanding Contributions to Student Learning, for the development of supportive resources to enhance student learning of academic integrity (AI) which has influenced a significant reduction of AI cases at UniSA College. This work was awarded a 2019 Australian Award for University Teaching. Anthea currently serves on the Executive board of the National Association of Enabling Educators of Australia 2018 - 2020.

Abelardo Pardo, University of South Australia

Abelardo Pardo is Professor and Dean of Programs (Engineering) at STEM at the University of South Australia. His research interests include the design and deployment of technology to increase the understanding and improve digital learning experiences. More specifically, his work examines the areas of learning analytics, personalized active learning, and technology for student support. Abelardo is the author of over 150 research papers in scholarly journals and international conferences in the area of educational technology and engineering education. He is currently member of the executive board and president of the Society for Learning Analytics Research (SoLAR).

Sheridan Gentili, University of South Australia

Associate Professor Sheridan Gentili is the Director of the Teaching Innovation Unit at the University of South Australia. Sheridan’s research interest lies in exploring how learning analytics can be used to improve the student experience and academic performance. Sheridan is also interested in exploring the impact that personalised feedback, using real-time data of online learning behaviour, can foster academic success. Specifically, her work focusses on exploring the learning and teaching experiences, and behaviours that encourage high achieving students and those of average achieving students, with an aim to better inform teaching practices at all academic levels.

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Published

2020-12-23

How to Cite

Lim, L.-A., Dawson, S., Gašević, D., Joksimović, S. ., Fudge, A., Pardo, A., & Gentili, S. (2020). Students’ sense-making of personalised feedback based on learning analytics. Australasian Journal of Educational Technology, 36(6), 15–33. https://doi.org/10.14742/ajet.6370

Issue

Vol. 36 No. 6 (2020): AJET Special Issue: Learning Analytics: Pathways to Impact

Section

Special Issue 2020 Learning Analytics: Pathways to Impact

License

Articles published in the Australasian Journal of Educational Technology (AJET) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant AJET right of first publication under CC BY-NC-ND 4.0.

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