Predicting learner confusion for enhanced feedback and self-regulation
About
This project investigated learner cognition and emotion, with a view to creating real-time feedback for students as they work through activities in digital learning environments (DLEs). One particular focus of the investigations was learner confusion. A state of disequilibrium or confusion is often a necessary pre-condition for lasting conceptual change. The researchers examined confusion and the process of conceptual change at a physiological, cognitive and educational level. The research methods included neuroimaging, electroencephalograms, eye tracking, data mining and randomised control trials.
Aim
The researchers were particularly interested in combining the rigour afforded by experimental laboratory studies with the insights gleaned through the use of data mining and predictive modelling to assist students to reach a state of meaningful and lasting conceptual change.
Funding
This project was run between 2014-2017 and funded by the Australian Research Council / Science of Learning Research Centre
Researchers
- Professor Gregor Kennedy
- Associate Professor Jason Lodge
- Paula de Barba (PhD Candidate)
- Sadia Nawaz (PhD Candidate)
- Paul Wiseman (PhD Candidate)
Outcomes
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Journal articles
Arguel, A., Lockyer, L., Kennedy, G., Lodge, J. M., & Pachman, M. (2018). Seeking optimal confusion: a review on epistemic emotion management in interactive digital learning environments. Interactive Learning Environments, 1-11. https://www-tandfonline-com.ezp.lib.unimelb.edu.au/doi/abs/10.1080/10494820.2018.1457544
Arguel, A., Lockyer, L., Lipp, O. V., Lodge, J. M., & Kennedy, G. (2017). Inside out: detecting learners’ confusion to improve interactive digital learning environments. Journal of Educational Computing Research, 55(4), 526-551. https://doi-org.ezp.lib.unimelb.edu.au/10.1177/0735633116674732
De Barba, P., Kennedy, G. E., & Ainley, M. D. (2016). The role of students' motivation and participation in predicting performance in a MOOC. Journal of Computer Assisted Learning, 32(3), 218-231.https://doi-org.ezp.lib.unimelb.edu.au/10.1111/jcal.12130
Lodge, J. M., Kennedy, G., Lockyer, L., Arguel, A., & Pachman, M. (2018). Understanding difficulties and resulting confusion in learning: An integrative review. In Frontiers in Education (Vol. 3, p. 49). Frontiers. https://doi.org/10.3389/feduc.2018.00049
Lodge, J. M. (2016). Do the learning sciences have a place in higher education research? Higher Education Research & Development, 35 (3), 634-637. http://dx.doi.org/10.1080/07294360.2015.1094204
Lodge, J. M., Cottrell, D., & Hansen, L. Learning styles at the crossroads of the laboratory and the classroom. Learning: Research and Practice. http://dx.doi.org/10.1080/23735082.2017.1285630
Lodge, J. M., Kennedy, G. & Lockyer, L. (2016). Editorial: Brain, mind and educational technology. Australasian Journal of Educational Technology, 32 (6), i-iii. http://dx.doi.org/10.14742/ajet.3443Pachman, M., Arguel, A., Lockyer, L. & Kennedy, G., & Lodge, J. M. (2016). Eye tracking and early detection of confusion in digital learning environments: Proof of concept. Australasian Journal of Educational Technology, 32(6), 58 71. http://dx.doi.org/10.14742/ajet.3060
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Conference papers
Arguel, A., Lodge, J. M., Pachman, M., & de Barba, P. (2016). Confidence drives exploration strategies in interactive simulations. In Proceedings of the 2016 ASCILITE annual conference – Australian Society for Computers in Learning in Tertiary Education, 33-42. https://minerva-access.unimelb.edu.au/handle/11343/121991
de Barba, P., Kennedy, G., & Trezise, K. (2018). Procedural and conceptual confusion in a discovery-based digital learning environment. In Proceedings of the 2018 ASCILITE annual conference – Australian Society for Computers in Learning in Tertiary Education, 340-345. http://2018conference.ascilite.org/wp-content/uploads/2018/12/ASCILITE-2018-Proceedings-Final.pdf
Kennedy, G., & Lodge, J. (2016). All roads lead to Rome: Tracking students’ affect as they overcome misconceptions. In Proceedings of the 2016 ASCILITE annual conference – Australian Society for Computers in Learning in Tertiary Education, 318-328. http://2016conference.ascilite.org/wp-content/uploads/ascilite2016_kennedy_full.pdf
Lodge, J. M. & Kennedy, G. (2015). Prior knowledge, confidence and understanding in interactive tutorials and simulations. In Proceedings of the 2015 ASCILITE annual conference – Australian Society for Computers in Learning in Tertiary Education,, 178-188.
Wiseman, P., Lodge, J. M., Arguel, A., & Kennedy, G. (2017). The changing nature of student engagement during a digital learning task. In Proceedings of the 2017 ASCILITE annual conference – Australian Society for Computers in Learning in Tertiary Education, 433-440. http://2017conference.ascilite.org/wp-content/uploads/2017/11/Full-WISEMAN.pdf
Wiseman, P. J., Kennedy, G. E., & Lodge, J. M. (2016) Models for understanding student engagement in digital learning environments. In Proceedings of the 2016 ASCILITE annual conference – Australian Society for Computers in Learning in Tertiary Education, 666-671. http://2016conference.ascilite.org/wp-content/uploads/ascilite2016_wiseman_concise.pdf
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Book chapters
Broadbent, J., Panadero, E., Lodge, J.M., de Barba, P. (2019). Technologies to enhance self-regulated learning in online learning environments. Handbook of Research on Educational Communications and Technology. Springer.
Lodge, J.M, Panadero, E., Broadbent, J., de Barba, P. (2018). Supporting self-regulated learning with learning analytics. In J.M. Lodge, J.C. Horvath L. Corrin (eds.), Learning Analytics in the Classroom: Translating Learning Analytics Research for Teachers. Routledge.
Lodge, J. M., Kennedy, G., & Hattie, J. (2018). Understanding, assessing and enhancing student evaluative judgement in digital environments. In Developing Evaluative Judgement in Higher Education (pp. 86-94). Routledge.
More information
Dr Paula De Barba, Melbourne CSHE, The University of Melbourne