Eye tracking and early detection of confusion in digital learning environments: Proof of concept

Pachman, M; Arguel, A; Lockyer, L; Kennedy, G; Lodge, JM

Eye tracking and early detection of confusion in digital learning environments: Proof of concept

Pachman, M Arguel, A Lockyer, L

Kennedy, G Lodge, JM

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Publication Type:: Journal Article
Citation:: Australasian Journal of Educational Technology, 2016, 32 (6), pp. 58 - 71
Issue Date:: 2016-01-01

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Field	Value	Language
dc.contributor.author	Pachman, M	en_US
dc.contributor.author	Arguel, A	en_US
dc.contributor.author	Lockyer, L https://orcid.org/0000-0003-1517-2342	en_US
dc.contributor.author	Kennedy, G	en_US
dc.contributor.author	Lodge, JM	en_US
dc.date.issued	2016-01-01	en_US
dc.identifier.citation	Australasian Journal of Educational Technology, 2016, 32 (6), pp. 58 - 71	en_US
dc.identifier.uri	http://hdl.handle.net/10453/122128
dc.description.abstract	© Australasian Journal of Educational Technology 2016. Research on incidence of and changes in confusion during complex learning and problem-solving calls for advanced methods of confusion detection in digital learning environments (DLEs). In this study we attempt to address this issue by investigating the use of multiple measures, including psychophysiological indicators and self-ratings, to detect confusion in DLEs. Participants were subjected to two intrinsically confusing insight problems in the form of visual digital puzzles. They were asked to solve problems while their eye trajectories were recorded and these data were triangulated with self-ratings of confusion and cued retrospective verbal reports. All participants had a significant increase in fixations on relevant (i.e., related to the solution) and not-relevant areas at an early stage of the problem-solving process. However, only fixations on not-relevant areas were positively correlated with confusion ratings. Moreover, participants who significantly solved the problem differed in their fixations duration on relevant and not-relevant areas from non-solvers. The importance of early detection of confusion and the affordances of emerging technologies for this purpose are discussed.	en_US
dc.relation.ispartof	Australasian Journal of Educational Technology	en_US
dc.relation.isbasedon	10.14742/ajet.3060	en_US
dc.subject.classification	Education	en_US
dc.title	Eye tracking and early detection of confusion in digital learning environments: Proof of concept	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	32	en_US
utslib.for	1303 Specialist Studies in Education	en_US
utslib.for	1302 Curriculum and Pedagogy	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Graduate Research School
pubs.organisational-group	/University of Technology Sydney/Strength - STEM Education Futures
utslib.copyright.status	open_access
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	32	en_US

Abstract:

© Australasian Journal of Educational Technology 2016. Research on incidence of and changes in confusion during complex learning and problem-solving calls for advanced methods of confusion detection in digital learning environments (DLEs). In this study we attempt to address this issue by investigating the use of multiple measures, including psychophysiological indicators and self-ratings, to detect confusion in DLEs. Participants were subjected to two intrinsically confusing insight problems in the form of visual digital puzzles. They were asked to solve problems while their eye trajectories were recorded and these data were triangulated with self-ratings of confusion and cued retrospective verbal reports. All participants had a significant increase in fixations on relevant (i.e., related to the solution) and not-relevant areas at an early stage of the problem-solving process. However, only fixations on not-relevant areas were positively correlated with confusion ratings. Moreover, participants who significantly solved the problem differed in their fixations duration on relevant and not-relevant areas from non-solvers. The importance of early detection of confusion and the affordances of emerging technologies for this purpose are discussed.

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http://hdl.handle.net/10453/122128