Improving Teaching and Learning in Higher Education through Machine Learning: Proof of Concept’ of AI’s Ability to Assess the Use of Key Microskills

Dann, C; O’Neill, S; Getenet, S; Chakraborty, S; Saleh, K; Yu, K

Improving Teaching and Learning in Higher Education through Machine Learning: Proof of Concept’ of AI’s Ability to Assess the Use of Key Microskills

Dann, C O’Neill, S Getenet, S Chakraborty, S Saleh, K Yu, K

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Education Sciences, 2024, 14, (8)
Issue Date:: 2024-08-01

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Field	Value	Language
dc.contributor.author	Dann, C
dc.contributor.author	O’Neill, S
dc.contributor.author	Getenet, S
dc.contributor.author	Chakraborty, S
dc.contributor.author	Saleh, K
dc.contributor.author	Yu, K https://orcid.org/0000-0001-5138-6749
dc.date.accessioned	2024-11-07T00:22:30Z
dc.date.available	2024-11-07T00:22:30Z
dc.date.issued	2024-08-01
dc.identifier.citation	Education Sciences, 2024, 14, (8)
dc.identifier.issn	2227-7102
dc.identifier.issn	2227-7102
dc.identifier.uri	http://hdl.handle.net/10453/181782
dc.description.abstract	Advances in artificial intelligence (AI), including intelligent machines, are opening new possibilities to support teaching and learning in higher education. This research has found a ‘proof of concept’ in the application of machine learning in the assessment of educators’ use of four key microskills, drawn from an internationally established framework. The analysis of teaching videos where these microskills were demonstrated multiple times in front of a green screen or in a space formed the data set. Multiple videos of this nature were recorded to allow for increased analysis and deconstruction of the video components to enable the application of machine learning. The results showed how AI can be used to support the collaborative and reflective practice of educators in a time when online teaching has become the norm. Having achieved a ‘proof of concept’, this research has laid the groundwork to allow for the whole framework of ten microskills to be applied in this way thus adding a new dimension to its use. Providing such critical information that is not currently available in such a systematic and personalised way to educators in the higher education sector can also support the validity of formative assessment practices.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Education Sciences
dc.relation.isbasedon	10.3390/educsci14080886
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	1301 Education Systems, 1302 Curriculum and Pedagogy, 1303 Specialist Studies in Education
dc.subject.classification	3901 Curriculum and pedagogy
dc.subject.classification	3902 Education policy, sociology and philosophy
dc.subject.classification	3904 Specialist studies in education
dc.title	Improving Teaching and Learning in Higher Education through Machine Learning: Proof of Concept’ of AI’s Ability to Assess the Use of Key Microskills
dc.type	Journal Article
utslib.citation.volume	14
utslib.for	1301 Education Systems
utslib.for	1302 Curriculum and Pedagogy
utslib.for	1303 Specialist Studies in Education
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Data Science Institute (DSI)
pubs.organisational-group	University of Technology Sydney/Strength - DSI - Data Science Institute
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2024-11-07T00:22:28Z
pubs.issue	8
pubs.publication-status	Published
pubs.volume	14
utslib.citation.issue	8

Abstract:

Advances in artificial intelligence (AI), including intelligent machines, are opening new possibilities to support teaching and learning in higher education. This research has found a ‘proof of concept’ in the application of machine learning in the assessment of educators’ use of four key microskills, drawn from an internationally established framework. The analysis of teaching videos where these microskills were demonstrated multiple times in front of a green screen or in a space formed the data set. Multiple videos of this nature were recorded to allow for increased analysis and deconstruction of the video components to enable the application of machine learning. The results showed how AI can be used to support the collaborative and reflective practice of educators in a time when online teaching has become the norm. Having achieved a ‘proof of concept’, this research has laid the groundwork to allow for the whole framework of ten microskills to be applied in this way thus adding a new dimension to its use. Providing such critical information that is not currently available in such a systematic and personalised way to educators in the higher education sector can also support the validity of formative assessment practices.

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http://hdl.handle.net/10453/181782