Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics

Atif, A; Jha, M; Richards, D; Bilgin, A

Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics

Atif, A

Jha, M Richards, D Bilgin, A

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Publisher:: Elsevier-Academic Press
Publication Type:: Chapter
Citation:: Intelligent Systems and Learning Data Analytics in Online Education, 2021, 2021, pp. 3-29
Issue Date:: 2021-06-18

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Field	Value	Language
dc.contributor.author	Atif, A https://orcid.org/0000-0003-0381-0343
dc.contributor.author	Jha, M
dc.contributor.author	Richards, D
dc.contributor.author	Bilgin, A
dc.contributor.editor	Caballe, S
dc.contributor.editor	Demetriadis, S
dc.contributor.editor	Gomez-Sanchez, E
dc.contributor.editor	Papadopoulos, P
dc.contributor.editor	Weinberger, A
dc.contributor.editor	Xhafa, F
dc.date.accessioned	2021-06-24T04:57:42Z
dc.date.available	2021-06-24T04:57:42Z
dc.date.issued	2021-06-18
dc.identifier.citation	Intelligent Systems and Learning Data Analytics in Online Education, 2021, 2021, pp. 3-29
dc.identifier.isbn	978-0-12-823410-5
dc.identifier.uri	http://hdl.handle.net/10453/149743
dc.description.abstract	Advancements in Artificial Intelligence (AI) have potentially created new ways to teach and learn, such as the use of Learning Analytics (LA) to monitor and support students using data captured in Learning Management Systems (LMS). To add human rather than data-based support, in this chapter, we present our use of AI-enabled Pedagogical Conversational Agents (CAs) over the past 12 months in multiple units/subjects across two universities. These CAs play a role similar to a teacher or peer learner by sharing the expertise they have acquired from the knowledge contained in student–teacher social interactions in LMS forums and grade book teacher feedback. Unlike teachers or peers, these CAs can be contacted anonymously at any time, they don’t mind being asked the same question repeatedly and they can empower students to explore options and outcomes. We conclude the chapter with a discussion of the potential of LA to automate CA interactions.
dc.format.extent	14
dc.language	en
dc.publisher	Elsevier-Academic Press
dc.relation.ispartof	Intelligent Systems and Learning Data Analytics in Online Education
dc.relation.ispartofseries	Intelligent Data-Centric Systems
dc.relation.isbasedon	10.1016/B978-0-12-823410-5.00013-9
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics
dc.type	Chapter
utslib.citation.edition	2021
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/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2021-06-24T04:57:41Z
pubs.edition	2021
pubs.place-of-publication	United Kingdom and United States
pubs.publication-status	Published online
dc.location	United Kingdom and United States

Abstract:

Advancements in Artificial Intelligence (AI) have potentially created new ways to teach and learn, such as the use of Learning Analytics (LA) to monitor and support students using data captured in Learning Management Systems (LMS). To add human rather than data-based support, in this chapter, we present our use of AI-enabled Pedagogical Conversational Agents (CAs) over the past 12 months in multiple units/subjects across two universities. These CAs play a role similar to a teacher or peer learner by sharing the expertise they have acquired from the knowledge contained in student–teacher social interactions in LMS forums and grade book teacher feedback. Unlike teachers or peers, these CAs can be contacted anonymously at any time, they don’t mind being asked the same question repeatedly and they can empower students to explore options and outcomes. We conclude the chapter with a discussion of the potential of LA to automate CA interactions.

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http://hdl.handle.net/10453/149743