Multi-Modal XAI Framework for Trustworthy Higher Education Applications

Altukhi, ZMA; Pradhan, S

Multi-Modal XAI Framework for Trustworthy Higher Education Applications

Altukhi, ZMA Pradhan, S

Permalink

Publication Type:: Conference Proceeding
Citation:: 2025, 18
Issue Date:: 2025-06-02

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (303.89 kB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Altukhi, ZMA
dc.contributor.author	Pradhan, S
dc.date	2025-08-14
dc.date.accessioned	2025-06-04T06:54:53Z
dc.date.available	2025-06-04T06:54:53Z
dc.date.issued	2025-06-02
dc.identifier.citation	2025, 18
dc.identifier.uri	http://hdl.handle.net/10453/187618
dc.description.abstract	In this paper, we propose a framework that integrates XAI methods in higher education applications. The framework aims to provide clear, transparent, trustworthy AI-based systems. The framework we developed addresses different challenges that hinder the integration of XAI in education and utilising Design Science Research (DSR) to ensure the research rigour through the lens of affordance theory to examine the interaction between the AI-based application and the educators as end-users.
dc.language	en
dc.relation.ispartof	America’s Conference on Information Systems
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Multi-Modal XAI Framework for Trustworthy Higher Education Applications
dc.type	Conference Proceeding
utslib.citation.volume	18
utslib.location.activity	Montreal, Canada
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 Professional Practice and Leadership
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2025-06-04T06:54:51Z
pubs.finish-date	2025-08-16
pubs.publication-status	Published
pubs.start-date	2025-08-14
pubs.volume	18

Abstract:

In this paper, we propose a framework that integrates XAI methods in higher education applications. The framework aims to provide clear, transparent, trustworthy AI-based systems. The framework we developed addresses different challenges that hinder the integration of XAI in education and utilising Design Science Research (DSR) to ensure the research rigour through the lens of affordance theory to examine the interaction between the AI-based application and the educators as end-users.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/187618