A Conceptual Framework for Authentic AI‐Enabled Assessment (AAA) in Higher Education
| aut.relation.articlenumber | fer3.70049 | |
| aut.relation.journal | Future in Educational Research | |
| dc.contributor.author | Gedera, Dilani | |
| dc.date.accessioned | 2026-08-03T02:21:15Z | |
| dc.date.issued | 2026-07-26 | |
| dc.description.abstract | Higher education is at a critical juncture as generative artificial intelligence (AI) redefines assessment practices. This article offers a conceptual framework illustrating how authentic AI-enhanced assessments (AAA) can support the reclamation of higher education's core mission: developing critical thinking, creativity, ethical reasoning, and meaningful real-world problem-solving. With the advent of AI, current assessment practices may not adequately evaluate the deep interdisciplinary competencies required for today's complex professional environments. Instead of resorting to increased surveillance or outright bans on AI, this article contends that institutions should embrace AI as a supportive tool to reinforce authentic assessment strategies. The AAA framework emphasises not only the final output but also the iterative learning process—integrating reflective practice, student agency, and responsiveness to unexpected twists that compel students to think on their feet. The article demonstrates that AI-enhanced authentic assessments—ranging from interactive tasks to multi-stage applied projects—can transform evaluation across disciplines by supporting the development of a solid theoretical foundation and the practical, adaptable competencies demanded by modern professional practice. | |
| dc.identifier.citation | Future in Educational Research, ISSN: 2835-9402 (Print); 2835-9402 (Online), Wiley. doi: 10.1002/fer3.70049 | |
| dc.identifier.doi | 10.1002/fer3.70049 | |
| dc.identifier.issn | 2835-9402 | |
| dc.identifier.issn | 2835-9402 | |
| dc.identifier.uri | http://hdl.handle.net/10292/21684 | |
| dc.language | en | |
| dc.publisher | Wiley | |
| dc.relation.uri | https://onlinelibrary.wiley.com/doi/10.1002/fer3.70049 | |
| dc.rights | Creative Commons Attribution CC BY 4.0 | |
| dc.rights.accessrights | OpenAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | 3903 Education Systems | |
| dc.subject | 39 Education | |
| dc.subject | Networking and Information Technology R&D (NITRD) | |
| dc.subject | Machine Learning and Artificial Intelligence | |
| dc.subject | 4 Quality Education | |
| dc.subject | AI-enhanced assessments | |
| dc.subject | authentic assessment | |
| dc.subject | business education | |
| dc.subject | generative AI | |
| dc.subject | higher education | |
| dc.title | A Conceptual Framework for Authentic AI‐Enabled Assessment (AAA) in Higher Education | |
| dc.type | Journal Article | |
| pubs.elements-id | 770652 |
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