Generative Artificial Intelligence in Tertiary Education
Assessment Redesign Principles and Considerations
Bibliographic Data
| ID | 22048872 |
|---|---|
| Authors | Che Yee Lye (0000-0003-1635-1975, Singapore University of Social Sciences), Lisa Lim (0000-0002-8199-5761, Teaching & Learning Centre, Singapore University of Social Sciences, 463 Clementi Road, Singapore 599494, Singapore), Lyndon Lim (The University of Western Australia, corresponding author) |
| Year | 2024 |
| Volume | 14 |
| Issue | 6 |
| Pages | 569 |
| Publication date | 2024-05-26 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci14060569 |
| OpenAlex | W4399042694 |
| Language | EN |
| Citations received | 10 |
| References cited | 20 |
The emergence of generative artificial intelligence (AI) such as ChatGPT has sparked significant assessment concerns within tertiary education. Assessment concerns have largely revolved around academic integrity issues among students, such as plagiarism and cheating. Nonetheless, it is also critical to consider that generative AI models trained on information retrieved from the Internet could produce biased and discriminatory outputs, and hallucination issues in large language models upon which generative AI acts provide made-up and untruthful outputs. This article considers the affordances and challenges of generative AI specific to assessments within tertiary education. It illustrates considerations for assessment redesign with the existence of generative AI and proposes the Against, Avoid and Adopt (AAA) principle to rethink and redesign assessments. It argues that more generative AI tools will emerge exponentially, and hence, engaging in an arms race against generative AI and policing the use of these technologies may not address the fundamental issues in assessments
Generative grammar · Higher education · Mathematics education · Political science · Artificial Intelligence in Healthcare and Education · Computer Science · Engineering Education and Technology · Online Learning and Analytics · Psychology · Artificial Intelligence
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Decoding symmetric and asymmetric pathways in generative AI learning adoption
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Innovations in Introductory Programming Education
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Redesigning Assessments for AI-Enhanced Learning
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Transforming Education
Assessment in the age of artificial intelligence
Generative AI tools and assessment
Generative AI and ChatGPT
The theory of planned behavior
Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior 1
Investigating antecedents of plagiarism using extended theory of planned behavior
Critical analysis of the technological affordances, challenges and future directions of Generative AI in education
Mapping out a research agenda for generative artificial intelligence in tertiary education
A framework for understanding assessment practice in higher education
Struggling and juggling
Exploring Academic Dishonesty among University Students in Barbados
Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour
| Citations per year | 5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |