Tang, Chun Meng, and Chaw, Lee Len (2024) Student learning performance evaluation: Mitigating the challenges of generative AI chatbot misuse in student assessments. In: Proceedings of the European Conference on e-Learning (23) pp. 357-364. From: ECEL 20245: 23rd European Conference on e-Learning, 25-25 October 2024, Porto, Portugal.

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Abstract

Since the launch of ChatGPT, a growing number of generative artificial intelligence (AI) chatbots have entered the market. Although chatbots have the potential to help students learn, misusing them to complete assessments raises questions about the authenticity of the work and puts students at risk of academic misconduct. Given the crucial role of assessments in evaluating students’ learning performance, uncertainties about the authenticity of the work call into question the extent to which students have achieved the intended learning outcomes. This study conducted a thematic analysis to provide an overview of the challenges that chatbot misuse may pose to student learning performance evaluation, followed by the various mitigation strategies to overcome these challenges. This study searched the Education Resources Information Centre (ERIC) database for peer-reviewed articles published in scholarly journals after 30 November 2022 (the launch date of ChatGPT, as this study focuses on generative AI rather than other types of AI) and until 30 April 2024. The thematic analysis of 17 articles identified five major themes (and respective sub-themes) in the discussions of these articles, i.e., reasons students use chatbots for assessments, challenges that chatbots may pose to student learning performance evaluation, mitigation strategies, detection strategies, and counter-detection strategies. As chatbots become more prevalent and powerful, the study's findings provide education stakeholders with insightful information on the implications of students misusing chatbots for assessments and how this affects their learning performance evaluation.

Item ID:	84055
Item Type:	Conference Item (Research - E1)
ISBN:	978-1-917204-22-4
Date Deposited:	14 Jan 2025 00:45
FoR Codes:	39 EDUCATION > 3902 Education policy, sociology and philosophy > 390201 Education policy @ 20% 39 EDUCATION > 3901 Curriculum and pedagogy > 390102 Curriculum and pedagogy theory and development @ 30% 39 EDUCATION > 3904 Specialist studies in education > 390402 Education assessment and evaluation @ 50%
SEO Codes:	16 EDUCATION AND TRAINING > 1603 Teaching and curriculum > 160301 Assessment, development and evaluation of curriculum @ 60% 16 EDUCATION AND TRAINING > 1603 Teaching and curriculum > 160304 Teaching and instruction technologies @ 20% 16 EDUCATION AND TRAINING > 1602 Schools and learning environments > 160205 Policies and development @ 20%
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