The Use of VLE Assessments in The Presence of AI Technology

Kara-Mohamed, M ORCID: 0000-0001-6423-7275 (2025) The Use of VLE Assessments in The Presence of AI Technology. Journal of Educational Technology Systems, 54 (1). pp. 67-87. ISSN 0047-2395

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Abstract

(1) Context: The growing accessibility of Artificial Intelligence (AI) technology, such as ChatGPT, poses a challenge to the integrity of online assessments in higher education. As AI becomes more integrated into academic contexts, educators face the complex task of maintaining assessment standards particularly within modern Virtual Learning Environments (VLEs). (2) Challenge: To address this issue, assessments must be thoughtfully designed to account for the capabilities of AI technology. Without such consideration, online assessment tools, such as online quizzes, may be perceived by students as opportunities to obtain marks with minimal effort or preparation. This in turn undermines the educational value of assessments. (3) Strategies: This paper presents strategies implemented within the engineering programmes at Liverpool John Moores University (LJMU) to safeguard the integrity of VLE assessments. It focuses on innovative and effective methods that can be implemented when designing a VLE quiz to minimise academic misconduct while at the same time ensuring a meaningful evaluation of student learning. (4) Results: An analysis of academic performance data indicates that these measures have been effective. Results demonstrate a normal distribution of marks comparable to previous years when assessments were conducted in supervised and in-person settings. (5) Recommendations: The findings indicate that maintaining academic standards in the era of AI requires well-designed online assessments that incorporate diverse approaches. This paper proposes several effective methods to support this goal.

Item Type:	Article
Uncontrolled Keywords:	3903 Education Systems; 39 Education; Minority Health; Networking and Information Technology R&D (NITRD); Bioengineering; Health Disparities and Racial or Ethnic Minority Health Research; Machine Learning and Artificial Intelligence; 4 Quality Education; 1303 Specialist Studies in Education; 3904 Specialist studies in education
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Engineering
Publisher:	SAGE
Date of acceptance:	5 June 2025
Date of first compliant Open Access:	23 July 2026
Date Deposited:	23 Jul 2026 14:06
Last Modified:	23 Jul 2026 14:06
DOI or ID number:	10.1177/00472395251351638
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29055

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