Skip to content
Research Article Open access CC BY 4.0

Impact of Generative AI in Academic Integrity and Learning Outcomes: A Case Study in the Upper East Region

Japheth Kodua Wiredu, Nelson Seidu Abuba, Hassan Zakaria

Asian Journal of Research in Computer Science · pp. 70–88 · Published 30 Jul 2024

10.9734/ajrcos/2024/v17i7491

Abstract

With the increasing use of Generative Artificial Intelligence (AI) tools like ChatGPT and Bard, universities face challenges in maintaining academic integrity. This research investigates the impact of these tools on learning outcomes (factual knowledge, comprehension, critical thinking) in selected universities of Ghana's Upper East Region during the 2023-2024 academic year. The study specifically analyzes changes in student comprehension and academic integrity concerns when using Generative AI for content generation, research assistance, and summarizing complex topics. A mixed-methods approach was employed, combining qualitative data from interviews and open-ended questions with quantitative analysis of survey data and academic records. The research focuses on three institutions: C. K. Tedam University of Technology and Applied Sciences, Bolgatanga Technical University, and Regentropfen University College. A purposive sampling technique recruited 150 participants (50 from each university) who had used Generative AI tools. Key findings show that 72% of students reported improved understanding of course material through Generative AI use, yet 75% cited academic integrity as a primary concern. Quantitative analysis revealed a weak to moderate positive correlation (r = 0.45) between AI tool usage and improved grades, with variations depending on the specific AI tasks performed. Qualitative data highlighted concerns about overreliance on AI and its impact on critical thinking skills. This research contributes to the ongoing debate on AI's role in education by providing valuable insights for educators and policymakers worldwide. The findings suggest that while AI tools can enhance comprehension, ethical considerations and potential drawbacks related to critical thinking require careful attention. The study concludes with recommendations for integrating AI literacy programs, developing ethical guidelines, and implementing advanced plagiarism detection systems to harness the benefits of Generative AI while mitigating risks to academic integrity. Although specific to the Upper East Region of Ghana, these insights may be applicable to other educational systems with similar characteristics.

Generative AI academic integrity learning outcomes higher education Upper East Region

Cited by 32

Validation of the GenAI Usage Scale (GAIUS) and the role of demographics in academic dishonesty in higher education

Aizhan Shomotova, Salwa Husain, Areej Elsayary · Innovations in Education and Teaching International · 2025

Enhancing Accessibility and Engagement in Computer Science Education for Diverse Learners

Japheth Kodua Wiredu, Nelson Seidu Abuba, Reuben Wiredu Acheampong · Asian Journal of Research in Computer Science · 2024

Embrace, Don’t Avoid: Reimagining Higher Education with Generative Artificial Intelligence

Teuku Rizky Noviandy, Aga Maulana, Ghazi Mauer Idroes · Journal of Educational Management and Learning · 2024

Efficiency Analysis and Optimization Techniques for Base Conversion Algorithms in Computational Systems

Japheth Kodua Wiredu, Basel Atiyire, Nelson Seidu Abuba · International Journal of Innovative Science and Research Technology (IJISRT) · 2024

AI-Enhanced Project-Based Learning

Muhammad Usman Tariq · Advances in Computational Intelligence and Robotics · 2025

The Automation Trap

Elif Karamuk · Advances in Computational Intelligence and Robotics · 2025

Mechanisms of academic stress affecting AI-assisted cheating behaviour in college students: a mixed methods study

Guohua Wang, Lianghao Tian, Xueru Xing · Interactive Learning Environments · 2025

How AI Tools are Accepted and Utilized in Academia: A Mixed Methods Study

Jose Noel Fabia, Vanessa Napoles, Joselito Eduard Goh · Journal of Social and Scientific Education · 2025

Showing 20 of 32 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

32

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.