Exploring the Use of Artificial Intelligence in Designing Course Descriptions: A Study at Abu IssaFaculty of Education, University of Zawia, Libya

Hanan Mansour; Magda Hassan; Someraa Shakonah; Soud Kaa; Mohamed Hmouma; Emran Altuwayb

doi:10.61227/jetti.v3i1.182

Authors

Hanan Mansour University of Zawia
Magda Hassan University of Zawia
Someraa Shakonah University of Zawia
Soud Kaa University of Zawia
Mohamed Hmouma University of Zawia
Emran Altuwayb University of Zawia

DOI:

https://doi.org/10.61227/jetti.v3i1.182

Keywords:

Artificial Intelligence, Course Description, Education, Training

Abstract

This study investigates faculty members’ perceptions regarding the integration of Artificial Intelligence (AI) in the design and development of course descriptions atAbu Issa faculty of Education, University of Zawia, Libya, which is a context where higher education institutions are increasingly exploring AI to improve curriculum quality but face challenges of limited training, institutional readiness, and skepticism about its reliability. By using a descriptive research design, the study examined data from 87 faculty members across various disciplines through a structured questionnaire administered after a hands-on AI training workshop. Participants engaged with AI tools in authentic curriculum development tasks before reflecting on their experiences. Data were analyzed using descriptive statistical techniques: frequencies, percentages, means, and standard deviations, to identify patterns and summarize perceptions without inferring causal relationships. The findings reveal a moderately positive attitude toward the use of AI, especially in enhancing efficiency, aligning with accreditation standards, and updating course content. However, notable reservations emerged concerning the reliability of AI for language refinement, institutional support, and faculty preparedness. Despite recognizing AI’s transformative potential in curriculum design, participants expressed concerns about data security, the loss of human creativity, and the need for intensive training. The study highlights the need for capacity building initiatives and institutional support to ensure effective and equitable AI integration in academic settings. Finally, it recommends future research with broader samples, longitudinal designs, and objective outcome measures to deepen understanding and guide responsible AI adoption in higher education.

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