https://ir.zou.ac.zw/files/original/89210af9949e799ba0df894ee612fe68.pdf 99f95fa10015effed380c781bb150645 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Staff Publications Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource ARTIFICIAL INTELLIGENCE IN ACADEMIC DECISION-MAKING AND STUDENTS’ RECORDKEEPING: A CASE OF AN ODEL UNIVERSITY Creator An entity primarily responsible for making the resource GODFREY TSVUURA Description An account of the resource The integration of artificial intelligence (AI) into higher education is reshaping traditional processes of academic decision-making and students’ recordkeeping. This study explores the use of AI in academic decision–making and students’ recordkeeping at Zimbabwe Open University (ZOU). A qualitative research methodology was adopted along with purposive sampling technique in which a sample of 5 heads of sections who deal with students’ recordkeeping were chosen as they have knowledge about the problem at hand. Data collected were analysed in thematic strands. Findings underscore that at ZOU, AI is being used to generate educational materials such as study guides, quizzes, automate administrative tasks like students grading as well as in other e-learning platforms such as My Vista, students support services, coursework material preparation and writing by students, data analytics and in widespread research. The study concludes that while AI offers significant opportunities to improve the management of students’ recordkeeping and academic decisions, its deployment must be guided by ethical principles, legal compliance, and capacity-building initiatives tomaximise benefits and mitigate risks. The study recommends the need for human oversight, inclusive data practices and robust governance frameworks to ensure fairness and accountability in AI-enabled academic decision-making and students’ recordkeeping. Date A point or period of time associated with an event in the lifecycle of the resource 2026 Publisher An entity responsible for making the resource available Zimbabwe Open University Journal of Applied Social Sciences Artificial Intelligence digital environments machine-learning records Records Management students’ recordkeeping