The current study aims to examine how students perceive the effect of generative artificial intelligence (GenAI) on their learning experiences in a risk management course.
Grounded in the artificial intelligence (AI)-supported (learner-as-collaborator) paradigm and constructivist theories, a single case study design was used to examine the personal narratives of 24 business students at a university in Ghana about their experiences using GenAI tools in a risk management course.
The findings revealed that students perceive the use of GenAI in their academic activities based on three dimensions: the functions, features and applicability to specific academic tasks. These three dimensions are also connected to the motivation of students to use GenAI tools, which include their reliability, speed and ability to learn and apply the information they gather.
The findings of the present study are discussed in relation to some weaknesses and future research propositions. First, data from the present study were gathered from students who were enrolled in a business program. What this means is that the experiences of students from other disciplines, such as engineering and information technology, were not included for purposes of comparison in the current study.
Ghana represents a suitable context for this research for a number of reasons. First, although the institutional regulatory frameworks and policies, especially in most universities, are at the embryonic stage, their application among students is conspicuous. In fact, recent studies in Ghana have shown that while students are upbeat about the benefits of GenAI in the educational setting, they would also like to see its uptake in educational institutions. Second, while Ghana is touted as one of the first few countries in Sub-Saharan Africa to have adopted an ICT policy document, little is known about how students perceive the effect of GenAI on their learning experiences. Third, the uneven pace of development in artificial intelligence in Africa underscores the need to thoroughly examine the readiness of tertiary institutions in the implementation and adoption of AI Technologizing the credibility of the findings.
