Investigating students’ perspectives on the integration of generative artificial intelligence in university curricula and assessments

The incorporation of Generative Artificial Intelligence (GenAI) in education offers new opportunities to enhance students’ learning experiences. Using a Chi-square Automatic Interaction Detection (CHAID) analysis, this study examined how the frequency of GenAI use for higher-order learning tasks and for supporting learning, as well as various demographic factors, influence students’ attitudes towards GenAI. The first decision tree analysis revealed that the respondents’ GenAI usage frequency for higher-order learning was the most important factor determining their desire to see GenAI incorporated into the university’s curriculum and assessment. In addition, for some learners, the study found that age was a significant factor, with the younger learners having a more positive attitude towards this technology than those who were older. An analysis of the second decision tree found that the frequency of GenAI use for learning support was the most important determinant of the students’ willingness to have GenAI mark their assignments. An understanding of how demographic and contextual factors influence the students’ attitudes towards the role of GenAI in education can guide academic institutions and educators in the development of effective educational strategies and policies that facilitate its acceptance by a diverse student population.