Artificial Intelligence Enhanced Course Content Labelling Conceptual Model and Testing with University Teachers

Abstract

<p>This study presents a novel approach by investigating the efficacy of an artificial intelligence (AI) -aided tool, Annif, in generating course-specific keywords for university courses. With the increasing number of university courses, there is a need for an effective method to assist students in navigating and selecting courses based on their interests and job market compatibility. The traditional manual keyword approach, while accurate, can be laborious and time-consuming. AI has the potential to automate this process, but it is crucial for teachers to validate the results to ensure accuracy. This study seeks to explore the potential of AI in this context, addressing two key questions: the ability of AI-generated keywords to establish course connections and the reactions of teachers to the use of AI in keyword generation. The results reveal that the AI tool can provide accurate keywords for about 64% of the courses. While teachers found this approach useful, the study highlights the need for teacher validation to ensure the accuracy and appropriateness of the AI-generated data. Therefore, while AI can significantly contribute to keyword generation, human intervention is still indispensable to maintain its quality in the academic context.</p>