The current structure of module management within the school CIT features an overlapping array of responsibilities among coordinators that spans multiple departments and competence centers. This structure results in inefficiencies and confusion due to the lack of a cohesive framework, impacting the strategic alignment of educational objectives and research initiatives. This thesis proposes a redefined framework aimed at streamlining module coordination, which will establish clear roles and minimize content overlap, aligning modules with CIT’s broader educational and research goals.
To address these challenges, the thesis will focus on developing and implementing AI-driven tools to automate and enhance the accuracy of module descriptions. The project will unfold in three main phases: analyzing and categorizing existing modules to identify core areas and redundancies, integrating new modules effectively to ensure seamless incorporation into CIT’s offerings, and deploying AI tools to facilitate ongoing management and updating of module information. This approach will significantly reduce redundancies and clarify jurisdiction, thereby improving the overall management of academic modules.