Assessing AI Literacy among Academic Staff: Insights from a Higher Education Survey

<p dir="ltr">This study explores the level of artificial intelligence (AI) literacy among academic staff. Using</p><p dir="ltr">the ‘technological pedagogical content knowledge’ (TPACK) framework, we employed mixed-</p><p dir="ltr">method research, collecting data from 106 academic staff members across various disciplines.</p><p dir="ltr">We investigated the challenges and benefits of educators adopting AI as well as their AI</p><p dir="ltr">understanding, abilities, confidence and competencies. Our findings indicate a low rate of AI</p><p dir="ltr">adoption by academics, with most applying it superficially for lower-order tasks. Our findings</p><p dir="ltr">also reveal the different weighting of the TPACK framework components – technological</p><p dir="ltr">knowledge (TK), technological content knowledge (TCK) and technological pedagogical</p><p dir="ltr">knowledge (TPK) – with major concern raised by staff on TPK where it is indicated that staff</p><p dir="ltr">need guidance and training on how to make the most of AI in their teaching. The significance</p><p dir="ltr">of this paper lies in its exploration of the current state of AI adoption among academic staff,</p><p dir="ltr">highlighting both its benefits and challenges. Given the limited existing research on AI literacy</p><p dir="ltr">from the perspective of academic staff, this study offers a distinctive and valuable contribution</p><p dir="ltr">to the discourse. Furthermore, the integration of the TPACK framework offers a crucial</p><p dir="ltr">perspective, emphasising the need for a more comprehensive and effective incorporation of</p><p dir="ltr">AI into educational practices.</p>