Integrating generative artificial intelligence into teaching and assessment: A case study from a University in the UK: A case study from a University in the UK

Tadhg Blommerde*, Elenia Charalambous, William Bright, Ellie Musgrave, Lilian Ueno, Teagan Magee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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Abstract

This chapter explores the pioneering integration of generative artificial intelligence (GenAI) into teaching and assessment within a module at a UK university. This initiative represents a significant step in advancing AI literacy in higher education, aiming to equip students with essential employability skills. The innovative approach empowered students to use GenAI tools effectively, critically, ethically, and responsibly. The collaborative effort with students provided valuable insights into GenAI's potential to enhance student learning and future career prospects. Key recommendations for educators include dispelling the notion that GenAI use equates to cheating and that its ethical and critical application should be promoted. Encouraging transparency in GenAI usage can mitigate student engagement issues, while continuous feedback from students ensures the module remains responsive to their needs and experiences. By making GenAI use explicit and teaching effective prompt engineering, the module fostered a transition from covert use to responsible application. Hands-on experiential learning sessions were pivotal in developing students' GenAI proficiency, enhancing their engagement and skill development.

Original languageEnglish
Title of host publicationEffective Practices in AI Literacy Education
Subtitle of host publicationCase Studies and Reflections
EditorsXianghan O’Dea, Davy Tsz Kit Ng
Place of PublicationLeeds
PublisherEmerald
Pages119-126
Number of pages8
Edition1st
ISBN (Electronic)9781836088523
ISBN (Print)9781836088530
DOIs
Publication statusPublished - 2 Dec 2024

Keywords

  • Ethical AI literacy
  • Experiential learning
  • Generative artificial intelligence
  • Higher education
  • Student engagement

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