Section

Curriculum and assessment design

Abstract

Large Language Models (LLMs) and conversational-style generative artificial intelligence (AI) are causing major disruption to higher education pedagogy. The emergence of tools like ChatGPT has raised concerns about plagiarism detection but also presents opportunities for educators to leverage AI to build supportive learning environments. In this commentary, we explore the potential of AI-augmented teaching and learning practice in higher education, discussing both the productive affordances and challenges associated with these technologies. We offer instructional advice for writing instructional text to guide the generation of quality outputs from AI models, as well as a case study to illustrate using AI for assessment design. Ultimately, we suggest that AI should be seen as one tool among many that can be used to enhance teaching and learning outcomes in higher education.

Practitioner Notes

  1. Learning to write effective instructional prompts for AI models will help augment learning and teaching practice.

  2. AI models offer the potential for significant productive affordances, including personalised feedback, adaptive learning pathways, and enhanced student engagement.

  3. To successfully integrate AI into higher education, institutions must prioritise faculty development programs that provide training and support for educators to effectively use these technologies in the classroom.

  4. Institutions must ensure that AI is used in a way that aligns with their values and mission and that students are informed about how their data is being used.

  5. It is important to recognise that AI is not a panacea for all of the challenges facing higher education. Rather, it should be seen as one tool among many that can be used to enhance teaching and learning outcomes.

Twitter Handle

@bron_eager

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