Date
Publisher
arXiv
The arrival of AI tools and in particular Large Language Models (LLMs) has
had a transformative impact on teaching and learning and institutes are still
trying to determine how to integrate LLMs into education in constructive ways.
Here, we explore the adoption of LLM-based tools into two teaching programmes,
one undergraduate and one postgraduate. We provided to our classes (1) a
LLM-powered chatbot that had access to course materials by RAG and (2)
AI-generated audio-only podcasts for each week$\text{'}$s teaching material. At
the end of the semester, we surveyed the classes to gauge attitudes towards
these tools. The classes were small and from biological courses. The students
felt positive about AI generally and that AI tools made a positive impact on
teaching. Students found the LLM-powered chatbot easy and enjoyable to use and
felt that it enhanced their learning. The podcasts were less popular and only a
small proportion of the class listened weekly. The class as a whole was
indifferent to whether the podcasts should be used more widely across courses,
but those who listened enjoyed them and were in favour.
Study at a glance
- Question: How do university biology students view using an AI chatbot and AI-generated podcasts in their courses?
- Setting and data: Small undergraduate and postgraduate biology classes at the end of a semester.
- Method: End-of-semester student survey.
Why it matters
AI tools and Large Language Models have had a transformative impact on teaching and learning. Yet, institutes are still trying to determine how to integrate LLMs into education in constructive ways.
Key findings
- In small undergraduate and postgraduate biology courses, students found an AI chatbot easy and enjoyable to use and felt it enhanced their learning.
- Students expressed positive attitudes toward AI generally and felt that AI tools made a positive impact on teaching.
- AI-generated course podcasts were less popular, though the few students who listened weekly enjoyed them and favored wider use.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Study design
