Supporting self-directed learning and self-assessment using TeacherGAIA, a generative AI chatbot application: Learning approaches and prompt engineering

ABSTRACT

Self-directed learning and self-assessment require student responsibility over learning needs, goals, processes, and outcomes. However, this student-led learning can be challenging to achieve in a classroom limited by a one-to-many teacher-led instruction. We, thus, have designed and prototyped a generative artificial intelligence chatbot application (GAIA), named TeacherGAIA, that can be used to asynchronously support students in their self-directed learning and self-assessment outside the classroom. We first identified diverse constructivist learning approaches that align with, and promote, student-led learning. These included knowledge construction, inquiry-based learning, self-assessment, and peer teaching. The in-context learning abilities of large language model (LLM) from OpenAI were then leveraged via prompt engineering to steer interactions supporting these different learning approaches. These interactions contrasted with ChatGPT, OpenAI’s chatbot which by default engaged in the traditional transmissionist mode of learning reminiscent of teacher-led instruction. Preliminary design, prompt engineering and prototyping suggested fidelity to the learning approaches, cognitive guidance, and social-emotional support, all of which were implemented in a generative AI manner without pre-specified rules or “hard-coding”. Other affordances of TeacherGAIA are discussed and future development outlined. We anticipate TeacherGAIA to be a useful application for teachers in facilitating self-directed learning and self-assessment among K-12 students.

KEYWORDS:

• GPT-4
• chatbot
• generative AI
• self-directed learning
• self-assessment

Acknowledgments

We thank Abdul Kamal Ahmed for application development.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/23735082.2023.2258886