Deploy an educational chatbot to give students instant question-and-answer support outside class when teacher interaction time is limited¶

Strategy · All strategies
Evidence · 2 claims (2 for) · 2 studies (1 causal, 1 qualitative), q2 · 0 of 2 report an effect size · 2 claims rest on one study

Description¶

The article recommends providing suitable learning tools for out-of-class biology study because teachers "do not have enough class time to interact with students, and students often do not have the opportunities to raise questions in class." A chatbot offers instant interactions and supports anytime and anywhere, letting students review biology knowledge on faulty foundations rather than falling behind.

Design Implications¶

Context¶

Requirements¶

• A chatbot capable of instant interaction and learning support must be available to students outside class hours

Constraints¶

• The article's evidence covers a grade 7 biology course in a junior high school; out-of-class use assumes students can access the tool independently

Target Learners¶

• junior high school students in biology courses

Target Learning Goals¶

• reviewing and consolidating biology knowledge out of class
• obtaining instant answers to questions teachers cannot address in limited class time

Claims¶

• A biology learning chatbot system had a positive impact on grade 7 students' biology learning achievement in a quasi-experiment [+W]
• Students perceived ChatGPT as a valuable learning tool for asking questions, getting explanations, and clarifying understanding [+W]

Related Strategies¶

• Use asynchronous AI tutoring for students' first engagement with challenging material, reserving class time for higher-order skills
• Use a non-generative AI chatbot with a pre-programmed, human-curated knowledge base to answer student questions with pre-approved responses
• Evaluate AI systems before deploying them with students

Examples¶

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Key Sources¶

• Yen-Ting Lin, Jian-Heng Ye. (2023). Development of an Educational Chatbot System for Enhancing Students’ Biology Learning Performance. Journal of Internet Technology, vol. 24, no. 2, pp. 275-281. https://doi.org/10.53106/160792642023032402006