ArticleJournal of microbiology & biology education2026
Harnessing AI and chatbots to develop an interactive learning activity: student perceptions and outcomes.
Article in Journal of microbiology & biology education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Artificial intelligence (AI) has transformed various industries, and education is no exception. This paper details how AI can be utilized to support the development of an interactive, choose-your-own-adventure learning activity for pre-health students. With ChatGPT assistance, we identified and implemented the open-source platform Twine to create a branching, scenario-based activity focused on sexually transmitted diseases (STDs), allowing students to engage with clinical decision-making and apply course concepts. Additionally, ChatGPT's natural language processing capabilities allowed educators to create a script-based learning experience informed by prior student feedback, providing students with immediate, targeted feedback and support. This study describes how AI was used to develop a novel learning activity that encourages student engagement and application of course concepts. Students who piloted this activity in an upper-division course reported the activity to be an effective and engaging learning experience that helped them apply course content to real-life scenarios. Importantly, the use of AI helped streamline the development of this activity, lowering barriers to creating complex educational activities that may otherwise be difficult to implement. Here, we demonstrate how AI can be leveraged to support the development of interactive, scenario-based learning activities and provide practical guidance for instructors.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.