An experimental study on the use of Markov chains to teach generative AI to high school students

Bibliographic Data

ID22411096
AuthorsJing Li (0000-0001-7792-4322, Yancheng Teachers University, corresponding author)
Year2026
Pages1-13
Publication date2026-07-19
Open AccessYes
TypeARTICLE
VenueThe Journal of Educational Research (JOURNAL)
Journal identifiersISSN: 0022-0671 • E-ISSN: 1940-0675
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00220671.2025.2551595
OpenAlexW7169727059
LanguageEN
References cited27

This study investigates a teaching intervention that uses Markov chains as a core tool to introduce high school students to generative artificial intelligence (GenAI). The intervention aims to teach students the foundational principles of AI and its role in text generation through a probabilistic model. The study employs a mixed-methods approach, quantifying changes in students’ understanding of AI basics, model thinking, and critical comprehension. Additionally, qualitative analysis of classroom observations and learning journals provides deeper insights into the learning process. Results show that students exhibit significant improvement in grasping AI concepts and develop strong construction skills and creative expression through hands-on modeling. The study emphasizes the importance of introducing low-barrier, interpretable AI modeling tools in K-12 education to facilitate a smoother transition into understanding complex AI systems.

Generative grammar · Generative model · Intervention (counseling) · Markov chain · Probabilistic logic · Qualitative analysis · Educational Games and Gamification · Statistics Education and Methodologies · Teaching and Learning Programming

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