Epistemic network analysis to study an unplugged model-eliciting activity for computational thinking with high school students in Mexico

Purpose This study examines how model-eliciting activities (MEAs) help students in a private school with middle-income high school students elicit computational thinking (CT) in an unplugged activity. The focus is on equitable participation across diverse academic backgrounds in resource-limited settings. Design/methodology/approach The research employed epistemic network analysis (ENA) to analyze video-recorded conversations of two three-student teams solving an unplugged tic-tac-toe MEA. Participants represented varied academic tracks, programming experience levels and socioeconomic backgrounds. The researchers coded the conversations for computational thinking constructs: decomposition, pattern recognition, abstraction and algorithms. Findings ENA revealed similar network structures between teams and participants despite their different compositions. Both teams demonstrated robust connections across all four computational thinking constructs. The unplugged MEA format enabled equitable participation regardless of prior programming experience or academic background, with balanced engagement observed across all team members. Originality/value This study uniquely applies ENA to examine computational thinking development through unplugged MEAs in Mexico’s educational context. It provides empirical evidence for MEAs as tools for democratizing access to computational thinking education in resource-limited settings while introducing a methodological framework for analyzing cognitive development in collaborative learning environments.