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Scientific inquiry learning with a simulation: providing within-task guidance tailored to learners’ understanding and inquiry skill

Mari Fukuda, Shiva Hajian, Misha Jain, Arita L. Liu, Teeba Obaid, John C. Nesbit, Philip H. Winne

2022International Journal of Science Education22 citationsDOI

Abstract

In scientific inquiry learning, within-task guidance tailored to the learner’s domain knowledge and inquiry skill may be essential to promote intended learning outcomes. However, due to dynamic complexity across the timeline of inquiry learning, principles for designing tailored guidance are elusive. In this study, experienced tutors provided just-in-time guidance to 11 learners. We analysed tutor-learner interactions to investigate how tutors adapted guidance. We found tutors provided five types of guidance: prompts, support for domain knowledge, assessments, hints, and feedback. Guidance was provided when learners made errors, expressed difficulties, or asked questions; or when the tutor judged a learner successfully demonstrated a skill and was ready to progress to a follow-on skill. Based on these results, we propose a model for tailored, just-in-time guidance in simulation-assisted inquiry learning environments.

Topics & Concepts

TimelineTUTORTask (project management)Computer scienceDomain (mathematical analysis)Mathematics educationPsychologyManagementMathematicsMathematical analysisHistoryEconomicsArchaeologyIntelligent Tutoring Systems and Adaptive LearningVisual and Cognitive Learning ProcessesInnovative Teaching and Learning Methods
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