Guided inquiry in school science: A mini review of orchestration, assessment, and AI

Shaljan Areepattamannil^*

• Emirates College for Advanced Education, Abu Dhabi, United Arab Emirates

This mini review asks how to orchestrate guidance, assessment, and student agency so inquiry reliably yields durable understanding and inclusion, moving beyond the inquiry versus direct instruction debate. It draws on twenty-six peer-reviewed studies from 2017 to 2025 spanning classroom interventions, video studies, large-scale secondary analyses, discipline-specific and teacher-education reviews, flipped and other technology-mediated inquiry, and AI. Studies were coded for inquiry phases, forms of guidance, assessment practices, and outcomes, and were synthesised configuratively across four strands: learning and affect, enactment quality, assessment literacy, and technology/AI. Findings showed that guided, discourse-rich inquiry supported conceptual understanding, higher-order thinking, and motivation, while the raw frequency of "inquiry activities" related inconsistently to achievement when quality and guidance were ignored; assessment literacy for scientific practices remained a key bottleneck; and flipped structures and AI copilots helped when they scaffolded prediction–evidence–explanation sequences and preserved learner agency. The review concludes that systems should prioritise phase-specific orchestration, build assessment capability for modelling, data analysis, and argumentation, instrument classrooms to capture process quality, and evaluate AI as formative infrastructure rather than as an answer engine.