Supplementary file 1_Aligning AI affordances with critical thinking skills in Chinese EFL: a discrepancy-based needs analysis for an AI-integrated blended reading module.docx

IntroductionArtificial intelligence (AI) is increasingly embedded in blended learning (BL) environments, yet its integration frequently emphasizes efficiency and performance outcomes rather than the systematic cultivation of higher-order cognition. Addressing this gap, the present study employs a discrepancy-based needs analysis to investigate how critical thinking skills (CTS) can be deliberately aligned with AI affordances in blended reading among Chinese undergraduates.
MethodsDrawing on qualitative evidence from 20 Chinese EFL undergraduates, this study collected data through AI-mediated reading interactions, reflective learning logs, semi-structured interviews, and a focused literature–technology scan. A discrepancy-based needs analysis was conducted to examine the alignment between AI affordances, instructional design, and critical thinking development.
ResultsThe findings suggest three interrelated structural misalignments between AI affordances, instructional design, and critical thinking development: (1) predominance of literal comprehension over analytical and evaluative processing, (2) limited metacognitive self-regulation, and (3) instrumental use of AI for surface-level linguistic assistance rather than structured reasoning support. Despite these patterns, learners appear ready for CTS-oriented blended learning and articulate clear expectations for explicit cognitive modelling, dialogic engagement, and adaptive AI feedback that evaluates reasoning quality rather than correctness alone.
DiscussionIn response to these findings, the study proposes a design-oriented Technology–CTS Needs Matrix that integrates empirical findings from participant data with literature- and theory-informed design extrapolations, systematically mapping Facione’s six CTS dimensions onto targeted AI and pedagogical affordances. By reconceptualising needs analysis as a mechanism for instructional alignment rather than deficiency identification, the study provides a theoretically integrated and empirically grounded foundation for structuring AI-mediated blended reading environments that foster critical thinking skills in EFL contexts.