Chinese EFL Student Data on AI and Critical Thinking in Blended Reading

Qualitative evidence from 20 Chinese undergraduates learning English as a foreign language, collected by Anni Yang and published on figshare in April 2026. The data includes AI-mediated reading interactions, reflective logs, and interview transcripts, analyzed to identify misalignments between AI affordances and critical thinking skill development. The study proposes a design matrix to align technology with cognitive skill cultivation.

Use Cases

• Designing AI feedback systems that evaluate reasoning quality based on the described need for adaptive feedback.
• Developing blended reading modules that promote analytical and evaluative processing based on the identified structural misalignments.
• Creating instructional materials for metacognitive self-regulation in language learning based on the study's findings.
• Conforming pedagogical design to a Technology–Critical Thinking Skills Needs Matrix based on the proposed framework.

Strengths

• Data is licensed under CC-BY-4.0, permitting broad reuse and adaptation.
• Study employs a multi-method qualitative approach, including interviews, logs, and AI interactions.
• Findings are grounded in empirical data from 20 participants and integrated with theoretical frameworks.

Limitations

• The dataset is a 498.2 KB DOCX file, indicating a limited textual document rather than a structured data file.
• Row count and column-level documentation are absent; data structure and semantics must be inferred from the document.
• The sample size of 20 participants may limit the generalizability of the findings.

Provenance

Source

figshare, authored by Anni Yang.

Collection Method

Data collected through AI-mediated reading interactions, reflective learning logs, and semi-structured interviews with 20 Chinese EFL undergraduates.

Time Range

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Freshness

Last updated 2026-04-13 04:35:46; freshness should be verified.

Geography

Data likely pertains to Chinese undergraduate students.