AI-related measures and self-reported lesson-aim attainment: an explainable machine-learning analysis of TALIS 2024.

Mao Z

DOI: 10.3389/fpubh.2026.1911565
Published: 2026
Container: Frontiers in public health
Publisher: Not recorded
Open access: yes

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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.3389/fpubh.2026.1911565,
  title = {AI-related measures and self-reported lesson-aim attainment: an explainable machine-learning analysis of TALIS 2024.},
  author = {Mao Z},
  year = {2026},
  journal = {Frontiers in public health},
  doi = {10.3389/fpubh.2026.1911565},
  url = {https://doi.org/10.3389/fpubh.2026.1911565}
}

RIS

TY  - JOUR
TI  - AI-related measures and self-reported lesson-aim attainment: an explainable machine-learning analysis of TALIS 2024.
AU  - Mao Z
PY  - 2026
JO  - Frontiers in public health
DO  - 10.3389/fpubh.2026.1911565
UR  - https://doi.org/10.3389/fpubh.2026.1911565
ER  -

APA

Z, M. (2026). AI-related measures and self-reported lesson-aim attainment: an explainable machine-learning analysis of TALIS 2024.. Frontiers in public health. https://doi.org/10.3389/fpubh.2026.1911565

Source records

pubmed · retrieved 2026-09-25T18:08:16.517Z