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Zusammenfassungen
Chat Generative Pre-Trained Transformer (ChatGPT) has generated excitement and concern in
education. While cross-sectional studies have highlighted correlations between ChatGPT use and
learning performance, they fall short of establishing causality. This review examines experimental
studies on ChatGPT’s impact on student learning to address this gap. A comprehensive search
across five databases identified 69 articles published between 2022 and 2024 for analysis. The
findings reveal that ChatGPT interventions are predominantly implemented at the university
level, cover various subject areas focusing on language education, are integrated into classroom
environments as part of regular educational practices, and primarily involve direct student use of
ChatGPT. Overall, ChatGPT improves academic performance, affective-motivational states, and
higher-order thinking propensities; it reduces mental effort and has no significant effect on selfefficacy.
However, methodological limitations, such as the lack of power analysis and concerns
regarding post-intervention assessments, warrant cautious interpretation of results. This review
presents four propositions from the findings: (1) distinguish between the quality of ChatGPT
outputs and the positive effects of interventions on academic performance by shifting from welldefined
problems in post-intervention assessments to more complex, project-based assessments
that require skill demonstration, adopting proctored assessments, or incorporating metrics such as
originality alongside quality; (2) evaluate long-term impacts to determine whether the positive
effects on affective-motivational states are sustained or merely owing to novelty effect; (3) prioritise
objective measures to complement subjective assessments of higher-order thinking; and (4)
use power analysis to determine adequate sample sizes to avoid Type II errors and provide
reliable effect size estimates. This review provides valuable insights for researchers, instructors,
and policymakers evaluating the effectiveness of generative AI integration in educational
practice.
Von Ruiqi Deng, Maoli Jiang, Xinlu Yu, Yuyan Lu, Shasha Liu im Text Does ChatGPT enhance student learning? (2024) Dieser wissenschaftliche Zeitschriftenartikel erwähnt ...
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