Developing metacognitive awareness in Olympiad students through the flipped classroom and generative artificial intelligence

Importance. The study addresses the growing role of metacognitive skills in Olympiad preparation in foreign languages, where assessment criteria differ significantly from international examinations and their interpretation requires a high level of self-regulation. The purpose of the study is to empirically test the effectiveness of a flipped classroom model combining asynchronous interaction with generative artificial intelligence models and synchronous peer assessment for developing metacognitive awareness, assessment literacy, and Olympiad writing quality among gifted students.

Materials and Methods. A quasi-experimental design with a two-year observation period (2023– 2025) was employed. The experimental group (n = 27) is taught using a flipped classroom model with a triad of feedback sources (self-assessment, peer review, and feedback from generative artificial intelligence). The control group (n = 28) received traditional preparation. The main measures are scores on the written part of the municipal stage of the All-Russian Olympiad for Schoolchildren, level of metacognitive awareness (an adapted questionnaire based on the Metacognitive Awareness Inventory), and assessment literacy. Statistical analysis included Welch’s t-test, Fisher’s exact test, and Benjamini–Hochberg correction for multiple comparisons.

Results and Discussion. In the second year, the experimental group demonstrated significantly higher results in total writing score (d = 0.85, p = 0.003) and in the communicative task achievement criterion (d = 0.99, p < 0.001). Higher levels of regulatory awareness (d = 0.93, p = 0.001) and conditional knowledge (d = 0.82, p = 0.004) are found in the experimental group. No differences emerged in the first year, indicating the need for prolonged metacognitive skill development. Qualitative analysis of reflective journals (324 entries, κ = 0.82) revealed the complementary nature of feedback sources: artificial intelligence provided a calibration function (78 % of entries) and immediacy (65 %), while peers offered contextually specific recommendations.

Conclusions. The comprehensive flipped classroom model with generative artificial intelligence integration, structured peer assessment, and metacognitive awareness development leads to significant improvement in Olympiad writing results. The effect manifests in the second year, indicating the need for prolonged metacognitive skill formation. Generative systems serve a calibration function, complementing (but not replacing) peer assessment and teacher feedback.

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