From Concordance to Confidence: A Sequential Explanatory Evaluation of a Digital Inductive Model for Linguistic Thinking in Pre-Service French Teacher Education

<title>Abstract</title> <p>This sequential explanatory mixed-methods study examined whether a structured digital inductive model could strengthen linguistic thinking and reshape pedagogical orientations among pre-service French as a Foreign Language (FFL) teachers in Egypt. The model combined guided concordance work, a purpose-built corpus of authentic French texts, collaborative pattern discovery, and reflective discussion across a ten-week course intervention. Fifty-six third-year student-teachers completed the intervention; matched quantitative data were available for 55 participants. Linguistic thinking was assessed through a researcher-developed Linguistic Analysis Task (LAT) targeting pattern recognition, evidence-based hypothesis formulation, and metalinguistic reflection. Paired-samples analysis indicated a substantial observed increase in LAT performance from pre-test to post-test, t(54) = 21.43, p &lt; .001, d = 2.89, with gains across all three subcomponents. Reflective journals and a focus group were then analyzed thematically to explain the quantitative pattern. Qualitative findings indicated a staged movement from initial uncertainty and technical friction toward active inquiry, confidence in using authentic evidence, and a more facilitative conception of language teaching. The results suggest that corpus-supported inductive work can offer a productive route for developing analytic language-teaching competence. Because the quantitative phase used a single-group pre-test/post-test design, the findings should be interpreted as strong evidence of within-cohort development rather than as definitive causal proof. The study contributes a refined model for linking data-driven learning, digital pedagogical competence, and pre-service teacher identity formation in technology-enhanced language teacher education.</p>