ADAPTIVE TESTING AS A MECHANISM FOR INDIVIDUALIZING STUDENTS’ FOREIGN-LANGUAGE ACADEMIC WRITING INSTRUCTION: A DATA-DRIVEN APPROACH
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Author(s): | Orekhova E. Y., Yurin A. A., |
| Number of journal: | 3(76) | Date: | September 2026 |
| Annotation: | Teaching foreign-language academic writing to students at non-linguistic universities requires the search for and theoretical justification of effective approaches and tools for individualizing instruction in response to students’ heterogeneous linguistic, rhetorical and disciplinary backgrounds. The purpose of the article is to position computerized adaptive testing (CAT) as a mechanism for individualizing instruction in discipline-specific academic writing within a datadriven approach. To achieve this purpose, CAT is considered as a diagnostic and routing procedure that links assessment results with subsequent learning actions, making assessment part of the learning process rather than merely a tool for final evaluation. The methodological basis of the study is the data-driven approach. Drawing on this approach, the study employs literature analysis, theoretical generalization, systematization, instructional modelling and operationalization of academic writing skills. The article clarifies the relationship between individualization, adaptability, adaptive testing (AT) and CAT; identifies groups of discipline-specific academic writing skills as objects of adaptive diagnosis; and presents the CAT instructional framework, including an item bank, routing rules, a digital learning trace, formative feedback and teacher-mediated interpretation of data. The conditions for using CAT are substantiated: valid operationalization of writing skills, a balanced item bank, transparent routing, a combination of automated and teacher feedback, and ethically appropriate use of educational data. The article concludes that CAT effectiveness depends not on digitalization itself, but on pedagogical control over adaptive decisions. The practical significance of the results lies in using the proposed CAT design to develop adaptive courses, diagnostic tasks and micro-modules for academic writing instruction. | ||
| Keywords: | data-driven approach, individualized instruction, discipline-specific academic writing, computerized adaptive testing, formative assessment, educational data, digital learning trace, automated feedback, large language models, non-linguistic university |
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| For citation: | Yurin A. A., Orekhova E. Y. Adaptive testing as a mechanism for individualizing students’ foreign-language academic writing instruction: a data-driven approach. Biznes. Obrazovanie. Pravo = Business. Education. Law. 2026;3(76):320—327. DOI: 10.25683/VOLBI.2026.76.1708. |
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