Research Approach

Analysis Phase: What are freshmen students learning and support needs for the process of ML-enabled academic writing and how can students data literacy for academic writing as a precondition for evaluating and using feedback be assessed?

Study 1 (Design): What are quality indicators of practical and effective ML-enabled learning support with two components: a) formative evaluation: immediate feedback during writing process, b) summative evaluation: automatic scoring of texts and what are influencing contextual factors in both universities (e.g., European teaching culture in Switzerland, Asian teaching culture in Thailand)?

Study 2 (Outcomes): How and to what extent does the use of ML-enabled learning support contribute to freshmen students learning outcomes and the quality of the generated academic text?

Study 3 (Change in Writing Practice): To what extent is the personalized learning support system accepted by students and contributes to altered writing performance and practices in the long run?