Redesigning Scaffolding with AI-Assisted Dynamic Assessment to Support Real-Time Learning Growth in EFL Learners
DOI:
https://doi.org/10.33394/jollt.v14i4.18614Keywords:
AI-assisted assessment, Real-time learning growth, Scaffoldings, Zone of proximal developmentAbstract
The integration of Artificial Intelligence in language learning is increasingly important because it can provide fast, personalized, and adaptive feedback that supports language competency development. However, in practice, the use of AI is often separated from the formative assesment framework, so it is not yet fully aligned with the principles of Dynamic Assesment (DA), which emphasizes the simultaneous integration of assessment and learning. This gap creates a need to understand how AI can used pedagogically to redesign scaffolding and support real-time learning growth in the context of English as a Foreign Language (EFL). This study aims to explore the use of AI in Dynamic Assessment and to examine the expereience and perception of students and lectures regarding its use. Using qualitataive approach, data were collected through observation, in-depth interviews, and documentation of AI exercise result among students in English Language and Culture Study Program of Universitas Tompotika Luwuk. Finding indicate that AI act as co-mediator that provide linguistic, phonological, metacognitive, and affective scaffolding, thereby accelerating the DA cycle and enhancing real-time learning growth. Students reported increased feelingsof security, independence, and motivation, while lecturers felt that assessment effeciency and the quality of pedagogical interventions had improved. This study concluded that AI-assisted DA presents an effective innovative assessment model, but still requires conceptual mediation from lecturers for learning to be optimal.
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