Speaker
Description
The rapid integration of Generative Artificial Intelligence (GenAI) in English as a Foreign Language (EFL) education offers unprecedented linguistic scaffolding but risks inducing "cognitive offloading". This uncritical reliance on AI tools threatens to erode learner autonomy and produce "AI-nized writing" devoid of the authentic student-author voice. Furthermore, traditional assessment models that evaluate static end-products are increasingly inadequate for capturing the complex meaning-negotiation processes between learners and AI. To address this pedagogical gap, this study proposes a novel, process-oriented assessment framework aligned with the dimensions of AI literacy, agency, and ethical assessment.
The framework introduces two primary instruments: the AI-mediated Learner Autonomy Scale (LAS) and the Student-Author Voice (SAV) Rubric. The LAS quantifies students' self-regulation strategies, metacognitive fact-checking habits, and independent decision-making capacities. Concurrently, the SAV Rubric evaluates the degree of human-AI co-creation by assessing authenticity of expression, argumentative ownership, and nuanced contextualization. To empirically validate these instruments, the study utilizes an explanatory sequential mixed-methods design, collecting real-time "digital footprints" such as prompt-logs and screencast videography (SCV) to observe actual meaning-negotiation behaviors within the learner's Zone of Proximal Development. By shifting the evaluation paradigm from the final product to the cognitive process, this framework equips educators with actionable metrics to transform GenAI from an intellectual crutch into a constructive cognitive scaffold, ensuring the preservation of academic integrity and learner agency.
