The AI Paradox in L2 Writing: Why Helpful Feedback Creates Unhelpful Dependency in Higher Education

Large Language Models (LLMs) offer immediate pedagogical benefits in higher education L2 writing instruction, yet sustained reliance creates critical, underexplored risks to learner autonomy, metacognitive judgment, and linguistic identity. This Critical Interpretive Synthesis (CIS) of 47 peer-reviewed studies (2015–2025) identifies which patterns of AI-assisted interaction led to successful versus unsuccessful educational outcomes in higher education. Spanning pre-LLM and Generative AI (GenAI) eras, it addresses three knowledge gaps: how sustained reliance affects learner confidence and autonomy (psychological); how algorithmic approval reshapes communicative intentionality (cognitive); and how algorithmic norms systematically marginalize non-Western linguistic expression (ideological). The synthesis develops the AI Dependency Syndrome (ADS) framework, which maps four fundamental trade-offs in AI-mediated writing: fluency gains versus metacognitive erosion, anxiety reduction versus autonomous judgment, grammatical accuracy versus communicative intent, and improved essay quality versus voice authenticity. These trade-offs arise from three interconnected mechanisms: Loss of Confidence in Unaided Production, Algorithmic Approval Bias, and Internalization of AI Norms, which recursively interact to reshape learner conceptions of competence, authorship, and linguistic identity. The framework integrates self-efficacy, communicative competence, and identity theories to provide nine observable diagnostic indicators enabling educators to recognize emerging dependency patterns in real classrooms. Critically, it operationalizes three evidence-based design principles grounded in theory and research. By clarifying what distinguishes effective from ineffective AI-assisted interactions in higher education L2 writing, this synthesis positions AI dependency not as incidental overuse, but as a systemic, preventable condition requiring intentional pedagogical design.