Abstract Book of the 9th International Conference on Research in Education
Year: 2025
DOI:
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Balancing Innovation and Academic Integrity in AI-Driven Language Education: A Task-Based Approach
Nadine Jaafarawi
ABSTRACT:
As education undergoes a rapid digital transformation, the integration of Artificial Intelligence (AI) in language classrooms presents both opportunities and ethical challenges. This qualitative study explores the role of AI within Task-Based Language Teaching (TBLT), emphasizing how technology can enhance language learning while maintaining academic integrity. By embedding AI into communicative tasks, the research investigates how students engage in “learning by doing,” improving their critical thinking, interactional competence, and problem-solving skills in real-world contexts. The methodology includes classroom observations to capture student interactions and engagement, semi-structured interviews with students to understand their perceptions of AI-enhanced language learning, and reflective journals to explore their experiences with AI use in their assignments. Additionally, students’ presentation grades were collected from Blackboard (BB) to measure learning outcomes, providing a comprehensive analysis of AI’s impact on language acquisition. The study examines AI’s role in scaffolding language acquisition, analyzing how teacher facilitation fosters responsible and reflective AI engagement. Through classroom observations and practical implementations, findings reveal the delicate balance between leveraging AI for pedagogical innovation and upholding ethical teaching practices. The study proposes strategies for educators, policymakers, and curriculum designers to ethically integrate AI-driven tools in language instruction, ensuring that technological advancements support rather than undermine learner autonomy and academic rigor. By bridging innovation and integrity, this research contributes to the ongoing discourse on sustainable and ethical AI adoption in education.
keywords: ChatGPT, critical-thinking, ethical, real-world, TBLT