Speakers
Description
This research investigates how EFL Juniors at HUFLIT perceive academic integrity when utilizing AI-supported writing scaffolds during their Introduction to Research Methods course (Project 2). The integration of generative artificial intelligence tools into institutions of higher education presents a dichotomy between their potential pedagogical advantages and the need to uphold authentic authorship. This study utilizes a concurrent mixed-methods design, incorporating quantitative data from 176 EFL Juniors via structured questionnaires, alongside qualitative insights from 7 EFL Juniors’ reflective pieces and open-ended responses from semi-structured interviews. Using quantitative methods, the collected numerical data were analyzed to identify clear patterns in students' perceptions of AI-assisted writing and their correlations with academic integrity. Qualitative data were examined through thematic analysis to uncover recurring perceptions, concerns, and usage practices. The evidence indicates that EFL Juniors commonly regard AI as an advantageous scaffolding tool, facilitating processes such as ideation, structural organization, and lexical enrichment, and consequently augmenting their overall self-assurance in written composition. However, the risks of over-reliance on AI and its corresponding impact on individuals' writing abilities still need careful consideration. This investigation advances the field of EFL research on the processes students use to manage the application of AI in their academic writing. Furthermore, this research offers practical insights into integrating AI functionalities into pedagogical approaches to academic writing while maintaining principles of academic integrity.
Keywords: academic integrity, AI-supported writing, EFL Juniors, mixed-methods design, pedagogical approaches
