Biography
Assistant Professor Tilen Smajla, Ph.D., is a Slovenian language educator and researcher with over twenty years of teaching experience across primary, secondary, vocational, and university education, including Slovenia’s Italian minority school system. He graduated in English and German studies from the University of Ljubljana in 2002, completed a specialisation in educational management in 2005 from The Faculty of Management, University of Primorsko, Koper, and earned his doctorate at the University of Primorsko, Koper, in 2019. His career combines classroom teaching with research into second language acquisition, early foreign language learning, content and language integrated learning, and digitally supported education. He has contributed to the University of Maribor’s research on artificial intelligence in language education and the international ELITE-AI project. His publications connect learners’ and teachers’ perspectives with practical questions about language pedagogy, distance learning, digital competence, and responsible AI integration. Affiliated with the University of Maribor, he investigates students’ experiences of online language learning and the application of artificial intelligence in specialised language courses.
Conference contributions 1
BEYOND ACCESS:
How learner agency and AI integration shape motivation, interaction, and accuracy in LSP language learning
Through a survey of 513 university students in a criminal justice and security LSP course, this study investigates the effects of LLMs on language learning and instruction. Four hypotheses on motivation, interaction quality, critical assessment, and integration are tested using non-parametric techniques. Compared to peers who perceive AI as neutral or harmful, students who believe it eases learning report far greater enthusiasm and active involvement (p < 0.001). Interaction quality, prompt effectiveness, and comprehension of AI output are considerably greater among students using AI proactively and autonomously rather than responding to teacher-directed prompts (p < 0.001). No discernible difference emerged in self-reported grammatical correctness between those who critically check AI replies and those who accept them without question (p = 0.72), indicating verification alone does not ensure increased accuracy. Deeper AI integration shows a favorable correlation with overall satisfaction (rho = 0.529) and perceived efficacy (rho = 0.543), both significant at p < 0.001. These results suggest learner satisfaction and engagement in AI-supported language learning are driven by learner agency and perceived utility rather than mere access to AI technologies. Proactive, self-directed AI use may improve interaction quality and motivation more effectively than teacher-controlled, prescriptive adoption. The findings add empirical support to discussions on the pedagogical significance of LLMs while cautioning that critical assessment skills may need pairing with explicit accuracy-focused teaching to produce measurable grammatical gains. Implications for task design, evaluation, and teacher preparation in LLM-integrated courses are examined, offering curriculum designers recommendations for balancing autonomy with pedagogical scaffolding.