Biography
Dr. Wassila Tebaa is a lecturer in the Department of English language at High Teacher Training School of Bouzareah, Algeria with over 14 years of experience in English language teaching and teacher education. Her research interests include applied linguistics, artificial intelligence and educational technology, vocabulary development, materials design, development and evaluation, and digital literacy in EFL contexts. Her current research examines the role of AI-generated feedback tools in enhancing EFL pre-service teachers’ academic and dissertation writing. She has published research on productive vocabulary assessment. Besides her research, she has contributed to the renewal of English language teacher education programs and has participated in curriculum development initiatives and professional development workshops for pre-service teachers. She has also presented her research at national academic study days and conferences on EFL teacher education, competency-based assessment, AI literacy, and AI-assisted formative feedback. Through her work, she seeks to promote innovative approaches to English language teaching, learning, and assessment in higher education within the competency-based and artificial intelligence paradigms.
Conference contributions 1
THE USE OF AUTOMATED FEEDBACK TOOLS IN EFL PRE-SERVICE TEACHERS’ DISSERTATION WRITING
PRACTICES, PERCEPTIONS AND CHALLENGES. A Case Study of High Teacher Training School of Bouzareah, Algiers
Currently, Artificial Intelligence (AI) and automated feedback tools are increasingly gaining significant attention, particularly in higher education EFL (English as a Foreign Language) academic writing. Despite integrating these tools into learning, little research has been conducted to examine how pre-service teachers engage with these tools during high-stakes academic writing tasks such as dissertations. This study, therefore, explores the use of automated feedback tools in EFL pre-service teachers’ dissertation writing, focusing on their actual practices, perceptions, and the challenges they face. To meet this objective, the study adopted a mixed-methods design, whereby a questionnaire was administered to 52 EFL pre-service teachers to collect both quantitative and qualitative data. The questionnaire examined patterns of use, perceived usefulness, and difficulties associated with automated feedback tools. The study indicated that automated feedback tools were inevitable in pre-service teachers’ dissertation writing, and tools such as Grammarly, plagiarism checker, and AI writing assistant were widely adopted for drafting, editing, and proofreading. The study also disclosed that these tools provided substantial assistance in enhancing writing quality and language accuracy, although participants raised some concerns related to unreliable feedback and ethical issues, including plagiarism, excessive reliance, and responsible AI use. The findings contribute to a deeper understanding of digital writing practices in EFL teacher education and offer a balanced approach integrating automated feedback tools alongside traditional supervisors’ feedback in dissertation writing, maintaining clear ethical boundaries to preserve academic integrity.