Browsing by Author "Ghania Hadj Kouider, Dalal Arbia Bouhamida"

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    Designing an Alpoweree system fon needs Analysis and personalized content generation in ESP course
    (جامعة غرداية, 2026) Ghania Hadj Kouider, Dalal Arbia Bouhamida
    English for Specific Purposes (ESP) has become strategically important in Algeria due to recent changes adopting English as a language of instruction in schools. However, one of the main difficulties faced by researchers is the lack of intelligent and contextualized software applications that can connect the language needs of a specific field to relevant materials. The aim of this thesis is to design, develop, and test TALEB-ESP, an artificial intelligence system for ESP instruction. Specifically, it seeks to solve a common problem in ESP teaching among first-year university students: the inability of instructors to identify learners” ESP needs and develop appropriate materials. As a possible solution, TALEB-ESP, an AI-assisted platform for needs analysis and personalized ESP material development, is proposed and investigated. The study employed a quasi-experimental mixed-methods design, involving a purposive initial sample of 80 first-year English for Specific Purposes (ESP) students, 75 of whom met the inclusion criteria. These students were divided into an experimental group and a control group. They participated in a six-week classroom experiment. The experimental group used TALEB-ESP to identify ESP needs and generate customized learning content. To measure the impact, students” reading, technical vocabulary, and professional writing skills were tested before and after the experiment using pre-tests and post-tests. Teacher evaluation and learner assessment were also used. The results showed that participants who studied with the AI-enhanced platform improved their language proficiency much more than those in the control group (F(1, 72) = 68.47, p < .001). Moreover, the AI-based needs analysis was highly consistent with expert assessment, meaning that using AI in ESP learning provides accurate data about learners” needs. Additionally, both teachers and students expressed very positive attitudes towards the usefulness and adaptability of the AI-generated materials. The conclusion is that the hypothesis is confirmed: artificial intelligence technology can help create more adaptive, learner-oriented, and contextualized ESP learning activities at Algerian universities. The dissertation also offers insights into the consequences of using AI in ESP learning for educators, curriculum developers, and future innovations in Algerian higher education. Keywords: English for Specific Purposes (ESP), Artificial Intelligence in Education, Needs Analysis, Personalized Learning, AI-Assisted Content Generation, Language Learning Technologies, Algerian Higher Education.