№ 2 (71) 2025
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Browsing № 2 (71) 2025 by Subject "Artificial Intelligence"
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Item Open Access EFL TEACHERS’ ATTITUDES TOWARDS THE USE OF AI GENERATED LESSON PLANS IN KAZAKHSTAN(SDU University, 2025) Alina Fazilova; Aizhan KayipProlific advancements in the sphere of Artificial Intelligence in Education and Artificial Intelligence, in general, beg the questions of how these technologies could be implemented in the English as a Foreign Language sphere and what English as a Foreign Language teachers’ attitudes towards Artificial Intelligence-generated lesson plans are. In this research paper, the attitudes of Kazakhstani secondary school English as a Foreign Language teachers towards the use of Artificial Intelligence-generated lesson plans have been explored. Through analyzing responses from an online survey, the study identifies several prominent themes that reflect the overall attitudes of teachers towards Artificial Intelligence-generated lesson planning. The study employed qualitative research design and involved 27 participants. Their attitudes were collected via an open-ended questionnaire and analyzed with thematic analysis. The results indicate that AI-generated lesson plans can have a positive impact on student learning outcomes, with the guidance and adjustments made by teachers. However, concerns about automation bias and the lack of personalization in the plans are also identified. The benefits of lesson planning generated by Artificial Intelligence include efficiency, customization, and innovative ideas, while drawbacks include inflexibility in unanticipated situations and a lack of specificity in students' needs. The study concludes that teachers express overall positive attitudes towards the use of Artificial Intelligence-generated lesson plans. According to the results, English as a Foreign Language teachers believe that they offer a range of benefits for teachers and can potentially enhance student learning outcomes when used in conjunction with teacher modifications and adjustments.Item Open Access FORMATIVE ASSESSMENT IN KAZAKHSTAN’S ENGLISH LANGUAGE CLASSROOMS: A NARRATIVE REVIEW OF CURRENT PRACTICES AND THE ROLE OF AI TOOLS(SDU University, 2025) Aidos Myrzabek; Gaukhar Yersultanova; Medet JandildinovFormative assessment (FA) has emerged as a critical component of effective teaching and learning, providing ongoing feedback that guides both teachers and students in improving educational outcomes. This narrative literature review examines the implementation of formative assessment in Kazakhstan’s English language classrooms and explores how artificial intelligence (AI) tools are enhancing and could further enhance these practices. The review synthesizes international and local research on FA – defining its key concepts, components, benefits, and challenges – within the context of Kazakhstan’s recent education reforms that mandate a criteria-based (formative) assessment system. It also discusses current applications of AI (such as adaptive learning platforms, natural language processing for feedback, and AI-driven peer/self-assessment tools) in education, and considers potential future uses of AI to support teachers and learners in formative assessment. The findings indicate that while formative assessment is valued for improving student engagement and achievement, Kazakhstani teachers face challenges in its implementation, including large classes and shifts in ingrained grading practices. AI technologies offer promising solutions to personalize feedback, automate routine assessment tasks, and inform data-driven instruction, albeit with the need for teacher training and careful integration. The review concludes with implications for educators and policymakers in Kazakhstan, emphasizing that blending proven formative assessment strategies with AI support can foster more responsive and effective English language teaching.