Transforming the Professional Development of Computer Science Teachers through Intelligent Technologies: Focus on Digital Competencies and Educational Outcomes

2025

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.18178/ijiet.2025.15.9.2396
Data confidence 70 medium
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Abstract

This study examines the integration of chatbot development methodologies in computer science education, focusing on modern teaching techniques and practical AI-based learning. It evaluates the impact of structured chatbot development on student motivation and programming skills. A pedagogical experiment was conducted with 180 undergraduate students at L.N. Gumilyov Eurasian National University, divided into an experimental group following the Chatbot Development Life Cycle (CDLC) methodology and a control group using traditional learning methods. The experimental group received a tailored curriculum, structured syllabus, and hands-on chatbot exercises to connect theory with practice. In addition to student-focused outcomes, the study also addresses the transformation of professional development for computer science teachers using intelligent technologies. By incorporating AI-driven learning environments, the experiment aimed to enhance not only students’ technical skills but also the digital competencies of participating instructors. Teachers involved in the experimental group underwent parallel training on AI integration, chatbot development supervision, and digital assessment tools, fostering continuous professional growth. Findings show that CDLC-based training significantly enhanced student motivation, engagement, and technical proficiency, particularly in debugging, deployment, and chatbot optimization. Furthermore, the initiative contributed to transforming educators’ professional development by equipping them with advanced digital skills and pedagogical strategies aligned with intelligent technology integration. Teachers demonstrated improved confidence in using AI tools, designing interactive lessons, and achieving better educational outcomes in technology-enhanced learning environments.