The Research Group on AI-Assisted Learning and Computer Science Education was established at Çukurova University to conduct interdisciplinary research at the intersection of artificial intelligence, educational technology, and computer science education. Its areas of work are programming education, AI-assisted feedback, large language models adapted for pedagogical use, digital measurement and assessment, learning analytics, microlearning, and the integration of emerging computing paradigms into curricula.

The group's approach is to develop technical systems and educational research together rather than in sequence. The aim is to produce solutions for teaching and learning that are implementable, evaluable, and grounded in evidence — not to demonstrate that a tool works, but to establish under what conditions and to what extent it does. To that end the group draws on design science research, educational design research, experimental and quasi-experimental designs, expert review, the Delphi method, learning analytics, instrument development, and comparative evaluation of large language models.

The group's work reaches back to 2008. The projects listed here follow successive waves of technology integration in vocational higher education: EU-funded distance and e-learning projects, gamified mobile learning applications, augmented reality, and microlearning studies. The current focus carries the same question into the age of AI: does a new technology actually improve learning, and how would we know?

Ongoing work includes a university-funded (BAP) research project on localizing an open-source large language model through pedagogically oriented fine-tuning for programming instruction, and examining its effectiveness.

The group seeks joint research with universities, vocational schools, faculty members, graduate students, and other stakeholders; it aims to run national and international projects and to produce scientific publications, open research outputs, and educational technology prototypes. Proposals for collaboration on multi-centre data collection, expert panels, and joint publication are welcome.