ABOUT THE GROUP
The Research Group for Advanced Teaching Methods in Technical Sciences (IG01) was established in 2018 within the Department of Core Courses at the Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, Croatia. The group brings together researchers and experts from mathematics, physics, and English and German language education, forming an interdisciplinary team dedicated to advancing innovation in higher STEM education.
The group’s main objective is to develop, implement, and scientifically evaluate digitally supported and student-centred teaching approaches that address contemporary challenges in engineering education. Its work focuses on integrating artificial intelligence, digital tools, experimental methodologies, and advanced programming practices into the teaching and learning process. The group aims to strengthen students’ analytical thinking, problem-solving abilities, digital competencies, and professional communication skills required in international STEM environments.
The group’s activities focus on developing digitally enhanced approaches to teaching technical English, researching modern digital tools and experimental methods in physics education, and designing specialised educational models for advanced programmers. Across these areas, it explores innovative teaching strategies, artificial intelligence applications, contemporary experimental practices, and advanced algorithmic training models. Using mixed research methodologies, including diagnostic testing, surveys, qualitative feedback, statistical modelling, and machine learning–based analysis, the group systematically evaluates learning outcomes, student motivation, conceptual understanding, and teaching effectiveness to promote evidence-based innovation in higher STEM education.
Furthermore, IG01 aligns its activities with national and European digital education strategies and contributes to raising scientific excellence, fostering interdisciplinarity, and supporting the digital transformation of higher engineering education.
KEY RESEARCH AREAS
- Cutting-edge technologies in teaching English for Specific Purposes (ESP)
- Educational research in the field of physics and other core engineering fields
- Advanced programming
- Soft materials in the fabrication of microstructured components
- Diophantine sets
RESEARCH AREAS
The IG01 group focuses its research on the application of cutting-edge digital technologies and artificial intelligence in English for Specific Purposes (ESP), integrating technical vocabulary, professional communication, and STEM content through project-based, task-based, and AI-supported learning. The group conducts educational research in physics and core engineering disciplines, examining conceptual understanding, experimental learning, and the impact of simulations, virtual laboratories, sensors, and digital measurement systems. A dedicated strand develops specialised educational models for advanced and competitive programmers, combining algorithmic thinking, graph theory, number theory, and optimisation techniques. Additional research includes machine learning models for evaluating teaching quality, application of soft materials (liquid crystals, elastomers) in microstructured optical components and adaptive sensors, and theoretical investigations of Diophantine sets. Across all areas, IG01 applies mixed quantitative and qualitative research methods to ensure evidence-based innovation in higher STEM education.
PROFESSIONAL EXPERTISE
The IG01 group possesses strong professional expertise in STEM education research, English for Specific Purposes (ESP), physics education, advanced programming, and applied mathematics. It focuses on developing and assessing innovative, digitally supported teaching approaches that incorporate artificial intelligence, machine learning, simulations, and modern experimental technologies into higher engineering education. Members have solid competencies in statistical analysis, data modelling, algorithm design, competitive programming, and the creation of adaptive digital learning materials. The team has extensive experience in interdisciplinary collaboration, active participation in research projects, STEM outreach activities, and promoting scientific literacy among school and university students.
KEY PROFESSIONAL EXPERTISE
- Design and evaluation of innovative STEM teaching methods (project-based, task-based, inquiry-based, flipped classroom, gamification)
- Application of digital technologies and artificial intelligence in education, including adaptive learning tools
- Machine learning modelling and statistical analysis for evaluation of learning outcomes and teaching effectiveness
- Development of interactive ESP (English for Specific Purposes) materials integrating technical content and professional communication
- Implementation of digital and sensor-based experimental systems in physics education (simulations, Arduino, data acquisition tools)
- Advanced algorithm design and competitive programming training, including graph theory, number theory, and optimisation techniques
