ISeGov Research Group

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eJustice

The team investigates the ways in which digital technologies can enhance teaching, learning, and assessment across formal, informal, and lifelong education. Our work in eLearning focuses on the design and evaluation of digital learning environments, pedagogical frameworks, and data-driven approaches to improve learner outcomes.
We are particularly interested in problem-based learning, learning analytics, and adaptive learning systems that tailor content and feedback to individual learner needs. Our research is grounded in both technical development and pedagogical theory, with applications ranging from higher education to public administration training.

Key Research Topics:

Selected Projects:

Beyond these projects, we are expanding our research to include AI-supported personalized learning, data-driven curriculum design, and the ethical implications of learning analytics. We are particularly interested in how generative technologies (e.g., large language models) can be responsibly integrated into teaching and assessment. Additional areas of interest include adaptive learning systems, competency-based education, and digital credentials such as micro-credentials and blockchain-based certification. We also explore how emerging pedagogies like immersive learning (AR/VR) and game-based learning can enhance student engagement and support diverse learning needs.

Technology-enhanced Problem-based learning

Technology-enhanced Problem-based Learning (PBL) integrates digital tools and resources into an instructional approach centered on solving authentic, real-world problems. In this model, students actively engage in learning by working collaboratively to investigate and find solutions, with technology facilitating research, communication, and the creation of diverse products. The use of various technologies, such as Web 2.0 tools, online databases, and simulation software, can support different stages of the PBL process, from problem analysis to presenting solutions. This approach aims to develop critical thinking, problem-solving skills, and self-directed learning, preparing students for complex challenges. Studies suggest that integrating technology into PBL can foster deeper learning, engagement, and the development of 21st-century skills.

Learning Analytics

Learning analytics involves the measurement, collection, analysis, and reporting of data about learners and their learning contexts. The primary purpose is to understand and optimize learning and the environments in which it occurs. By tracking student interactions with online learning systems, such as Learning Management Systems (LMS) or social media, educators can gain insights into engagement, progress, and potential difficulties. This data-driven approach can be used to personalize learning experiences, identify at-risk students, improve teaching strategies, and inform curriculum development. Ultimately, learning analytics aims to enhance learning outcomes and the overall effectiveness of educational programs.

Learning environments

A learning environment encompasses the complete physical, social, psychological, and cultural context in which learning takes place. It includes not only the physical setting, like a classroom or online platform, but also the educational approach, the interactions between students and instructors, and the overall ethos and culture of the learning space. Effective learning environments are designed to be nurturing, well-organized, and supportive of diverse learners, offering opportunities for choice, exploration, and experimentation. Factors such as classroom management, a sense of community, and the integration of home cultures can significantly impact student engagement and success. The design of learning spaces, including the flexible use of furniture and technology, plays a role in supporting various teaching and learning activities to meet individual student needs.