Research Topics

Research for tomorrow’s smart learning and working environments

Research-portfolio

At the intersection of computer science and social science, we conduct applied research into intelligent data-intensive systems and their application in social media, technology-enhanced learning, and knowledge management domains. We innovate scalable, interactive, and transparent tools that augment human capabilities to interact with and make sense of massive datasets to solve real world problems. Topics currently being researched at our group include:

Human-Centered Learning Analytics

Developing human-centered learning analytics technologies and applications that emphasize the human factors in learning analytics and truly meets the user's needs. Human-centered learning analytics (HCLA) refers to (1) the systematic user involvement in the design, development, deployment, and evaluation of learning analytics and (2) blending personalization and learning analytics to design and implement smart learning environments capable to continuously analyze and support the performance of learners, and offer them learning experiences in context.

  • Learning analytics & HCI
  • Privacy-preserving data collection and management
  • User modeling and personalization
  • Analytics-enhanced personalized learning
  • Open learning analytics
  • Educational data mining
  • Assessment and feedback
  • Learning analytics at the workplace

Social Media Modeling and Analysis

Mining social media to extract relevant semantic information (e.g. topics, interests, context, relations, emotions) and combining human know-how and machine analytics to gain new insights into social media data.

  • Interest and context modeling
  • Human-Data Interaction
  • Information visualization and visual analytics
  • Interactive recommender systems
  • Explainable machine learning / AI

Check out our research projects and publications for more information about our work.

Our research is part of the research profile Human-Centered Cyber-Physical Systems of the Faculty of Engineering.