Bakgrunn og aktiviteter
Vitenskapelig, faglig og kunstnerisk arbeid
- (2021) Sensing-Based Analytics in Education: The Rise of Multimodal Data Enabled Learning Systems. IT Professional Magazine. vol. 23 (6).
- (2021) Children's play and problem-solving in motion-based learning technologies using a multi-modal mixed methods approach. International Journal of Child-Computer Interaction.
- (2021) Exploring students' cognitive and affective states during problem solving through multimodal data: Lessons learned from a programming activity. Journal of Computer Assisted Learning.
- (2021) Investigating gaze interaction to support children’s gameplay. International Journal of Child-Computer Interaction.
- (2021) Information flow and cognition affect each other: Evidence from digital learning. International Journal of Human-Computer Studies. vol. 146.
- (2020) Utilizing multimodal data through fsQCA to explain engagement in adaptive learning. IEEE Transactions on Learning Technologies. vol. 13 (4).
- (2020) Characterizing Learners' Engagement in MOOCs: An Observational Case Study Using the NoteMyProgress Tool for Supporting Self-Regulation. IEEE Transactions on Learning Technologies. vol. 13 (4).
- (2020) Monitoring Children’s Learning Through Wearable Eye-Tracking: The Case of a Making-Based Coding Activity. IEEE pervasive computing. vol. 19 (1).
- (2020) Fitbit for learning: Towards capturing the learning experience using wearable sensing. International Journal of Human-Computer Studies. vol. 136.
- (2020) Using Multimodal Learning Analytics to Explore how Children Experience Educational Motion-Based Touchless Games. CEUR Workshop Proceedings. vol. 2610.
- (2020) Motion-Based Educational Games: Using Multi-Modal Data to Predict Player’s Performance. IEEE Conference on Computatonal Intelligence and Games, CIG.
- (2020) Multimodal learning analytics to inform learning design: Lessons learned from computing education. Journal of Learning Analytics. vol. 7 (3).
- (2020) Seeking Information on Social Commerce: An Examination of the Impact of User- and Marketer-generated Content Through an Eye-tracking Study. Information Systems Frontiers.
- (2020) Temporal analysis of multimodal data to predict collaborative learning outcomes. British Journal of Educational Technology (BJET). vol. 51 (5).
- (2020) How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data. Lecture Notes in Computer Science (LNCS). vol. 12067.
- (2020) Multimodal data capabilities for learning: What can multimodal data tell us about learning?. British Journal of Educational Technology (BJET). vol. 51 (5).
- (2020) Eye-tracking and artificial intelligence to enhance motivation and learning. Smart Learning Environments.
- (2020) Utilizing interactive surfaces to enhance learning, collaboration and engagement: Insights from learners’ gaze and speech. Sensors. vol. 20:1964 (7).
- (2020) Assessing cognitive performance using physiological and facial features: Generalizing across contexts. PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
- (2020) Measuring causality between collaborative and individual gaze metrics for collaborative problem‐solving with intelligent tutoring systems. Journal of Computer Assisted Learning.