| Multimodal data as a means to understand the learning experience MN Giannakos, K Sharma, IO Pappas, V Kostakos, E Velloso International Journal of Information Management 48, 108-119, 2019 | 220 | 2019 |
| Multimodal data capabilities for learning: What can multimodal data tell us about learning? K Sharma, M Giannakos British Journal of Educational Technology 51 (5), 1450-1484, 2020 | 209 | 2020 |
| Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors LP Prieto, K Sharma, P Dillenbourg, M Jesús Proceedings of the sixth international conference on learning analytics …, 2016 | 175 | 2016 |
| Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data LP Prieto, K Sharma, Ł Kidzinski, MJ Rodríguez‐Triana, P Dillenbourg Journal of computer assisted learning 34 (2), 193-203, 2018 | 138 | 2018 |
| Eye-tracking and artificial intelligence to enhance motivation and learning K Sharma, M Giannakos, P Dillenbourg Smart Learning Environments 7, 1-19, 2020 | 135 | 2020 |
| Building pipelines for educational data using AI and multimodal analytics: A “grey‐box” approach K Sharma, Z Papamitsiou, M Giannakos British Journal of Educational Technology 50 (6), 3004-3031, 2019 | 133 | 2019 |
| Leveraging mobile eye-trackers to capture joint visual attention in co-located collaborative learning groups B Schneider, K Sharma, S Cuendet, G Zufferey, P Dillenbourg, R Pea International Journal of Computer-Supported Collaborative Learning 13, 241-261, 2018 | 110 | 2018 |
| Coding activities for children: Coupling eye-tracking with qualitative data to investigate gender differences S Papavlasopoulou, K Sharma, MN Giannakos Computers in Human Behavior 105, 105939, 2020 | 97 | 2020 |
| How do you feel about learning to code? Investigating the effect of children’s attitudes towards coding using eye-tracking S Papavlasopoulou, K Sharma, MN Giannakos International Journal of Child-Computer Interaction 17, 50-60, 2018 | 86 | 2018 |
| Temporal analysis of multimodal data to predict collaborative learning outcomes JK Olsen, K Sharma, N Rummel, V Aleven British Journal of Educational Technology 51 (5), 1527-1547, 2020 | 83 | 2020 |
| Coding games and robots to enhance computational thinking: How collaboration and engagement moderate children’s attitudes? K Sharma, S Papavlasopoulou, M Giannakos International Journal of Child-Computer Interaction 21, 65-76, 2019 | 81 | 2019 |
| Exploring students' cognitive and affective states during problem solving through multimodal data: Lessons learned from a programming activity K Mangaroska, K Sharma, D Gašević, M Giannakos Journal of Computer Assisted Learning 38 (1), 40-59, 2022 | 79 | 2022 |
| Fitbit for learning: Towards capturing the learning experience using wearable sensing MN Giannakos, K Sharma, S Papavlasopoulou, IO Pappas, V Kostakos International Journal of Human-Computer Studies 136, 102384, 2020 | 76 | 2020 |
| Orchestration load indicators and patterns: In-the-wild studies using mobile eye-tracking LP Prieto, K Sharma, Ł Kidzinski, P Dillenbourg IEEE Transactions on Learning Technologies 11 (2), 216-229, 2017 | 75 | 2017 |
| Using mobile eye-trackers to unpack the perceptual benefits of a tangible user interface for collaborative learning B Schneider, K Sharma, S Cuendet, G Zufferey, P Dillenbourg, R Pea ACM Transactions on Computer-Human Interaction (TOCHI) 23 (6), 1-23, 2016 | 73 | 2016 |
| Predicting learners' effortful behaviour in adaptive assessment using multimodal data K Sharma, Z Papamitsiou, JK Olsen, M Giannakos Proceedings of the tenth international conference on learning analytics …, 2020 | 72 | 2020 |
| Utilizing multimodal data through fsQCA to explain engagement in adaptive learning Z Papamitsiou, IO Pappas, K Sharma, MN Giannakos IEEE Transactions on Learning Technologies 13 (4), 689-703, 2020 | 70 | 2020 |
| Children’s play and problem-solving in motion-based learning technologies using a multi-modal mixed methods approach S Lee-Cultura, K Sharma, M Giannakos International Journal of Child-Computer Interaction 31, 100355, 2022 | 69 | 2022 |
| How to quantify student’s regularity? MS Boroujeni, K Sharma, Ł Kidziński, L Lucignano, P Dillenbourg Adaptive and Adaptable Learning: 11th European Conference on Technology …, 2016 | 66 | 2016 |
| A gaze-based learning analytics model: in-video visual feedback to improve learner's attention in MOOCs K Sharma, HS Alavi, P Jermann, P Dillenbourg Proceedings of the sixth international conference on learning analytics …, 2016 | 65 | 2016 |
Michail N. GiannakosNorwegian University of Science and Technology / University of AgderE-mail megerősítve itt: idi.ntnu.no