Background and activities

My background is in the area of Human-Computer Interaction and Collaborative/cooperative learning. In particular, my doctoral work was in the area of using multimodal data (EEG, eye-tracking, facial expressions, audio, dialogues, blood pressure, skin conductance, heart rate) to explain the differences between and predict, experts and novice groups; good and poor students; functional and non-functional groups. The main context for the application of my research has been education. My research interests are primarily in the area of Applied Machine Learning, Artificial Intelligence, and Human-Computer Interaction (HCI) with a heavy emphasis on groups’ behavior and physiological data such as eye-tracking, EEG, facial expressions (theoretical and practical methods in digital interaction). I seek to understand relations between users’ data (EEG, eye-tracking, system log data, users’ actions) and the profile of the user (expertise, motivation, strategy, performance) based on empirical experimentation (controlled experiments) and mixed methods analysis (utilizing a multitude of digital technologies). The knowledge gained from these studies is then used to provide feedback to the group or adapt to the needs of the group in a proactive manner. For this effort, in my studies, I have combined eye-tracking and users’ actions to provide more comprehensive results through data science, statistics, and machine learning practices. 

After finishing my doctoral studies in 2015, I started working on developing methods based on Extreme Values Theory (EVT), a methodological space to compute features from abnormalities in data emerging out of collaborative work. EVT is well suited for big data time series. The results show an improvement over contemporary feature extraction methods in terms of their prediction capabilities. During the same period, I have expanded my application area beyond collaborative and educational technologies and have conducted studies in the context of e-commerce, information systems, and Entertainment Computing.

For details please visit my Scholar page

Journal Articles

Sharma, K., Giannakos, M., & Dillenbourg, P. (2020). Eye-tracking and artificial intelligence to enhance motivation and learning. Smart Learning Environments7, 1-19.

Giannakos, M. N., Sharma, K., Papavlasopoulou, S., Pappas, I. O., & Kostakos, V. (2020). Fitbit for learning: Towards capturing the learning experience using wearable sensing. International Journal of Human-Computer Studies136, 102384.

Papavlasopoulou, S., Sharma, K., & Giannakos, M. N. (2020). Coding activities for children: Coupling eye-tracking with qualitative data to investigate gender differences. Computers in Human Behavior105, 105939.

Giannakos, M. N., Papavlasopoulou, S., & Sharma, K. (2020). Monitoring Children's Learning Through Wearable Eye-Tracking: The Case of a Making-Based Coding Activity. IEEE Pervasive Computing19(1), 10-21.

Sharma, K., Leftheriotis, I., & Giannakos, M. (2020). Utilizing Interactive Surfaces to Enhance Learning, Collaboration and Engagement: Insights from Learners’ Gaze and Speech. Sensors20(7), 1964.

Sharma, K., Papamitsiou, Z., & Giannakos, M. (2019). Building pipelines for educational data using AI and multimodal analytics: A “grey‐box” approach. British Journal of Educational Technology50(6), 3004-3031.

Giannakos, M. N., Sharma, K., Pappas, I. O., Kostakos, V., & Velloso, E. (2019). Multimodal data as a means to understand the learning experience. International Journal of Information Management48, 108-119.

Sharma, K., Papavlasopoulou, S., & Giannakos, M. (2019). Coding games and robots to enhance computational thinking: How collaboration and engagement moderate children’s attitudes?. International Journal of Child-Computer Interaction21, 65-76.

Asselborn, T., Sharma, K., Johal, W., & Dillenbourg, P. (2019). Bridging Multilevel Time Scales in HRI: An Analysis Framework. ACM Transactions on Human-Robot Interaction (THRI)8(3), 1-24.

Gomez, J., Jaccheri, L., Maragoudakis, M., & Sharma, K. (2019). Digital storytelling for good with Tappetina game. Entertainment Computing30, 100297.

Sharma, K., Chavez-Demoulin, V., & Dillenbourg, P. (2018). Nonstationary modelling of tail dependence of two subjects’ concentrationThe Annals of Applied Statistics12(2), 1293-1311.

Papavlasopoulou, S., Sharma, K., & Giannakos, M. N. (2018). How do you feel about learning to code? Investigating the effect of children’s attitudes towards coding using eye-tracking. International Journal of Child-Computer Interaction.

Prieto, L. P., Sharma, K., Kidzinski, Ł., Rodríguez‐Triana, M. J., & Dillenbourg, P. (2018). Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data. Journal of computer assisted learning34(2), 193-203.

Prieto, L. P., Sharma, K., Kidzinski, Ł., & Dillenbourg, P. (2018). Orchestration load indicators and patterns: In-the-wild studies using mobile eye-tracking. IEEE Transactions on Learning Technologies11(2), 216-229.

Schneider, B., Sharma, K., Cuendet, S., Zufferey, G., Dillenbourg, P., & Pea, R. (2018). Leveraging mobile eye-trackers to capture joint visual attention in co-located collaborative learning groups. International Journal of Computer-Supported Collaborative Learning13(3), 241-261.

Mangaroska, K., Sharma, K., Giannakos, M., Træteberga, H., & Dillenbourg, P. (2018). Gaze-Driven Design Insights to Amplify Debugging Skills: A Learner-Centred Analysis Approach. Journal of Learning Analytics5(3), 98-119.

Sharma, K., Chavez-Demoulin, V., & Dillenbourg, P. (2018). Nonstationary modelling of tail dependence of two subjects’ concentration. The Annals of Applied Statistics12(2), 1293-1311.

Sharma, K., Chavez-Demoulin, V., & Dillenbourg, P. (2017). An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-tracking Data. Journal of Learning Analytics, 4(3), 140- 164. 

Schneider, B., Sharma, K., Cuendet, S., Zufferey, G., Dillenbourg, P., & Pea, R. (2016). Using mobile eye-trackers to unpack the perceptual benefits of a tangible user interface for collaborative learning. ACM Transactions on Computer-Human Interaction (TOCHI), 23(6), 39.

Sharma, K., Caballero, D., Verma, H., Jermann, P., & Dillenbourg, P. (2015). Shaping learners’ attention in massive open online courses. Revue internationale des technologies en pédagogie universitaire/International Journal of Technologies in Higher Education12(1-2), 52-61.

Conference Papers

Sharma, K., Papamitsiou, Z., Olsen, J. K., & Giannakos, M. (2020, March). Predicting learners' effortful behaviour in adaptive assessment using multimodal data. In Proceedings of the Tenth International Conference on Learning Analytics & Knowledge (pp. 480-489).

Pappas, I. O., Sharma, K., Mikalef, P., & Giannakos, M. N. (2020, April). How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data. In Conference on e-Business, e-Services and e-Society (pp. 429-440). Springer, Cham.

Sharma, K., Papavlasopoulou, S., & Giannakos, M. (2019, June). Joint emotional state of children and perceived collaborative experience in coding activities. In Proceedings of the 18th ACM International Conference on Interaction Design and Children (pp. 133-145).

Sharma, K., Dillenbourg, P., & Giannakos, M. (2019, July). Stimuli-Based Gaze Analytics to Enhance Motivation and Learning in MOOCs. In 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT) (Vol. 2161, pp. 199-203). IEEE.

Sharma, K., Papamitsiou, Z., & Giannakos, M. N. (2019, September). Modelling Learners’ Behaviour: A Novel Approach Using GARCH with Multimodal Data. In European Conference on Technology Enhanced Learning (pp. 450-465). Springer, Cham.

Sharma, K., & Olsen, J. (2019). An Alternate Statistical Lens to Look at Collaboration Data: Extreme Value Theory. In Computer-Supported Collaborative Learning. 

Sharma, K., Pappas, I., Papavlasopoulou, S., & Giannakos, M. (2019). Towards automatic and pervasive physiological sensing of collaborative learning. In Computer-Supported Collaborative Learning. 

Giannakos, M. N., Sharma, K., & Niforatos, E. (2019, September). Exploring EEG signals during the different phases of game-player interaction. In 2019 11th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games) (pp. 1-8). IEEE.

Pérez-Sanagustín, M., Sharma, K., Pérez-Álvarez, R., Maldonado-Mahauad, J., & Broisin, J. (2019, September). Analyzing learners’ behavior beyond the MOOC: An exploratory study. In European Conference on Technology Enhanced Learning (pp. 40-54). Springer, Cham.

Lorås, M., Trætteberg, H., & Sharma, K. (2019). Investigating students’ journey through a computer science program using exam data: three new approaches.

Sharma, K., Olsen, J. K., Aleven, V., & Rummel, N. (2018, September). Exploring Causality Within Collaborative Problem Solving Using Eye-Tracking. In European Conference on Technology Enhanced Learning (pp. 412-426). Springer, Cham.

Sharma, K., Papavlasopoulou, S., Giannakos, M., & Jaccheri, L. (2018, June). Kid Coding Games and Artistic Robots: Attitudes and Gaze Behavior. In Proceedings of the Conference on Creativity and Making in Education (pp. 64-71). ACM.

Sharma, K., Mangaroska, K., Trætteberg, H., Lee-Cultura, S., & Giannakos, M. (2018, September). Evidence for programming strategies in university coding exercises. In European Conference on Technology Enhanced Learning (pp. 326-339). Springer, Cham.

Sharma, K. & Jermann P., (2018, July). Gaze as a Proxy for Cognition and Communication. In 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) (pp. 152-154). IEEE.

Sharma, K., Papavlasopoulou, S., Giannakos, M., & Jaccheri, L. (2018, June). Kid Coding Games and Artistic Robots: Attitudes and Gaze Behavior. In Proceedings of the Conference on Creativity and Making in Education (pp. 64-71).

Sharma, K., Mangaroska, K., Giannakos, M., & Dillenbourg, P. (2018). Interlacing Gaze and Actions to Explain the Debugging Process. Rethinking Learning in the Digital Age. Making the Learning Sciences Count Volume.

Håklev, S., Sharma, K., Slotta, J., & Dillenbourg, P. (2018, September). Semantically Meaningful Cohorts Enable Specialized Knowledge Sharing in a Collaborative MOOC. In European Conference on Technology Enhanced Learning (pp. 370-384). Springer, Cham.

Mangaroska, K., Sharma, K., Giannakos, M., Trætteberg, H., & Dillenbourg, P. (2018, March). Gaze insights into debugging behavior using learner-centred analysis. In Proceedings of the 8th international conference on learning analytics and knowledge (pp. 350-359).

Venant, R., Sharma, K., Vidal, P., Dillenbourg, P., & Broisin, J. (2018). Étude du comportement des apprenants dans les travaux pratiques et de sa corrélation avec la performance académique. Sciences et Technologies de l'Information et de la Communication pour l'Éducation et la Formation25(1), 169-194.

Olsen, J., Sharma, K., Aleven, V., & Rummel, N. (2018). Combining Gaze, Dialogue, and Action from a Collaborative Intelligent Tutoring System to Inform Student Learning Processes. International Society of the Learning Sciences. Inc.[ISLS].

Ozgur, A. G., Wessel, M. J., Johal, W., Sharma, K., Özgür, A., Vuadens, P., ... & Dillenbourg, P. (2018). Iterative Design of an Upper Limb Rehabilitation Game with Tangible Robots. In ACM/IEEE International Conference on Human-Robot Interaction (HRI) (p. 187).

Lee-Cultura, S., Mangaroska, K., & Sharma, K. (2018, September). Adult Perception of Gender-Based Toys and Their Influence on Girls’ Careers in STEM. In International Conference on Entertainment Computing (pp. 407-410). Springer, Cham.

Pappas, I., Sharma, K., Mikalef, P., & Giannakos, M. (2018). Visual aesthetics of E-commerce websites: An eye-tracking approach.

Pappas, I. O., Sharma, K., Mikalef, P., & Giannakos, M. N. (2018). A Comparison of Gaze Behavior of Experts and Novices to Explain Website Visual Appeal. In PACIS (p. 105).

Mikalef, P., Sharma, K., & Pappas, I. (2018). Social commerce and consumer search behavior: An eye-tracking study.

Sharma, K., Alavi, H. S., Jermann, P., & Dillenbourg, P. (2017, September). Looking THROUGH versus looking AT: A strong concept in technology enhanced learning. In European Conference on Technology Enhanced Learning (pp. 238-253). Springer, Cham.

Sharma, K., Leftheriotis, I., Noor, J., & Giannakos, M. (2017). Dual Gaze as a Proxy for Collaboration in Informal Learning. Philadelphia, PA: International Society of the Learning Sciences..

Sharma, K., Jermann, P., Dillenbourg, P., Prieto, L. P., D’Angelo, S., Gergle, D., ... & Rummel, N. (2017). Cscl and eye-tracking: Experiences, opportunities and challenges. Philadelphia, PA: International Society of the Learning Sciences..

Håklev, S., Sharma, K., Slotta, J., & Dillenbourg, P. (2017, September). Contextualizing the co-creation of artefacts within the nested social structure of a collaborative MOOC. In European Conference on Technology Enhanced Learning (pp. 67-81). Springer, Cham

Papavlasopoulou, S., Sharma, K., Giannakos, M., & Jaccheri, L. (2017, June). Using Eye-Tracking to Unveil Differences Between Kids and Teens in Coding Activities. In Proceedings of the 2017 Conference on Interaction Design and Children(pp. 171-181). ACM.

Prieto, L. P., Sharma, K., Kidzinski, Ł., & Dillenbourg, P. (2017). Orchestration load indicators and patterns: In-the-wild studies using mobile eye-tracking. IEEE Transactions on Learning Technologies11(2), 216-229.

Venant, R., Sharma, K., Vidal, P., Dillenbourg, P., & Broisin, J. (2017, September). Using sequential pattern mining to explore learners’ behaviors and evaluate their correlation with performance in inquiry-based learning. In European Conference on Technology Enhanced Learning (pp. 286-299). Springer, Cham.

Venant, R., Sharma, K., Dillenbourg, P., Vidal, P., & Broisin, J. (2017, June). A Study of Learners’ Behaviors in Hands-On Learning Situations and Their Correlation with Academic Performance. In International Conference on Artificial Intelligence in Education (pp. 570-573). Springer, Cham.

Mikalef, P., Sharma, K., Pappas, I. O., & Giannakos, M. N. (2017, November). Online Reviews or Marketer Information? An eye-tracking study on social commerce consumers. In Conference on e-Business, e-Services and e-Society (pp. 388-399). Springer, Cham.

Mikalef, P., Pappas, I. O., Giannakos, M. N., & Sharma, K. (2017, November). Determining Consumer Engagement in Word-of-Mouth: Trust and Network Ties in a Social Commerce Setting. In Conference on e-Business, e-Services and e-Society (pp. 351-362). Springer, Cham.

Sharma, K., D'Angelo, S., Gergle, D., & Dillenbourg, P. (2016). Visual augmentation of deictic gestures in mooc videos. Singapore: International Society of the Learning Sciences.

Sharma, K., Alavi, H. S., Jermann, P., & Dillenbourg, P. (2016). A gaze-based learning analytics model: in-video visual feedback to improve learner's attention in MOOCs. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 417-421). ACM

Sharma K. ,Kidzinski Ł. Jermann, P., & Dillenbourg, P. (2016). Towards predicting success in MOOCs: Programming assignments. Proceedings of the European Stakeholder Summit on experiences and best practices in and around MOOCs (EMOOCS 2016), 135.

Schneider, B., Sharma, K., Cuendet, S., Zufferey, G., Dillenbourg, P., & Pea, R. (2016). Detecting collaborative dynamics using mobile eye-trackers. Singapore: International Society of the Learning Sciences.

Boroujeni, M. S., Sharma, K., Kidziński, Ł., Lucignano, L., & Dillenbourg, P. (2016, September). How to quantify student’s regularity?. In European conference on technology enhanced learning (pp. 277-291). Springer, Cham.

Kidzinsk, L., Sharma, K., Boroujeni, M. S., & Dillenbourg, P. (2016). On Generalizability of MOOC Models. International Educational Data Mining Society.

Prieto, L. P., Sharma, K., Dillenbourg, P., & Jesús, M. (2016). Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors. In Proceedings of the sixth international conference on learning analytics & knowledge (pp. 148-157). ACM.

Sharma, K., Jermann, P., & Dillenbourg, P. (2015). Identifying Styles and Paths toward Success in MOOCs. International Educational Data Mining Society.

Sharma, K., Jermann, P., & Dillenbourg, P. (2015). Displaying teacher’s gaze in a MOOC: Effects on students’ video navigation patterns. In Design for Teaching and Learning in a Networked World (pp. 325-338). Springer, Cham.

Sharma, K., Caballero, D., Verma, H., Jermann, P., & Dillenbourg, P. (2015). Looking AT versus looking THROUGH: A dual eye-tracking study in MOOC context. International Society of the Learning Sciences, Inc.[ISLS]..

Prieto, L. P., Sharma, K., & Dillenbourg, P. (2015). Studying teacher orchestration load in technology-enhanced classrooms. In Design for teaching and learning in a networked world (pp. 268-281). Springer, Cham.

Prieto, L. P., Sharma, K., Wen, Y., & Dillenbourg, P. (2015). The burden of facilitating collaboration: towards estimation of teacher orchestration load using eye-tracking measures. International Society of the Learning Sciences, Inc.[ISLS]..

Schneider, B., Sharma, K., Cuendet, S., Zufferey, G., Dillenbourg, P., & Pea, R. D. (2015). 3D tangibles facilitate joint visual attention in dyads. International Society of the Learning Sciences, Inc.[ISLS]..

Sharma, K., Jermann, P., & Dillenbourg, P. (2014). “With-me-ness”: A gaze-measure for students’ attention in MOOCs. In Proceedings of International Conference of the Learning Sciences 2014 (No. CONF, pp. 1017-1022). ISLS.

Sharma, K., Jermann, P., & Dillenbourg, P. (2014). How students learn using MOOCs: An eye-tracking insight (No. CONF, pp. 147-154).

Prieto, L. P., Wen, Y., Caballero, D., Sharma, K., & Dillenbourg, P. (2014, November). Studying teacher cognitive load in multi-tabletop classrooms using mobile eye-tracking. In Proceedings of the Ninth ACM International Conference on Interactive Tabletops and Surfaces (pp. 339-344).

Sharma, K., Jermann, P., Nüssli, M. A., & Dillenbourg, P. (2013). Understanding collaborative program comprehension: Interlacing gaze and dialogues. In Proceedings of Computer Supported Collaborative Learning (CSCL 2013) (Vol. 1, No. EPFL-CONF-184007, pp. 430-437).

Sharma, K., Jermann, P., Nüssli, M. A., & Dillenbourg, P. (2012). Gaze Evidence for different activities in program understanding. In Proceedings of 24th Annual conference of Psychology of Programming Interest Group (No. EPFL-CONF-184006).

 

 

 

Scientific, academic and artistic work

Journal publications