This is the most up-to-date list of my research experience. You can also find me in other Academic exchange platforms:

Daniele counts 30 publications, 288 citations and 9 H-index starting from 2014, (Google Scholar, 13th September 2021).

Journal publications

  • Di Mitri, D., Schneider, J., & Drachsler, H. (2021). Keep Me in the Loop: Real-Time Feedback with Multimodal Data. Accepted. International Journal of Artificial Intelligence in Education (IJAIEd).
  • Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler,H. (2021). Are we there yet? - A Systematic Literature Review on Chatbots in Education. Frontiers in Artificial Intelligence, 4. DOI: 10.3389/frai.2021.654924
  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2019). Detecting mistakes in CPR training with multimodal data and neural networks. Sensors (Switzerland), 19(14), 1–20. DOI: 10.3390/s19143099.
  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018).   From signals to knowledge: A conceptual model for multimodal learning analytics. Journal of Computer Assisted Learning, 34(4), 338–349. DOI: 10.1111/jcal.12288. (Most-cited publication)

Conference publications

  • Karademir O., Ahmad A., Schneider J., Di Mitri D., Jivet I., Drachsler H. (2022) Designing the Learning Analytics Cockpit - A Dashboard that Enables Interventions. In: De la Prieta F. et al. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning, 11th International Conference. MIS4TEL 2021. Lecture Notes in Networks and Systems, vol 326. Springer, Cham. DOI: 10.1007/978-3-030-86618-1_10.
  • Buraha T., Schneider J., Di Mitri D., Schiffner D. (2021) Analysis of the “D’oh!” Moments. Physiological Markers of Performance in Cognitive Switching Tasks. In: De Laet T., Klemke R., Alario-Hoyos C., Hilliger I., Ortega-Arranz A. (eds) Technology-Enhanced Learning for a Free, Safe, and Sustainable World. EC-TEL 2021. Lecture Notes in Computer Science, vol 12884. Springer, Cham. DOI: 10.1007/978-3-030-86436-1_11.
  • Mat Sanusi, K. A., Di Mitri, D., Limbu, B., & Klemke, R. (2021). Table Ten- nis Tutor: Forehand Strokes Classification Based on Multimodal Data and Neural Networks. Sensors, 21(9), 3121. 10.3390/s21093121
  • Di Mitri D., Asyraaf Mat Sanusi K., Trebing K., Bromuri S. (2021) MOBIUS: Smart Mobility Tracking with Smartphone Sensors. In: Paiva S., Lopes S.I., Zitouni R., Gupta N., Lopes S.F., Yonezawa T. (eds) Science and Technologies for Smart Cities. SmartCity360° 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 372. Springer, Cham. DOI: 10.1007/978-3-030-76063-2_31 (video) (slides) (best paper award)
  • Di Mitri, D., Schneider, J., Trebing, K., Sopka, S., Specht, M., Drachsler, H. (2020) Real-time Multimodal Feedback with the CPR Tutor. In: Bittencourt, I.I., Cukurova, M., Muldner, K. (eds) Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science. Springer, Cham. DOI: 10.1007/978-3-030-52237-7_12 (slides)
  • Di Mitri, D. , Schneider, J., Specht, M., Drachsler, H. (2019) The Multimodal Learn- ing Analytics Pipeline. In Proceedings of the Artificial Intelligence and Adaptive Education Conference – AIAED’19. Beijing, China: IEEE. ResearchGate (slides)
  • Di Mitri, D. , Schneider, J., Specht, M., Drachsler, H. (2019) Read Between the Lines: An Annotation Tool for Multimodal Data for Learning. In Proceedings of the 9th International Conference on Learning Analytics & Knowledge - LAK19 (pp. 51–60). New York, NY, USA: ACM. DOI: 10.1145/3303772.3303776 (slides)
  • Guest, W., Wild, F., Di Mitri, D., Klemke, R., Karjalainen, J., & Helin, K. (2019, December). Architecture and design patterns for distributed, scalable augmented reality and wearable technology systems. In 2019 IEEE International Conference on Engineering, Technology and Education (TALE) (pp. 1-8). IEEE. doi: 10.1109/TALE48000.2019.9225855.
  • Di Mitri, D. (2018) Multimodal Tutor for CPR. In: Penstein Rosé C. et al. (eds) Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science, vol 10948. Springer, Cham. DOI: 10.1007/978-3-319-93846-2_96
  • Schneider, J., Di Mitri, D., Limbu, B. & Drachsler, H. (2018). Multimodal Learning Hub: a tool for capturing customizable multimodal learning experiences. In European Conference on Technology Enhanced Learning. Springer, Cham. DOI: 10.1007/978-3-319-98572-5_4
  • Di Mitri, D., Scheffel, M., Drachsler, H., Börner, D., Ternier, S., & Specht, M. (2017). Learning Pulse: a Machine Learning Approach for Predicting Performance in Self-Regulated Learning Using Multimodal Data. In: Proceedings of the Seventh International Learning Analytics & Knowledge Conference 2017 (LAK ’17) (pp. 188-197). New York, NY, USA. ACM. DOI: 10.1145/3027385.3027447 (video) (slides)
  • Guest, W., Wild, F., Vovk, A., Fominykh, M., Limbu, B., Klemke, R. Sharma, P., Karjalainen, J., Smith, C., Rasool, J., Aswat, S., Helin, K., Di Mitri, D., and Schnei- der, J. (2017) Affordances for Capturing and Re-enacting Expert Performance with Wearables. In: Lavoué É., Drachsler H., Verbert K., Broisin J., Pérez-Sanagustín M. (eds) Data Driven Approaches in Digital Education. EC-TEL 2017. Lecture Notes in Computer Science, vol 10474. Springer, Cham. DOI: 10.1007/978-3-319-66610-5_34
  • Di Mitri, D., Scheffel, M., Drachsler, H., Börner, D., Ternier, S., & Specht, M. (2016). Learning Pulse: Using Wearable Biosensors and Learning Analytics to Investigate and Predict Learning Success in Self-regulated Learning. In R. Martinez- Maldonado & D. Hernandez-Leo (Eds.), Proceedings of the First International Workshop on Learning Analytics Across Physical and Digital Spaces, Vol. 1601 (pp. 34-39): CEUR Proceedings. http://ceur-ws.org/Vol-1601/CrossLAK16Paper7.pdf

Workshop publications

  • Buraha, T., Schneider, J., Di Mitri, D. (2021) In Spikol, D. et al. (Eds.), Proceedings of the Third Multimodal Learning Analytics Across (Physical and Digital) Spaces (CrossMMLA).
  • Di Mitri, D. (2019) Detecting Medical Simulation Errors with Machine learning and Multimodal Data. Doctoral Consortium of the Seventeenth Conference of Artificial Intelligence in Medicine (AIME’19). Poznań, Poland. (slides)
  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2019) Multimodal Pipeline: A generic approach for handling multimodal data forsupporting learning. First workshop on AI-based Multimodal Analytics for Understanding Human Learning in Real-world Educational Contexts (AIMA4EDU) IJCAI’19 Macau, China (best paper award).
  • Schneider, J., Di Mitri, D., Specht, M., & Drachsler, H. (2019) Multimodal Learning Analytics Runtime Framework. In Spikol, D. et al. (Eds.), Proceedings of the Third Multimodal Learning Analytics Across (Physical and Digital) Spaces (CrossMMLA).
  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018) Multimodal Chal- lenge: Analytics Beyond User-computer Interaction Data. In Pardo, A., Bartimote, K., Lynch, G., Buckingham Shum, S., Ferguson, R., Merceron, A., & Ochoa, X. (Eds.). (2018). Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 362-365). Sydney, Australia: Society for Learning Analytics Research.
  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018) The Big Five: Ad- dressing Recurrent Multimodal Learning Data Challenges. In R. Martinez-Maldonado et al. (Eds.), Proceedings of the Second Multimodal Learning Analytics Across (Physical and Digital) Spaces (CrossMMLA), Vol. 2163. CEUR Proceedings. http://ceur-ws.org/Vol-2163/#paper6
  • Di Mitri, D. (2017). Digital Learning Projection. Learning performance estimation from multimodal learning experiences. In E. André, R. Baker, X. Hu, Ma. M.T. Rodrigo, & B. du Boulay (Eds.), Proceedings of AIED 2017, 18th International Conference on Artificial Intelligence in Education (pp. 609–612). Wuhan, China: Springer International Publishing. DOI: 10.1007/978-3-319-61425-0 (slides)

Books & Collections

  • Di Mitri, D., Martinez-Maldonado, R., Santos, O., Schneider, J., Asyraaf Mat Sanusi, K., Cukurova, M., Spikol, D., Molenaar, I., Michail, G., Klemke, R. & Azevedo, R. (2021) Proceedings of the 1st International Workshop on Multimodal Artificial Intelligence in Education (MAIEd’21). At the 22nd International Conference on Artificial Intelligence in Education (AIED 2021). Online, Utrecht, The Netherlands. CEUR-WS.org/Vol-2902, ISSN 1613-0073.
  • Giannakos, M., Spikol, D., Di Mitri, D., Sharma, K., Ochoa, X., Hammad, R. (2020) Handbook of Multimodal Learning Analytics. Springer Nature. In preparation.
  • Di Mitri, D. (2020). The Multimodal Tutor: Adaptive Feedback from Multimodal Experiences. PhD dissertation. Open Universiteit. OU Digital Library. ISBN: 978-94-93211-21-6

Book chapters

  • Di Mitri, Schneider, J., Drachsler, H. (2021) The Rise of Multimodal Tutors in Education: Insights from Recent Research. In review. To appear in Handbook of Open, Distance, and Digital Education. in Springer’s Major Reference Works Series.
  • Di Mitri, D., Limbu, B., Schneider, J., Klemke, R. (2021) Multimodal Learning Analytics For Deliberate Practice. Accepted. To appear in The Handbook of Multimodal Learning Analytics. Springer Nature.
  • Schneider, J., Di Mitri, D., Limbu, B., Drachsler, H. (2020) Der multimodale Lern- Hub: Ein Werkzeug zur Erfassung individualisierbarer und sensorgestützter multi- modaler Lernerfahrungen. In Digitale Bildung und Künstliche Intelligenz in Deutsch- land (pp. 537-557). Springer, Wiesbaden.

Technical reports

  • Klemke, R., Di Mitri, D., Limbu, B., Sharma (2018). Software Prototype with Sensor Fusion API Specification and Usage Description. WEKIT project deliverable D3.6.
  • Klemke, R., Di Mitri, D., Limbu, B., Schneider, J., Sharma, P., Wild, F., Azam, T. (2017, 4 July). Software Prototype with Sensor Fusion API Specification and Usage Description. WEKIT project deliverable D3.3.

Roles in conferences

  • Publicity Chair of the Learning Analytics & Knowledge Conference. (LAK’20). Cyberspace. Website: https://lak20.solaresearch.org/
  • Local Chair of the EATEL Summer School of Technology-Enhanced. Learning (jTELSS’19) (2019) Bari, Italy Website: https://ea-tel.eu/jtelss/
  • Organisation committee member of the EATEL Summer School of Technology-Enhanced. Learning (jTELSS’18), (2018) Durres, Albania
  • Coordinator of the international conference “Education in Crisis”, OBESSU (2014) Rome, Italy
  • Trainer at the Training for International Officers, OBESSU (2013) Brussels
  • Trainer for the Bulgarian School Student Union, OBESSU, (2013) Sofia, Bulgaria
  • Activity leader “YOUVET – Training for Young VET campaigners”, OBESSU (2013) Brussels, Belgium
  • Coordinator of the 8th European School Student Convention “Education at 360°”, OBESSU, (2012), Bern, Switzerland

Organised workshops

  • Di Mitri, D., Martinez-Maldonado, R., Santos, O., Schneider, J., Asyraaf Mat Sanusi, K., Cukurova, M., Spikol, D., Molenaar, I., Michail, G., Klemke, R. & Azevedo, R. (2021) First International Workshop on Multimodal Artificial Intelli- gence in Education (MAIEd’21). At the 22nd International Conference on Artificial Intelligence in Education (AIED 2021). Online.
  • Di Mitri, D., Berg, A., Kismihók, G., Ruipérez-Valiente, J., Kitto, K., Schneider, J., Ahmad A. and Mol, S. (2021) The 7th LAKathon: Is Learning in Isolation a Mis- sion Impossible?. Pre-conference workshop at the Learning Analytics & Knowledge Conference (LAK’21). Online.
  • Spikol, D., Ochoa, X., Worsley, M., Di Mitri, D., Cukurova, M., Martinez-Maldonado, R. and Schneider, J., (2021) CROSSMMLA Futures: Collecting and analysing multimodal data across the physical and the virtual. Pre-conference workshop at the Learning Analytics & Knowledge Conference (LAK’21). Online.
  • Michail, G. Spikol, D., Molenaar, I., Di Mitri, D., Sharma, K., Ochoa, X., Ham- mad, R. (2020) CrossMMLA in practice: Collecting, annotating and analyzing multimodal data across spaces. Pre-conference workshop at the Learning Analytics & Knowledge Conference (LAK’20). Online.
  • Di Mitri, D., & Schneider, J. (2019, 6th June) Multimodal Tutor. Thematic workshop at the 15th EATEL Summer School in Technology Enhanced Learning (JTEL), Bari, Italy.
  • Di Mitri, D., Cooper, A., Kitto, K., Kismihók, G. Mol, S.T., Sclater, N., Schneider, J. & Berg, A. (2019) The Fifth LAK Hackathon: Trusted and Inclusive Learn- ing Analytics Across Spaces with New Tools, Standards and Infrastructures. Pre-conference workshop at the Learning Analytics & Knowledge Conference (LAK’19). Tempe, Arizona, US.
  • Spikol, D., Di Mitri, D., Echeverria, V., Martinez-Maldonado, R., Cukurova, M., Prieto, L.P, Rodríguez-Triana, M.J., Ochoa, X., Worsley, M. & Giannakos, M. (2019) 3rd CrossMMLA: Multimodal Learning Analytics Across Physical and Digital Spaces. Pre-conference workshop at the Learning Analytics & Knowledge Conference (LAK’19). Tempe, Arizona, US.
  • Di Mitri, D., & Specht, M. (2019, 8 April) Multimodal Learning Analytics parallel workshop and demonstration. Learning Analytics in Higher Education Conference, Delft Technical University Delft, The Netherlands.
  • Di Mitri, D., & Schneider, J. (2018, 15 May) Sensors for Learning, Thematic workshop at the 14th EATEL Summer School in Technology Enhanced Learning (JTEL), Dürres, Albania.
  • Di Mitri, D., & Schneider, J. (2017, 12 October) Multimodal Machines, Thematic workshop at the 13th EATEL Summer School in Technology Enhanced Learning (JTEL), Aveiro, Portugal.