Research Group Leader in Artificial Intelligence in Education at DIPF
Information Center for Education
Rostocker Straße 6, 60323 Frankfurt am Main

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Telephone: +49 (0) 69-24708-386
Email: dimitri [at]

Daniele Di Mitri is a research group leader at the Education Technology group at DIPF Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt. Daniele received his Ph.D. title at the Open University of The Netherlands (2020) in Learning Analytics. His Ph.D. project, the Multimodal Tutor, investigated the potentials of collecting and analysing multimodal data during physical interactions for automatic feedback and human behaviour analysis. Daniele’s current research focuses on designing responsible Artificial Intelligence applications for education and human support. He is a “Johanna Quandt Young Academy” fellow. He was elected “AI Newcomer 2021” at the KI Camp by the German informatics society and received the “Martin Wolpers Award” in technology-enhanced learning 2018. He is a member of the editorial board of Frontiers in Artificial Intelligence journal, a member of the CrossMMLA, a special interest group of the Society of Learning Analytics Research, and he is the chair of the Learning Analytics Hackathon (LAKathon) series.
  • Multimodal Learning Analytics
  • Artificial Intelligence in Education
  • Technology-Enhanced Learning
  • Machine Learning
  • Human Computer Interaction
  • Multimodal Tutor for CPR
  • Learning Pulse
  • Visual Inspection Tool
  • Nexus speech assistant
  • Mobius - transportation mode recognition
  • PhD in Learning Analyics and Wearable-Sensors Support Open University of the Netherlands, Heerlen Netherlands 2020
  • Master of Science in Artificial Intelligence, Department of Data Science and Knowledge Engineering, Maastricht University 2016
  • Bachelor of Science in Computer Science and Digital Communication, University of Bari, Italy 2020


    Journal articles (Peer-reviewed Journals)


  • Ciordas-Hertel, G.‑P., Rödling, S., Schneider, J., Di Mitri, D., Weidlich, J. & Drachsler, H. (2021). Mobile sensing with smart wearables of the physical context of distance learning students to consider its effects on learning. Sensors, 21(19), 6649. doi: 10.3390/s21196649 🔓
  • Di Mitri, D., Schneider, J. & Drachsler, H. (2021). Keep me in the loop: Real-time feedback with multimodal data. International Journal of Artificial Intelligence in Education, online first. doi: 10.1007/s40593-021-00281-z 🔓
  • Di Mitri, D., Schneider, J. & Drachsler, H. (2021). Keep Me in the Loop: Real-Time Feedback with Multimodal Data. International Journal of Artificial Intelligence in Education, online first. doi: 10.1007/s40593-021-00281-z 🔓
  • Mavrikis, M., Cukurova, M., Di Mitri, D., Schneider, J. & Drachsler, H. (2021). A short history, emerging challenges and co-operation structures for Artificial Intelligence in education. Bildung und Erziehung, 249-263. doi: 10.13109/buer.2021.74.3.249
  • 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, 4:654924. doi: 10.3389/frai.2021.654924 🔓
  • 2019

  • Di Mitri, D., Schneider, J., Specht, M. & Drachsler, H. (2019). Detecting mistakes in CPR training with multimodal data and neural networks. Sensors, 19(14), 3099. doi: 10.3390/s19143099 🔓
  • Book Chapters


  • 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 T. De Laet, R. Klemke, C. Alario-Hoyos, I. Hilliger & A. Ortega-Arranz (Hrsg.), Technology-enhanced learning for a free, safe, and sustainable world: 16th European Conference on Technology Enhanced Learning, EC-TEL 2021, Bolzano, Italy, September 20-24, 2021, proceedings (Lecture Notes in Computer Science, Bd. 12884, S. 137-148). Cham: Springer. doi: 10.1007/978-3-030-86436-1_11 🔓
  • Di Mitri, D. (2021). Restoring context in online teaching with artificial intelligence and multimodal learning experiences. In E. Langran & D. Rutledge (Hrsg.), Proceedings of SITE Interactive Conference, Oct 26, online (S. 494-501). Waynesville: Association for the Advancement of Computing in Education (AACE). Abgerufen unter:
  • Karademir, O., Ahmad, A., Schneider, J., Di Mitri, D., Jivet, I. & Drachsler, H. (2021). Designing the learning analytics cockpit: A dashboard that enables interventions. In F. De la Prieta, R. Gennari, M. Temperini, T. Di Mascio, P. Vittorini, Z. Kubincova, E. Popescu, D. Rua Carneiro, L. Lancia & A. Addone (Hrsg.), Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL), 11th International Conference (Lecture Notes in Networks and Systems, Bd. 326, S. 95-104). Cham: Springer. doi: 10.1007/978-3-030-86618-1_10
  • 2020

  • Di Mitri, D., Schneider, J., Trebing, K., Sopka, S., Specht, M. & Drachsler, H. (2020). Real-time multimodal feedback with the CPR Tutor. In I. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin & E. Millán (Hrsg.), Artificial Intelligence in education: 21st International Conference, AIED 2020, Ifrane, Morocco, July 6-10, 2020, proceedings (Lecture Notes in Computer Science, Bd. 12163, S. 141-152). Cham: Springer. doi: 10.1007/978-3-030-52237-7_12
  • Schneider, J., Di Mitri, D., Limbu, B. & Drachsler, H. (2020). Der multimodale Lern-Hub: Ein Werkzeug zur Erfassung individualisierbarer und sensorgestützter multimodaler Lernerfahrungen. In R. A. Fürst (Hrsg.), Digitale Bildung und Künstliche Intelligenz in Deutschland: Nachhaltige Wettbewerbsfähigkeit und Zukunftsagenda (AKAD University Edition, S. 537-557). Wiesbaden: Springer. doi: 10.1007/978-3-658-30525-3_23
  • 2019

  • Di Mitri, D., Schneider, J., Klemke, R., 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), Tempe, AZ, USA, March 04-08, 2019 (S. 51-60). New York: Association for Computing Machinery. doi: 10.1145/3303772.3303776 🔓