Publications

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

scholar gscholar dblp dblp orcid orcid mendeley mendeley reserach-gate researchgate

Academic publications

Daniele counts 67 publications, 2112 citations, and 20 H-index starting from 2014 (Google Scholar, December 2025).

Journal publications

Romano, G., Schneider, J., Di Mitri, D., Drachsler, H. (2025). Through the Telescope: A Systematic Review of Intelligent Tutoring Systems and Their Applications in Psychomotor Skill Learning. International Journal of Artificial Intelligence in Education. doi: 10.1007/s40593-025-00526-1; blog post

Hummel, S., Schneider, J., Mouhammad, N., Klemke, R., & Di Mitri, D. (2025). Enhancing presentation skills: Key technical features of automated feedback systems – a systematic feature analysis. International Journal of Technology Enhanced Learning, 17(6), 10073166. doi: 10.1504/IJTEL.2025.10073166

Khazanchi, R., Di Mitri, D. & Drachsler, H. (2025). The Effect of AI-Based Systems on Mathematics Achievement in Rural Context: A Quantitative Study. J Comput Assist Learn. doi: 10.1111/jcal.13098

Karademir, O., Borgards, L., Di Mitri, D., Strauss, S., Kubsch, M., Brobeil, M., Grimm, A., Gombert, S., Rummel, N., Neumann, K., & Drachsler, H. (2024). Following the Impact Chain of the LA Cockpit: An Intervention Study Investigating a Teacher Dashboard’s Effect on Student Learning. Journal of Learning Analytics, 1-14. doi: 10.18608/jla.2024.8399

Karademir, O., Di Mitri, D., Schneider, J., Jivet, I., Allmang, J., Gombert, S., Kubsch, M., Neumann, K., & Drachsler, H. (2024). I don’t have time! But keep me in the loop: Co-designing requirements for a learning analytics cockpit with teachers. Journal of Computer Assisted Learning, 1–19. doi: doi.org/10.1111/jcal.12997

Cardenas Hernandez, F. P., Schneider, J., Di Mitri, D., Jivet, I., & Drachsler, H. (2024). Beyond hard workout: A multimodal framework for personalised running training with immersive technologies. British Journal of Educational Technology, 00, 1–32. doi: 10.1111/bjet.13445

Gombert, S., Fink, A., Giorgashvili, T., Jivet, I., Di Mitri, D., Yau, J., … Drachsler, H. (2024). From the Automated Assessment of Student Essay Content to Highly Informative Feedback: A Case Study. International Journal of Artificial Intelligence in Education. doi: 10.1007/s40593-023-00387-6

Zanellati, A., Di Mitri, D., Gabbrielli, M., & Levrini, O. (2023). Hybrid Models for Knowledge Tracing: A Systematic Literature Review. IEEE Transactions on Learning Technologies, 1–16. doi: 10.1109/TLT.2023.3348690

Khazanchi, R., Di Mitri, D. & Drachsler, H. (2023). Measuring Efficacy of ALEKS as a Supportive Instructional Tool in K-12 Math Classroom with Underachieving Students. Journal of Computers in Mathematics and Science Teaching, 42(2), 155-176. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/p/221775.

Wollny, S., Di Mitri, D., Jivet, I., Muñoz-Merino, P., Scheffel, M., Schneider, J., Tsai, Y.-S., Whitelock-Wainwright, A., Gašević, D., & Drachsler, H. (2023). Students’ expectations of Learning Analytics across Europe. Journal of Computer Assisted Learning, 1– 14. doi: 10.1111/jcal.12802

Gombert, S., Di Mitri, D., Karademir, O., Kubsch, M., Kolbe, H., Tautz, S., Grimm, A., Bohm, I., Neumann, K., & Drachsler, H. (2022). Coding energy knowledge in constructed responses with explainable NLP models. Journal of Computer Assisted Learning, 1– 20. doi: 10.1111/jcal.12767

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. doi: 10.1007/s40593-021-00281-z

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.

Asyraaf Mat Sanusi, K., Di Mitri, D., Limbu, B., & Klemke, R. (2021). Table Tennis Tutor: Forehand Strokes Classification Based on Multimodal Data and Neural Networks. Sensors, 21(9), 3121. doi: 10.3390/s21093121

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.

Conference publications

Mouhammad, N., Schneider, J., Klemke, R., & Di Mitri, D. (2025). From Nervous to Noteworthy: Evaluating SPEAKS, an Educational Software for Speech Content. European Conference on E-Learning, 24, 271–280. doi: 10.34190/ecel.24.1.4104

Hummel, S., Alomari, M., Schneider, J., Mouhammad, N., Klemke, R., & Di Mitri, D. (2025). Evaluating WEBPOSE, a Posture Feedback System for Oral Presentations.
European Conference on E-Learning, 24(1), 162–169. doi: 10.34190/ecel.24.1.4285

Gombert, S., Menzel, L., Di Mitri, D., & Drachsler, H. (2024). Predicting Item Difficulty and Item Response Time with Scalar-mixed Transformer Encoder Models andRational Network Regression Heads. In E. Kochmar, M. Bexte, J. Burstein, A. Horbach, R. Laarmann-Quante, A. Tack, … Z. Yuan (Eds.), Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024) (pp. 483–492). Mexico City, Mexico: Association for Computational Linguistics. Retrieved from https://aclanthology.org/2024.bea-1.40

Cardenas Hernandez, F. P., Schneider, J., Di Mitri, D. & Drachsler, H. (2025). On-Your Marks, Ready? Exploring the User Experience of a VR Application for Runners with Cognitive-Behavioral Influences. In Proceedings of the 17th International Conference on Computer Supported Education – Volume 1: CSEDU; ISBN 978-989-758-746-7; ISSN 2184-5026, SciTePress, pages 331-341. doi: 10.5220/0013271300003932

Casalino, G., Castellano, G., Di Mitri, D., Kaczmarek-Majer, K. & Zaza G. (2024). A Human-centric Approach to Explain Evolving Data: A Case Study on Education. At the 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), Madrid, Spain, 2024, pp. 1-8, doi: 10.1109/EAIS58494.2024.10569098

Di Mitri, D., Epp, A., & Schneider. J., (2024). Preserving Privacy in Multimodal Learning Analytics with Visual Animation of Kinematic Data. In: Casalino, G., et al. Higher Education Learning Methodologies and Technologies Online. HELMeTO 2023. Communications in Computer and Information Science, vol 2076. Springer, Cham. doi: 10.1007/978-3-031-67351-1_45

Böttger, F., Cetinkaya, U., Di Mitri, D., Gombert, S., Shingjergji, K., Iren, D., & Klemke, R. (2022). Privacy-Preserving and Scalable Affect Detection in Online Syn- chronous Learning. In I. Hilliger, P. J. Munoz-Merino, T. De Laet, A. Ortega-Arranz, & T. Farrell (Eds.), Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption (pp. 45–58). Cham: Springer International Publishing. doi:  10.1007/978-3-031-16290-9_4

Khazanchi, R., Di Mitri, D., & Drachsler, H. (2022). Impact of Intelligent Tutoring Systems on Mathematics Achievement of Underachieving Students. In E. Langran (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1524-1534). San Diego, CA, United States: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/primary/p/220916/.

Ahmad, A., Schneider, J., Weidlich, J., Di Mitri, D., Yau, J., Schiffner, D. and Drachsler, H. (2022). What Indicators Can I Serve You with? An Evaluation of a Research-Driven Learning Analytics Indicator Repository. In Proceedings of the 14th International Conference on Computer Supported Education. doi: 10.5220/0010995800003182

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: 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.

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: Bitten- court, 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). 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). 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.

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 Schneider, 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

Workshop papers, posters, demos, keynotes, abstracts

Onat, T. B., & Di Mitri, D. (2025). Teacher-Driven Feedback System for a Presentation Training Software. 7th International Conference on Higher Education Learning Methodologies and Technologies Online (214–216), 23-25 September 2025, Naples, Italy. ISBN: 978-88-99978-68-6

Di Mitri, D., Schneider, J., Mouhammad, N., Hummel, S., Alomari, M., Alhag Ali, M., Masum, M. H. R., Arif, H., Rose, M., & Klemke, R. (2025). Enhance your presentation skills with Presentable. Companion Proceedings of the 15th International Learning Analytics and Knowledge Conference (LAK’25). Page 285 https://www.solaresearch.org/wp-content/uploads/2025/02/LAK25_CompanionProceedings-Final.pdf

Borgards, L., Karademir, O., Strauß, S., Di Mitri, D., Kubsch, M., Brobeil, M., … Rummel, N. (2024). Achieving Tailored Feedback by Means of a Teacher Dashboard? Insights into Teachers’ Feedback Practices. In: Ferreira Mello, R., Rummel, N., Jivet, I., Pishtari, G., Ruipérez Valiente, J.A. (eds) Technology Enhanced Learning for Inclusive and Equitable Quality Education. EC-TEL 2024. Lecture Notes in Computer Science, vol 15160. Springer, Cham. doi: 10.1007/978-3-031-72312-4_8

Epp, A., Schneider, J., & Di Mitri, D. (2023). Privacy-preserving multimodal learning analytics using visual animations of kinematic data. Higher Education Learning Methodologies and Technologies Online 2023 (214–216), Foggia, Italy. ISBN: 978-88-99978-64-8

Tobias, J.L., Di Mitri, D. (2023). Using Accessible Motion Capture in Educational Games for Sign language Learning. In: Viberg, O., Jivet, I., Muñoz-Merino, P., Perifanou, M., Papathoma, T. (eds) Responsive and Sustainable Educational Futures. EC- TEL 2023. Lecture Notes in Computer Science, vol 14200. Springer, Cham. doi: 10.1007/978-3-031-42682-7_74

Gombert, S., Menzel, L., Karademir, O., Di Mitri, D., & Drachsler, H. (2023). Making an Online Whiteboard Ready for Multimodal Interaction: Integrating Text-and Voice Chat into Hyperchalk. In K. A. M. Sanusi, B. Limbu, J. Schneider, M. Kravčík, & R. Klemke (Eds.), Proceedings of the Third International Workshop on Multimodal Immersive Learning Systems (MILeS 2023) (pp. 44-48). Aveiro, Portugal: CEUR. Retrieved from https://ceur-ws.org/Vol-3499/paper6.pdf

Menzel, L., Gombert, S., Di Mitri, D., Drachsler, H. (2022). Superpowers in the Classroom: Hyperchalk Is an Online Whiteboard for Learning Analytics Data Collection. In: Hilliger, I., Muñoz-Merino, P.J., De Laet, T., Ortega-Arranz, A., Farrell, T. (eds) Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. EC-TEL 2022. Lecture Notes in Computer Science, vol 13450. Springer, Cham. doi: 10.1007/978-3-031-16290-9_37 (best demo award)

Di Mitri, D., Gombert, S., & Karademir, O. (2022). Reflecting on the Actionable Components of a Model for Augmented Feedback. In K. A. M. Sanusi, B. Limbu, J. Schneider, D. Di Mitri, & R. Klemke (Eds.), Proceedings of the Second International Workshop on Multimodal Immersive Learning Systems (MILeS 2022) (pp. 45–50). Toulouse, France: CEUR. Retrieved from http://ceur-ws.org/Vol-3247/#paper8

Buraha, T., Schneider, J., Di Mitri, D. (2021) Using MMLA to study the link between body and mind. In Spikol, D. et al. (Eds.), Companion Proceedings 11th International Conference on Learning Analytics & Knowledge (LAK21) (386–389). Retrieved from https://www.solaresearch.org/

Di Mitri, D. (2021). Restoring Context in Online Teaching with Artificial Intelligence and Multimodal Learning Experiences. In E. Langran & D. Rutledge (Eds.), Proceedings of SITE Interactive Conference (pp. 494-501). Online, United States: Association for the Advancement of Computing in Education (AACE). Retrieved December 6, 2021 from https://www.learntechlib.org/primary/p/220376/

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). The Multimodal Learning 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). Multimodal Pipeline: A generic approach for handling multimodal data for supporting 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).

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

Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018). Multimodal Challenge: 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. Retrieved from http://bit.ly/lak18-companion-proceedings 

Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018). The Big Five: Addressing 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)

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/Cross- LAK16Paper7.pdf

Books & collections

Di Mitri, D., Ortega-Arranz, A. & Poquet, O. (2023). Proceedings of the Doctoral Consortium of the 18th European Conference on Technology Enhanced Learning. Co-located with the 18th European Conference on Technology Enhanced Learning (EC-TEL 2023).Aveiro, Portugal. https://ceur-ws.org/Vol-3539/

Di Mitri D., Srivastava, N., Martinez-Maldonado, R., Cukurova, M. & Spikol, D. (2023). Proceedings of the 6th CROSSMMLA workshop “Leveraging Multimodal Data for Generating Meaningful Feedback”. At the 13th International Learning Analytics & Knowledge (LAK’23). Arlington, Texas, United States: CEUR. Retrieved from https://ceur-ws.org/Vol-3439/.

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, 74(3), 249-263. doi: 10.13109/buer.2021.74.3.249

 Books & Collections

  1. Di Mitri, D., Ortega-Arranz, A. & Poquet, O. (2023). Proceedings of the Doctoral Con- sortium of the 18th European Conference on Technology Enhanced Learning. Co-located with the 18th European Conference on Technology Enhanced Learning (EC-TEL 2023).Aveiro, Portugal. https://ceur-ws.org/Vol-3539/
  2. Di Mitri D., Srivastava, N., Martinez-Maldonado, R., Cukurova, M. & Spikol, D. (2023). Proceedings of the 6th CROSSMMLA workshop “Leveraging Multimodal Data for Generating Meaningful Feedback”. At the 13th International Learning Analytics & Knowledge (LAK’23). Arlington, Texas, United States: CEUR. Retrieved from https://ceur-ws.org/Vol-3439/.
  3. Jivet, I., Di Mitri, D., Schneider, J., Papamitsiou, Z., & Fominykh, M. (2022). Proceed- ings of the Doctoral Consortium of the 17th European Conference on Technology Enhanced Learning. Toulouse, France: CEUR. Retrieved from https://ceur-ws.org/Vol-3292/
  4. Giannakos, M., Spikol, D., Di Mitri, D., Sharma, K., Ochoa, X., & Hammad, R. (Eds.). (2022). The Multimodal Learning Analytics Handbook (1st ed. 2022 edition). S.l.: Springer.
  5. Asyraaf Mat Sanusi, K., Limbu, B., Schneider, J., Di Mitri, D., & Klemke, R. (Eds.). (2022). Proceedings of the Second International Workshop on Multimodal Immersive Learning Systems (MILeS 2022) (Vol. 3247). CEUR. https://ceur-ws.org/Vol-3247/
  6. Klemke, R., Asyraaf Mat Sanusi, K., Majonica, D., Richert, A., Varney, V., Keller, T., Schneider, J., Di Mitri, D., Ciordas-Hertel, G., Cardenas-Hernandez, F., Romano, G., Kravcik, M., Paaßen, B., Klamma, R., Slupczynski, M., Klatt, S., Geisen, M., Baumgartner, T., & Riedl, N. (2021) Proceedings of the 1st In- ternational Workshop on Multimodal Multimodal Immersive Learning Systems (MILeS 2021). At the 16th European Conference on Technology Enhanced Learn- ing: Technology-Enhanced Learning for a Free, Safe, and Sustainable World. On- line, Bozen-Bolzano, Italy, September 20-24, 2021, CEUR-WS.org/Vol-2979, ISSN 1613-0073.
  7. 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.
  8. Giannakos, M., Spikol, D., Di Mitri, D., Sharma, K., Ochoa, X., Hammad, R. eds (2022) The Multimodal Learning Analytics Handbook. 1st ed. 2022 edition. S.l.: Springer, 2022.
  9. Di Mitri, D. (2020). The Multimodal Tutor: Adaptive Feedback from Multi-modal Experiences. PhD dissertation. Open Universiteit. OU Digital Library. ISBN: 978-94-93211-21-6

Book chapters

  1. Di Mitri, D., & Whittaker, C. (2024). Profiling. In the book published by the Johanna Quandt Academy on “Connectivity, Networks, Flows”. (in Publication)
  2. Ruipérez-Valiente, J. A., Martínez-Maldonado, R., Di Mitri, D., & Schneider, J. (2022). From Sensor Data to Educational Insights. Sensors, 22(21), 8556. doi: 10.3390/s22218556
  3. Di Mitri, D., Schneider, J., Drachsler, H. (2022). The Rise of Multimodal Tutors in Education. In: Handbook of Open, Distance and Digital Education. Springer, Singapore. 10.1007/978-981-19-0351-9_58-1.
  4. Di Mitri, D., Limbu, B., Schneider, J., Klemke, R. (2021) Multimodal Learning Analytics For Deliberate Practice. Accepted. To appear in The Multimodal Learning Analytics Handbook. Springer Nature.
  5. Schneider, J., Di Mitri, D., Limbu, B., Drachsler, H. (2020) Der multimodale Lern-Hub: Ein Werkzeug zur Erfassung individualisierbarer und sensorgestützter multimodaler Lernerfahrungen. In Digitale Bildung und Künstliche Intelligenz in Deutschland (pp. 537-557). Springer, Wiesbaden.