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

Outline

  1. PhD Thesis
  2. Academic journal publications
  3. Conference proceedings publications
  4. Workshop proceedings publications
  5. Project deliverables
  6. Invited Talks and Presentations
  7. Workshops and interactive sessions
  8. Awards
  9. Teaching activities
  10. Interviews
  11. Reviewer Roles

1. PhD Thesis

  • Di Mitri, D. (2020). The Multimodal Tutor: Adaptive Feedback from Multimodal Experiences. Open Universiteit. OU Digital Library slides

2. Academic Journal publications

  • 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

3. Conference proceedings publications

  • Di Mitri, D., Asyraaf, K., Trebing, K., Bromuri, S. (2020)  MOBIUS: Smart Mobility Tracking with Smartphone Sensors. To appear in 6th EAI International Summit, SmartCity360, online, December 2-4, 2020, Proceedings. Springer Nature. slides / video
  • 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 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) 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
  • 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 / slides / video
  • 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
  • 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

4. Workshop proceedings publications

  • 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. ResearchGate slides
  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2019) Multimodal Pipeline: A generic approach for handling multimodal data for supporting learning. The first workshop on AI-based Multimodal Analytics for Understanding Human Learning in Real-world Educational Contexts (AIMA4EDU) IJCAI'19 Macau, China. ResearchGate (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 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. https://lakhackathon.files.wordpress.com/2018/02/lakhackathon2018_paper_5.pdf
  • 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

5. Project deliverables

  • Klemke, R. (Ed.), Di Mitri, D., Limbu, B., Sharma (2018). Software Prototype with Sensor Fusion API Specification and Usage Description. WEKIT project deliverable D3.6.
  • Klemke, R. (Ed.), 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.

6. Invited Talks and Presentations

  • Di Mitri, D. (2020, 8th July). Real-time Multimodal Feedback with the CPR Tutor. Paper Presentation at the International Conference in Artificial Intelligence in Education 2020. slides
  • Di Mitri, D. (2019, 6 March). Read Between The Lines. Paper Presentation at the 9th Learning Analytics & Knowledge conference 2018, Tempe, Arizona, United States. slides
  • Di Mitri, D. (2019, 4th April) Multimodal Tutors: Enhancing learning using multimodal data and machine learning. Guest Lecture to the Adaptive Learning Lab of the Behavioural Science Institute, Radboud University Nijmegen, The Netherlands. (Slides upon request)
  • Di Mitri, D. (2018, 24 November) Multimodal Tutors: Enhancing learning using multimodal data and machine learning. OU Informatica StudieDag, Eindhoven, The Netherlands. (Slides upon request)
  • Di Mitri, D. (2018, 22 January) Multimodal Learning Analytics: An IoT approach for social signals. Guest lecture at Hogeschool Zuyd, Internet of Things Course Heerlen, The Netherlands.(Slides upon request)
  • Di Mitri, D. (2017, 13 March). Learning Pulse: a Machine Learning Approach for Predicting Performance in Self-Regulated Learning Using Multimodal Data. Presentation at the 7th International Learning Analytics & Knowledge Conference 2017 (LAK '17) slides   video

7. Workshops and interactive sessions

  • 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. slides
  • 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. slides
  • 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. slides
  • 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. slides

8. Awards

  • "From signals to knowledge: A conceptual model for multimodal learning analytics" was the Top Downloaded Paper 2018-19 in the Journal of Computer Assisted Learning

Image

  • Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2019) Multimodal Pipeline: A generic approach for handling multimodal data for supporting learning. Best Paper Award at AIMA4EDU workshop at IJCAI'19.
  • Schneider, J., Di Mitri, D., Drachsler, H. (2019) Best Demonstration Award at LAK19 with "Multimodal Tutor Builder Kit".
  • Di Mitri, D. (2018, 9 September) Martin Wolpers Award to the most young promising researcher at the 14th EATEL Summer School on Technology-Enhanced Learning.  Martin Wolpers’ Award, funded by Research Institute for Innovation & Technology in Education (UNIR iTED) at Universidad Internacional de La Rioja.

9. Teaching activities

  • November 2020 - Educational Technologies Seminar 2021 as part of the Computer Science master/bachelor of Goethe University Frankfurt info
  • November 2020 - Praktikum Educational Technologies 2021 as part of the Computer Science master/bachelor of Goethe University Frankfurt info
  • September 2020 - Human AI virtual Masterclass event 
  • February 2019 - ICT-ILO Course on Multimodal Learning Experiences as part of the Learning Analytics course

10. Interviews

  • March 2019 - Hackademia Podcast Interview - What are Multimodal Learning Analytics?

11. Reviewer roles

Conferences

  • Learning Analytics & Knowledge conference (LAK'17) 2017
  • Learning Analytics & Knowledge conference (LAK'18) 2018
  • Learning Analytics & Knowledge conference (LAK'19) 2019
  • Learning Analytics & Knowledge conference (LAK'20) 2020
  • Learning Analytics & Knowledge conference (LAK'20) 2021
  • Technology Enhanced Learning Conference (EC-TEL'17) 2017
  • Technology Enhanced Learning Conference (EC-TEL'18) 2018
  • Technology Enhanced Learning Conference (EC-TEL'19) 2019
  • Computer-Human Interaction conference (CHI'19) 2019
  • Computer-Human Interaction conference (CHI'20) 2020
  • Artificial Intelligence in Education (AIED'19) 2019
  • Artificial Intelligence in Education (AIED'20) 2020
  • Artificial Intelligence in Education (AIED'20) 2021

List of journals

  • Journal of Computer Assisted Learning, JCAL 2018 Special Issue
  • Transaction on Learning Technologies 2019, 2020
  • British Journal of Education Technologies
  • Journal of Learning Analytics
  • PLOS ONE
  • IEEE Transactions on Cognitive and Developmental Systems
  • International Journal of Serious Games IJSG 2019