Sebastian Gombert

I started to work as a doctoral researcher at the Educational Technologies group, DIPF, in 2021. Before this, I studied Linguistic and Literary Computing at TU Darmstadt. I finished with a thesis on detecting semantic uncertainty in scientific writing using pre-trained transformer language models and conditional random fields. Besides this, I worked as a teaching assistant, software developer and junior research assistant in various contexts and was active in academic self-government. When I am not busy researching, I like producing electronic music, playing the drums and hiking.

• Artificial Intelligence in Education
• Natural Language Processing
• Learning Analytics
• Feedback Generation
• Human-Computer Interaction
• Discourse Semantics
• Cognitive Linguistics

• Master of Arts in Linguistic and Literary Computing, 2021, TU Darmstadt
• Bachelor of Arts in Digital Philology and Computer Science, 2019, TU Darmstadt

• 2014 – Developer @ Sanofi-Aventis Deutschland GmbH
• 2015-2017 – Developer @ Abius GmbH
• 2015-2020 – Co-founder @ mediacollective UG
• 2017 – IT Administrator @ Student Council FB2, TU Darmstadt
• 2016-2021 Teaching- and Junior Research Assistant @ Corpus- and Computational Linguistics, TU Darmstadt
• 2020 Teaching Assistant @ Ubiquitous Knowledge Processing Lab, TU Darmstadt
• 2020-2021 Developer @ AskAlbert / studiumdigitale, Goethe Universität Frankfurt

• Menzel, L., Gombert, S., Weidlich, J., Fink, A., Frey, A., & Drachsler, H. (2023). Why You Should Give Your Students Automatic Process Feedback on Their Collaboration: Evidence from a Randomized Experiment. In Responsive and Sustainable Educational Futures. EC-TEL 2023. Lecture Notes in Computer Science, vol 14200. Springer, Cham. https://doi.org/10.1007/978-3-031-42682-7_14
• 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. In Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12767
• Gombert, S. (2022). Methods and perspectives for the automated analytic assessment of free-text responses in formative scenarios. In Proceedings of the Doctoral Consortium at the Seventeenth European Conference on Technology Enhanced Learning (EC-TEL 2022), Toulouse, France, September 12th-16th, 2022
• Daniele Di Mitri, Sebastian Gombert, & Onur Karademir (2022). Reflecting on the Actionable Components of a Model for Augmented Feedback. In Proceedings of the Second International Workshop on Multimodal Immersive Learning Systems (MILeS 2022) At the Seventeenth European Conference on Technology Enhanced Learning (EC-TEL 2022), Toulouse, France, September 12th-16th, 2022 (pp. 45–50). CEUR-WS.org.
• Böttger, F., Cetinkaya, U., Di Mitri, D., Gombert, S., Shingjergji, K., Iren, D., & Klemke, R. (2022). Privacy-Preserving and Scalable Affect Detection in Online Synchronous Learning. In Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. EC-TEL 2022. Lecture Notes in Computer Science, vol 13450. Springer International Publishing. https://doi.org/10.1007/978-3-031-16290-9_4
• 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 Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. EC-TEL 2022. Lecture Notes in Computer Science, vol 13450. Springer International Publishing. https://doi.org/10.1007/978-3-031-16290-9_37
• Gombert, S. (2021). Twin BERT Contextualized Sentence Embedding Space Learning and Gradient-Boosted Decision Tree Ensembles for Scene Segmentation in German Literature. In Proceedings of the Shared Task on Scene Segmentation co-located with the 17th Conference on Natural Language Processing (KONVENS 2021), Düsseldorf, Germany, September 6th, 2021 (Vol. 3001, pp. 42–48). CEUR-WS.org.
• Gombert, S., & Bartsch, S. (2021). TUDA-CCL at SemEval-2021 Task 1: Using Gradient-boosted Regression Tree Ensembles Trained on a Heterogeneous Feature Set for Predicting Lexical Complexity. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021) (pp. 130-137). Association for Computational Linguistics.
• Gombert, S. & Bartsch, S. (2020). MultiVitaminBooster at PARSEME Shared Task 2020: Combining Window- and Dependency-Based Features with Multilingual Contextualised Word Embeddings for VMWE Detection. In Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons (pp. 149–155). Association for Computational Linguistics.

• Fink, A., Gombert, S., & Frey, A. (2023). Using natural language processing to automate the assessment of student essay content. Paper presented at the Frontier Research in Educational Measurement – FREMO 2023, Oslo, Norway.
• Fink, A., Gombert, S., & Frey, A. (2023). Automatisierte Inhaltsanalyse von Essays mittels Transformern [Automated analysis of essay content using transformer models]. Paper presented at the 16th meeting of the Methods and Evaluation Division of the DGPs, Constance, Germany.
• Gombert, S., & Karademir, O. (2023). KI in der Bildung: Chancen und Risiken für die Gesellschaft. @ Common Purpose.
• Gombert, S., & Kube, D. (2023). Virtueller Kaffeetalk zum Thema ChatGPT in der Bildung. @ Digitaltag 2023.
• Gombert, S., & Menzel, L. (2023). Hyperchalk – How to Implement Self-hosted Whiteboard Tasks. @ Seventeenth EATEL Summer School on Technology Enhanced Learning.
• Gombert, S., Menzel, L., & Di Mitri, D. (2023). Large Language Models for Feedback Generation. @ Seventeenth EATEL Summer School on Technology Enhanced Learning.
• Karademir, O., Gombert, S., & Di Mitri, D. (2023). Teacher Dashboard Supported by AI-generated Feedback. @ Seventeenth EATEL Summer School on Technology Enhanced Learning.
• Di Mitri, D., Schmitz, M., Jivet, I., Gombert, S., Ahmad, A., Drachsler, H. (2023). Hi, LA! – Highly Informative Learning Analytics. @ 13th International Learning Analytics and Knowledge Conference.
• Fink, A., Frey, A., Liu, T., & Gombert, S. (2022). Nutzung von Natural Language Processing zur automatisierten Kodierung von Essays in digital gestützten Großveranstaltungen an Hochschulen. @ 52nd Conference of the German Psychological Society (DGPs).
• Gombert, S. (2022). Workshop: Assessing constructed responses with explainable natural language processing. @ Sixteenth EATEL Summer School on Technology Enhanced Learning.
• Gombert, S., Bhattacharya, S., Di Mitri, D., Drachsler, H. (2022). Interpretierbare maschinelle Sprachverarbeitung für die Identifikation konzeptionellen Wissens in energiephysikbezogenen deutschsprachigen Kurzantworten. @ Symposium: Komplexität nicht nur bewältigen, sondern zu Nutze machen: Log- und Textdaten im Educational Assessment. 9. Tagung der Gesellschaft für Empirische Bildungsforschung.