dr. G. Sedrakyan (Gayane)

Assistant Professor

Over mij

I obtained my PhD in Business Economics focusing on information systems, model-driven engineering, behavior / process analytics. My research interests include code generation (soft/web, backend/frontend/UI) to support simulation/testability, semantic/syntactic validation of business requirements represented as models (UML/XML/text) and process- / behavior- analytics based recommendation/feedback automation. My current teaching areas include Business Intelligence topics (e.g. BI methodologies, Business analytics, visual analytics dashboards, business performance management, process analytics) as well as low code application development. I am also interested in expanding my domain towards a broader context of data analytics including but not limited to NLP; machine learning, explainable AI.


Learning Process
Engineering & Materials Science
Social Sciences
Learning Behavior


Current research topics / projects

  • How educational feedback needs changed during the times of Covid pandemics and what are the long-term effects?
  • TeToMoCo: The goal of the project is three-fold: 1. TeToMo framework that combines the state-of-the-art natural language processing approaches and techniques for identifying potential architecture elements candidates out of textual descriptions (business requirements). 2. A subsequent prototype implementation that can assist a knowledge construction process through (semi-) automatic generation and validation of UML models. 3. Automatic web application generation (backend/frontend/UI) out of generated UML/XML models following principles of Model Driven Engineering


Sedrakyan, G., Abdi, A. , van den Berg, S. M. , Veldkamp, B. P. , & van Hillegersberg, J. (2022). Text-To-Model (TeToMo) Transformation Framework to Support Requirements Analysis and Modeling. In Proceedings of the 10th International Conference on Model-Driven Engineering and Software Development - MODELSWARD (pp. 129-136). SCITEPRESS. https://doi.org/10.5220/0010771600003119
Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A. (2020). Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation. Computers in human behavior, 107, [105512]. https://doi.org/10.1016/j.chb.2018.05.004
Sedrakyan, G., Dannerlein, S., Pammer-Schindler, V., & Lindstaedt, S. (2020). Measuring learning progress for serving immediate feedback needs: Learning process quantification framework (lpqf). In C. Alario-Hoyos, M. J. Rodríguez-Triana, M. Scheffel, I. Arnedillo-Sánchez, & S. M. Dennerlein (Eds.), Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Proceedings (pp. 443-448). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12315 LNCS). Springer. https://doi.org/10.1007/978-3-030-57717-9_42

Google Scholar Link



Universiteit Twente
Drienerlolaan 5
7522 NB Enschede

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Universiteit Twente
Postbus 217
7500 AE Enschede