The Eindhoven University of Technology (The Netherlands) offer a fully funded position for a Ph.D. student in the project „Learning Analytics in blended learning: Translating numbers into learning improvements“ (4 years) within the Human-Technology Interaction Group of the School of Innovation Sciences (IS).
The project is part of the TU/e 2030 Strategy which aims at leveraging digitization for creating personal learning paths and serving more diverse groups of learners. We aim at creating learning analytics models that predict students’ learning success or failure, self-regulated learning capabilities, study engagement, and other characteristics that can be used to improve teaching and learning. A sub-question is how early we can build such models in ongoing courses so that early warning and feedback systems can be created. Also, the consequences of planned educational interventions based on the Learning Management System data either in the class or online are relevant. We will use educational theories in field experiments to test whether specific educational designs increase student capabilities and learning outcomes. For a sample of students, we will collect survey data for additional measurement and to create predictive models for (amongst other things) students’ learning styles, students’ self-regulated learning capabilities, study crafting, study engagement, burnout, and academic performance.
The selected candidate will work within the Human-Technology Interaction Group within the department of Industrial Engineering and Innovation Science at Eindhoven University of Technology under the supervision of Dr. U. Matzat, Dr. Ir. A. Kleingeld (Human Performance Management group), and Prof. dr. C. Snijders. The applicant will access large databases and mine and analyze these data, taking into account the insights of learning theories. In addition, the applicant will administer surveys and perform (online) experiments. Findings will be presented at (international) conferences and written up for publication in scientific journals.
The applicant should have:
- A MSc degree, or equivalent, in Psychology, Sociology, Educational Science, Statistics, Economics, Computer Science, or a related field, completed by the start date of the PhD project
- A demonstrable interest in the topics studied in the project.
- Strong programming skills; experience in database programming is appreciated
- A good understanding of applied statistics.
- Experience with performing scientific research in the social & behavioral sciences
- Fluency in written and spoken English language.
The project will start May 1st, but a later starting date can be negotiated. Interviews will start taking place in February and March. At this time screening starts immediately, when we have found a suitable candidate we will close the vacancy so we advise you to apply a.s.a.p., but no later than March 1.
To apply please visit the official TU/e website describing the vacancy in more detail: