PhD vacancy at Lambda-Lab!

The Lambda-Lab currently has a PhD-student vacancy at the intersection of information retrieval and large-scale online learning. Apply by January 31, 2017. More details can be found in the vacancy text (pdf).

Recent & Upcoming Activities

  • March 2017: Our paper, in collaboration with René Kizilcec from Stanford's Lytics Lab, "Follow the Successful Crowd: Raising MOOC Completion Rates through Social Comparison at Scale" will appear at the 7th International Conference on Learning Analytics and Knowledge, LAK ’17. 
  • January 2017 Dan Davis presented our research on interventions facilitating social comparison in MOOCs at the Massachusetts Institute of Technology (MIT) STEP Lab in the Office of Digital Learning
  • November 2016 Claudia Hauff has been awarded an NWO Top Grant for her proposal on large-scale collaborative search in the domain of online learning. This personal grant will fund one 4-year PhD position. Details on the project can be found in her blog.
  • November 2016 Guanliang Chen, Dan Davis and Geert-Jan Houben were at the edx Global Forum in Paris.

  • October 2016 Claudia Hauff gave a talk about our MOOC research at the Data Science Northeast Netherlands meetup (slides).

  • October 2016 Claudia Hauff was at Learning with MOOCS III and talked about our work on linking MOOC learners across Web platforms (take a look at the slides).

  • September 2016: Our journal article in collaboration with Markus Krause from ICSI/Berkeley "Can Learners be Earners? Investigating a Design to Enable MOOC Learners to Apply their Skills and Earn Money in an Online Market Place" was accepted at IEEE Transactions on Learning Technologies. 
  • September 2016 Ioana Jivet successfully defended her Master thesis on how to improve self-regulation behaviour of MOOC learners. 
  • September 2016 Our paper, Retrieval Practice and Study Planning in MOOCs: Exploring Classroom-Based Self-Regulated Learning Strategies at Scale received the EC-TEL 2016 Best Student Paper Award.
  • September 2016 Lambda-Lab members contributed to two full papers that will be presented at ECTEL 2016: (1) Inferring student attention with ASQ, and (2) Retrieval Practice and Study Planning in MOOCs: Exploring Classroom-Based Self-Regulated Learning Strategies at Scale. Dan Davis was at the conference.
  • September 2016 Claudia Hauff joined a panel discussion on the impact of MOOCs at the TU Delft event celebrating 1 Million MOOC enrollments.
    • August 2016 Dan Davis presented our work on the analysis of learning pathways through MOOCs to HarvardX & Harvard's Vice Provost for Advances in Learning (VPAL) group at Harvard University and to Professor Neil Heffernan's ASSISTments Lab at the Worcester Polytechnic Institute.


    The Online Education Research program at TU Delft targets the elements of online education that align with Delft research strengths and allow us to support the next generation of online education - not just in Delft (as EdX partner we are at the forefront of the current drive towards MOOCs), but beyond.  With bringing education online and doing so at unprecedented scales, the role of technology in online education and its research is showing a paradigm shift. The nature and volume of learning data, the interaction between students and educators, and the interaction between all stakeholders in education change, and as a consequence the relevant research becomes more data-driven and computational

    Our Mission

    We as "Lambda-Lab" (part of the Web Information Systems group) contribute to this research team and focuses on Learner Modeling and Learning Analytics.

    Analyzing the large amount of digital traces learners leave within and outside the online learning environment such as EdX offers the possibility to adapt the environment itself, the teaching material and the manner of conveying knowledge to the individual learners' abilities and preferences. Relying on research methodologies developed across diverse fields such as educational psychology, human-centered design, data science and big data processing, we investigate three main questions within the learning analytics theme:

    • How is the design of the learning environment related to students' engagement and achievement in open online higher education?
    • Digital learning environments do not exist in isolation, they are embedded in the rich infrastructure of the Web. Learners regularly seek out additional materials available elsewhere on various portals, educational websites, etc. Moreover, we can seek out the learners' themselves on the social Web, inferring and building knowledge about them.  To what extent do these external sources enable us to explain and improve students' engagement and achievement?
    • Commonly, to analyze educational traces, adhoc pipelines are used that are specific to a particular use case. We envision to create a generic platform for conducting analytical tasks with large-scale traces that allow us to build not only research prototypes but also actual applications that make use of the analytics results.

    Researchers Involved

    Several researchers of the WIS group contribute to this research line:

    • Guanliang Chen: the focus of his PhD research is learner analytics beyond the MOOC platform, funded by TU Delft's Extension School.
    • Dan Davis' PhD research is centered around the impact of the online learning environment on learners and learning, funded as part of CEL.
    • Yue Zhao recently shifted his PhD focus to MOOCs as well, employing data analytics to make sense of MOOC learners' behaviour.
    • Claudia Hauff is Assistant Professor at WIS and the daily supervisor of the MSc and PhD projects within this research line.
    • Geert-Jan Houben is the head of WIS and provides expertise in user modeling and Web systems.

    as well as a number of Master students:

    • Ioana Jivet explored how to increase self-regulation in MOOC learners through the use of an interactive learning tracker. She defended her thesis in September 2016.  Currently, Ioana is working as a PhD student at the Welten-instituut.
    • Yingying Bao currently investigates the prevalence of cheating in MOOCs.
    • Jochem de Goede works on a workbench to increase the reproducibility of MOOC experiments.

    Overview of our Work

    To get a quick overview of the kind of questions we have looked at in the past year(s), take a look at the slides, they capture the essence of our approach and each of our publications in 1-2 slides.


    • Chen, G., Davis, D., Krause, M., Aivaloglou, E., Hauff, C. & Houben, G.J. (2016, September).  Can Learners be Earners? Investigating a Design to Enable MOOC Learners to Apply their Skills and Earn Money in an Online Market Place. In IEEE Transactions on Learning Technologies (accepted as regular article).

    • Triglianos, V., Pautasso, C., Bozzon, A., Hauff, C. (2016, September).  Inferring student attention with ASQ. In Proceedings of the 11th European Confernece on Technology Enhanced Learning (pp. 306-320). [Proceedings link]

    • Davis, D., Chen, G., van der Zee, T., Hauff, C. & Houben, G.J. (2016, September).  Retrieval Practice and Study Planning in MOOCs: Exploring Classroom-Based Self-Regulated Learning Strategies at Scale. In Proceedings of the 11th European Confernece on Technology Enhanced Learning (pp. 57-71). It received the Best Student Paper Award. [Proceedings link]

    • Davis, D., Chen, G., Hauff, C. & Houben, G.J. (2016, June). Gauging MOOC Learners’ Adherence to the Designed Learning Path. In Proceedings of the 9th International Conference on Educational Data Mining (pp. 54-61). [Proceedings link]

    • Chen, G., Davis, D., Hauff, C. & Houben, G.J. (2016, July). On the Impact of Personality in Massive Open Online Learning. In Proceedings of the 24th Conference on User Modeling, Adaptation and Personalization (pp. 121-130). [Proceedings link]

    • Chen, G., Davis, D., Lin, J., Hauff, C. & Houben, G.J. (2016, May). Beyond the MOOC platform: Gaining Insights about Learners from the Social Web. In Proceedings of the 8th International ACM Web Science Conference (pp. 15-24). ACM. [Proceedings link]

    • Chen, G., Davis, D., Hauff, C., & Houben, G. J. (2016, April). Learning Transfer: Does It Take Place in MOOCs? An Investigation into the Uptake of Functional Programming in Practice. In Proceedings of the Third (2016) ACM Conference on Learning@ Scale (pp. 409-418). ACM. Best Paper Nominee. [Proceedings link]

    • Davis, D., Chen, G., Jivet, I., Hauff, C. & Houben, G.J. (2016, April). Encouraging Metacognition & Self-Regulation in MOOCs through Increased Learner Feedback. Presented at the Learning Analytics for Learners workshop, co-located with LAK 2016. [PDF]