Dmitry Abbakumov
Welcome to my webpage! My name is Dmitry Abbakumov. I am a psychometrician and data scientist. I hold a PhD in psychometrics and methodology of educational sciences from KU Leuven, Belgium. After the doctorate in 2019, I have started up the Open Lab for Psychometrics of Digital Learning and now I am working as a PI there. In addition, I am leading a psychometric team at eLearning Office at HSE University in Russia.
My professional mission is to help universities and EdTech companies improving digital learning products by providing them with the (advanced psychometric) analysis of behavioral data collected by platforms and applications, which evidently shows when and why these products do or do not work.
On this website, you can find my CV, publications, and information on projects I and my collaborators are working on. You can contact me at mailbox@abbakumov.com.
Current Research
Creating an explanatory psychometric network of difficulties and problems of digital learners
The network will relate a certain difficulty, for instance, a specific set of mistakes in an assessment, to learners’ previous experience in a course. The network will show course developers whether the difficulty is systematic, for instance, content-driven, or just a random one. Random difficulties are not a problem for pedagogy cause they do not have substantial causes behind. For the systematic difficulties, the psychometric network will trace back to the source of the difficulty and therefore will help to fix the content. Therefore, the psychometric network may serve as an intellectual helper for course developers aimed at improving digital content and providing learners’ the best learning experience. By a product of this project, we will prepare a research paper(s), and an open analytic tool available globally.
Preprints
Abbakumov, D., Kravchenko, D., Kuskin, W., & Urban, A. (2020). How rewatching video lectures impacts students’ performance in assessments in MOOCs. https://doi.org/10.35542/osf.io/vcd5g
Presentations
Abbakumov, D. (2020, July). Combining explanatory IRT and psychological networks for understanding and modeling online learners’ difficulties. International Meeting of the Psychometric Society, Virtual. PDF
Publications
Preprints
Abbakumov, D., Kravchenko, D., Kuskin, W., & Urban, A. (2020). How rewatching video lectures impacts students’ performance in assessments in MOOCs. https://doi.org/10.35542/osf.io/vcd5g
Published
Kravchenko D., Bleskina I., Kalyaeva E., Zemlyakova E., & Abbakumov D. (2020). Personalization in education: from programmed to adaptive learning. Journal of Modern Foreign Psychology, 9(3), 34-46. PDF (in russian)
Abbakumov, D., Desmet, P., & Van den Noortgate, W. (2020). Psychometrics of MOOCs: Measuring learners’ proficiency. Psychologica Belgica, 60(1), 115-131. PDF
Abbakumov, D., Desmet, P., & Van den Noortgate, W. (2020). Rasch model extensions for enhanced formative assessments in MOOCs. Applied Measurement in Education, 33(2), 113-123. PDF
Abbakumov, D., Desmet, P., & Van den Noortgate, W. (2019). Measuring growth in students’ proficiency in MOOCs: Two component dynamic extensions for the Rasch model. Behavior Research Methods, 51(1), 332-341. PDF
Abbakumov, D., Desmet, P., & Van den Noortgate, W. (2018). Measuring student’s proficiency in MOOCs: Multiple attempts extensions for the Rasch model. Heliyon, 4(12), 1-15. PDF
Abbakumov, D., & Lebedeva, M. (2016). Russian as a foreign language grammar and vocabulary placement test: Design, pilot test, and psychometric analysis. Russian Language Abroad, 5, 70-75. PDF (in russian)
Abbakumov, D. (2011). Comparing the effectiveness of verbal and numerical tests for predicting results of employees’ productivity. Organizational Psychology, 1(2), 92-99. PDF (in russian)
Doctoral Dissertation
Psychometrics of MOOCs: How to Measure Proficiency?
Supervisor: Prof. Dr. Wim Van den Noortgate, Co-supervisor: Prof. Dr. Piet Desmet
Date of Public Defense: 13 September 2019
Summary English PDF | Dutch PDF
Chapter 1. Introduction PDF
Chapter 2. Measuring students’ proficiency in MOOCs: Multiple attempts extensions for the Rasch model PDF
Chapter 3. Measuring growth in students’ proficiency in MOOCs: Two component dynamic extensions for the Rasch model PDF
Chapter 4. Rasch model extensions for enhanced formative assessments in MOOCs PDF
Chapter 5. Measuring students’ activity in MOOCs using a Rasch model extension PDF
Chapter 6. Psychometrics of MOOCs: Measuring learners’ proficiency PDF
References PDF
Full Text PDF
Selected International Talks
Abbakumov, D. Ensuring the validity of data and the validity of predictions in digital learning. Times Higher Education Virtual Digital Transformation Forum, Virtual, 2020
Abbakumov, D. Combining explanatory IRT and psychological networks for understanding and modeling online learners’ difficulties. International Meeting of the Psychometric Society, Virtual, 2020 PDF
Abbakumov, D. Measuring student’s activity in MOOCs using extensions of the Rasch model. International Meeting of the Psychometric Society, Santiago, Chile, 2019 PDF
Abbakumov, D. Learners’ activity in MOOCs from a psychometric perspective. Coursera Partners Conference, London, the UK, 2019 PDF
Abbakumov, D. Measuring student’s proficiency in MOOCs: Multiple attempts extensions for the Rasch model. International Meeting of the Psychometric Society, New York, USA, 2018 PDF
Abbakumov, D. Measuring student’s proficiency in MOOCs: Multiple attempts IRT extensions. Coursera Partners Conference, Tempe, USA, 2018
Abbakumov, D. Measuring the impact of video lectures on learner’s productivity. Coursera Partners Conference, Boulder, USA, 2017
Abbakumov, D. Interest and interestingness: The new perspective on students and content. Coursera Partners Conference, the Hague, the Netherlands, 2016
Abbakumov, D. Psychometrics of MOOCs: The basics. EduLab, Rome, Italy, 2016
Abbakumov, D. Computerized adaptive testing algorithm for summative assessment. Computerized Adaptive Testing Summit, Princeton, USA, 2014
