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 investigating and explaining how these products work using the (advanced psychometric) analysis of behavioral data collected by platforms and applications.

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.

Publications

Published

Abbakumov, D., Desmet, P., & Van den Noortgate, W. (in press). Rasch model extensions for enhanced formative assessments in MOOCs. Applied Measurement in Education.

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)

Under review

Abbakumov, D., Desmet, P., & Van den Noortgate, W. Psychometrics of MOOCs: Measuring learners’ proficiency.

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

Measuring student’s activity in MOOCs using extensions of the Rasch model. International Meeting of the Psychometric Society, Santiago, Chile, 2019 PDF

Learners’ activity in MOOCs from a psychometric perspective. Coursera Partners Conference, London, the UK, 2019 PDF

Measuring student’s proficiency in MOOCs: Multiple attempts extensions for the Rasch model. International Meeting of the Psychometric Society, New York, USA, 2018 PDF

Measuring student’s proficiency in MOOCs: Multiple attempts IRT extensions. Coursera Partners Conference, Tempe, USA, 2018

Measuring the impact of video lectures on learner’s productivity. Coursera Partners Conference, Boulder, USA, 2017

Interest and interestingness: The new perspective on students and content. Coursera Partners Conference, the Hague, the Netherlands, 2016

Psychometrics of MOOCs: The basics. EduLab, Rome, Italy, 2016

Computerized adaptive testing algorithm for summative assessment. Computerized Adaptive Testing Summit, Princeton, USA, 2014

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