Publications
2025
Scholarly publications
Ruijer, E., Brinkhuis, M., & Hassink, W. (Accepted/In press). Towards a framework for digital governance curricula: what skills and knowledge do governance students need? Information Polity. [DOI]
van Grinsven, M., Brinkhuis, M., Krempl, G., & Snijder, J. (2025). Efficient and General Text Classification: An Active Learning Approach Using Active Learning and NLP to Aid Processes Such as Journalistic Investigations And document Analysis. In R. Meo, & F. Silvestri (Eds.), Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Revised Selected Papers (pp. 105-120). (Communications in Computer and Information Science; Vol. 2134 CCIS). Springer. [DOI] [Portal]
2024
Scholarly publications
van Haastrecht, M., Brinkhuis, M., & Spruit, M. (2024). Federated Learning Analytics: Investigating the Privacy-Performance Trade-Off in Machine Learning for Educational Analytics. In A. M. Olney, I.-A. Chounta, Z. Liu, O. C. Santos, & I. I. Bittencourt (Eds.), Artificial Intelligence in Education - 25th International Conference, AIED 2024, Proceedings (pp. 62-74). Article 14830 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14830 LNAI). Springer. [DOI] [Portal]
Maas, L., Madison, M. J., & Brinkhuis, M. J. S. (2024). Properties and performance of the one-parameter log-linear cognitive diagnosis model. Frontiers in Education, 9, Article 1287279. [DOI] [Repository]
2023
Scholarly publications
Ferguson, R., Khosravi, H., Kovanović, V., Viberg, O., Aggarwal, A., Brinkhuis, M., Shum, S. B., Chen, L. K., Drachsler, H., Guerrero, V. A., Hanses, M., Hayward, C., Hicks, B., Jivet, I., Kitto, K., Kizilcec, R., Lodge, J. M., Manly, C. A., Matz, R. L., ... Yan, V. X. (2023). Aligning the Goals of Learning Analytics with its Research Scholarship: An Open Peer Commentary Approach. Journal of Learning Analytics, 10(2), 14-50. [DOI] [Repository]
van Haastrecht, M., Brinkhuis, M., Wools, S., & Spruit, M. (2023). VAST: a practical validation framework for e-assessment solutions. Information Systems and e-Business Management, 21(3), 603-627. [DOI] [Repository]
Toledo, C. V., Schraagen, M., Dijk, F. V., Brinkhuis, M., & Spruit, M. (2023). Readability Metrics for Machine Translation in Dutch: Google vs. Azure & IBM. Applied Sciences, 13(7), 1-14. Article 4444. [DOI] [Repository]
Dijk, F. V., Gadellaa, J., Toledo, C. V., Spruit, M., Brinkkemper, S., & Brinkhuis, M. (2023). Uncovering the structures of privacy research using bibliometric network analysis and topic modelling. Organizational Cybersecurity Journal: Practice, Process and People. [DOI] [Repository]
Haastrecht, M. V., Brinkhuis, M., Peichl, J., Remmele, B., & Spruit, M. (2023). Embracing Trustworthiness and Authenticity in the Validation of Learning Analytics Systems. In LAK23: 13ᵗʰ International Learning Analytics and Knowledge Conference (LAK 2023) (pp. 552-558). Association for Computing Machinery. [DOI] [Repository]
van der Werf, J. M. E. M., Polyvyanyy, A., van Wensveen, B. R., Brinkhuis, M., & Reijers, H. A. (2023). All that glitters is not gold: Four maturity stages of process discovery algorithms. Information Systems, 114, Article 102155. [DOI] [Repository]
2022
Scholarly publications
van Toledo, C., Schraagen, M., van Dijk, F. W., Brinkhuis, M., & Spruit, M. (2022). Exploring the Utility of Dutch Question Answering Datasets for Human Resource Contact Centres. Information, 13(11), 1-11. Article 513. [DOI] [Repository]
van Haastrecht, M., Golpur, G., Tzismadia, G., Kab, R., Priboi, C., David, D., Răcătăian, A., Baumgartner, L., Fricker, S., Ruiz, J. F., Armas, E., Brinkhuis, M., & Spruit, M. (2022). Correction: van Haastrecht et al. A Shared Cyber Threat Intelligence Solution for SMEs. Electronics 2021, 10, 2913. Electronics (Switzerland), 11(3), 1-1. Article 349. [DOI] [Portal]
Domingue, B. W., Kanopka, K., Stenhaug, B., Sulik, M. J., Beverly, T., Brinkhuis, M., Circi, R., Faul, J., Liao, D., Mccandliss, B., Obradović, J., Piech, C., Porter, T., Consortium, P. I., Soland, J., Weeks, J., Wise, S. L., & Yeatman, J. (2022). Speed–Accuracy Trade-Off? Not So Fast: Marginal Changes in Speed Have Inconsistent Relationships With Accuracy in Real-World Settings. Journal of Educational and Behavioral Statistics, 47(5), 576-602. [DOI] [Repository]
Bolsinova, M., Brinkhuis, M. J. S., Hofman, A. D., & Maris, G. (2022). Tracking a multitude of abilities as they develop. British Journal of Mathematical and Statistical Psychology, 75(3), 753-778. [DOI] [Repository]
Maas, L., Brinkhuis, M., Kester, L., & Wijngaards, L. (2022). Cognitive diagnostic assessment in university statistics education: Valid and reliable skill measurement for actionable feedback using learning dashboards. Applied Sciences, 12(10), 1-19. Article 4809. [DOI] [Repository]
Maas, L., Brinkhuis, M., Kester, L., & Wijngaards, L. (2022). Diagnostic classification models for actionable feedback in education: Effects of sample size and assessment length. Frontiers in Education, 7, 1-17. Article 802828. [DOI] [Repository]
Bolsinova, M., Maris, G., Hofman, A. D., van der Maas, H. L. J., & Brinkhuis, M. J. S. (2022). Urnings: A new method for tracking dynamically changing parameters in paired comparison systems. Journal of the Royal Statistical Society. Series C: Applied Statistics, 71(1), 91-118. [DOI] [Repository]
2021
Scholarly publications
van Haastrecht, M., Golpur, G., Tzismadia, G., Kab, R., Priboi, C., David, D., Răcătăian, A., Brinkhuis, M., & Spruit, M. (2021). A shared cyber threat intelligence solution for smes. Electronics (Switzerland), 10(23), 1-21. Article 2913. [DOI] [Repository]
van der Werf, J. M. E. M., Polyvyanyy, A., van Wensveen, B. R., Brinkhuis, M. J. S., & Reijers, H. A. (2021). All that Glitters Is Not Gold: Towards Process Discovery Techniques with Guarantees. In M. La Rosa, S. Sadiq, & E. Teniente (Eds.), Advanced Information Systems Engineering: 33rd International Conference, CAiSE 2021, Melbourne, VIC, Australia, June 28 – July 2, 2021, Proceedings (1 ed., pp. 141-157). (Lecture Notes in Computer Science; Vol. 12751). Springer. [DOI] [Portal]
Dijk, F. V., Toledo, C. V., Spruit, M., & Brinkhuis, M. J. S. (2021). Pillars of Privacy: Identifying Core Theory in a Network Analysis of Privacy Literature. In ECIS 2021 Research Papers Article 1420 AIS Electronic Library (AISeL). https://aisel.aisnet.org/ecis2021_rp/84
van Haastrecht, M., Yigit Ozkan, B., Brinkhuis, M., & Spruit, M. (2021). Respite for SMEs: A Systematic Review of Socio-Technical Cybersecurity Metrics. Applied Sciences, 11(15), 1-28. Article 6909. [DOI] [Repository]
Vida, L. J., Brinkhuis, M. J. S., & Bolsinova, M. (2021). Speeding up without Loss of Accuracy: Item Position Effects on Performance in University Exams. In Proceedings of the 14th International Conference on Educational Data Mining https://educationaldatamining.org/EDM2021/virtual/poster_paper225.html [Repository]
van Haastrecht, M., Sarhan, I., Yigit Ozkan, B., Brinkhuis, M., & Spruit, M. (2021). SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing. Frontiers in Research Metrics and Analytics, 6, 1-14. Article 685591. [DOI] [Repository]
2020
Scholarly publications
van der Werf, J. M. E. M., Polyvyanyy, A., Wensveen, B. R. V., Brinkhuis, M., & Reijers, H. A. (2020). All That Glitters Is Not Gold: Towards Process Discovery Techniques with Guarantees. (pp. 1-13). arXiv. [DOI] [Repository]
Domingue, B., Kanopka, K., Stenhaug, B., Sulik, M., Beverly, T., Brinkhuis, M. J. S., Circi, R., Faul, J., Liao, D., McCandliss, B., Obradovic, J., Piech, C., Porter, T., Soland, J., Weeks, J., Wise, S., & Yeatman, J. D. (2020). Speed accuracy tradeoff? Not so fast: Marginal changes in speed have inconsistent relationships with accuracy in real-world settings. PsyArXiv. [DOI] [Repository]
Brinkhuis, M. J. S., Cordes, W., & Hofman, A. D. (2020). Governing games: Adaptive game selection in the Math Garden. In D. Ivanovic (Ed.), ITM Web Conf.: International Conference on ICT enhanced Social Sciences and Humanities (ICTeSSH 2020) (Vol. 33). Article 03003 EDP Sciences. [DOI] [Repository]
Omta, W., van Heesbeen, R., Shen, Z., de Nobel, J., van der Velden, L., Medema, R., Siebes, A., Feelders, A., Brinkkemper, S., Klumperman, J., Spruit, M., Brinkhuis, M., & Egan, D. (2020). Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening. SLAS Discovery, 25(6), 655–664. [DOI] [Repository]
Maris, G., Bolsinova, M., Hofman, A. D., van der Maas, H. L. J., & Brinkhuis, M. J. S. (2020). Urnings: A new method for tracking dynamically changing parameters in paired comparison systems. Open Science Framework. [DOI] [Repository]
Hofman, A. D., Brinkhuis, M. J. S., Bolsinova, M., Klaiber, J., Maris, G., & van der Maas, H. L. J. (2020). Tracking with (Un)certainty. Journal of Intelligence, 8(1), Article 10. [DOI] [Repository]
Brinkhuis, M. J. S., & Maris, G. (2020). Dynamic estimation in the extended marginal Rasch model with an application to mathematical computer-adaptive practice. British Journal of Mathematical and Statistical Psychology, 73(1), 72-87. [DOI] [Repository]
Omta, W., Heesbeen, R. V., Shen, I., Feelders, A., Brinkhuis, M., Egan, D., & Spruit, M. (2020). PurifyR: an R Package for highly automated reproducible variable extraction and standardization. Families, Systems and Health, 3(1), 1-7. [DOI] [Repository]
Niemeijer, K., Feskens, R., Krempl, G., Koops, J., & Brinkhuis, M. J. S. (2020). Constructing and Predicting School Advice for Academic Achievement: A Comparison of Item Response Theory and Machine Learning Techniques. In Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20) (pp. 462-471). Article 15 Association for Computing Machinery. [DOI], [DOI] [Repository]
2019
Scholarly publications
Brinkhuis, M. J. S., & Maris, G. (2019). Tracking Ability: Defining Trackers for Measuring Educational Progress. In B. P. Veldkamp, & C. Sluijter (Eds.), Theoretical and Practical Advances in Computer-based Educational Measurement (pp. 161). (Methodology of Educational Measurement and Assessment). Springer. [DOI] [Portal]
De Jong, P., Van Der Werf, J. M. E. M., Van Steenbergen, M., Bex, F., & Brinkhuis, M. (2019). Evaluating Design Rationale in Architecture. In 2019 IEEE International Conference on Software Architecture: proceedings, 25-29 March 2019, Hamburg, Germany (pp. 145-152). Article 8712158 IEEE. [DOI] [Portal]
2018
Scholarly publications
van der Waa, J., Robeer, M., van Diggelen, J., Brinkhuis, M., & Neerincx, M. (2018). Contrastive Explanations with Local Foil Trees. [DOI]
Brinkhuis, M. J. S., Savi, A. O., Coomans, F., Hofman, A. D., van der Maas, H. L. J., & Maris, G. (2018). Learning As It Happens: A Decade of Analyzing and Shaping a Large-Scale Online Learning System. Journal of Learning Analytics, 5(2), 29-46. [DOI] [Repository]
Sosnovsky, S., Müter, L., Valkenier, M., Brinkhuis, M., & Hofman, A. (2018). Detection of Student Modelling Anomalies. In Lifelong Technology-Enhanced Learning - 13th European Conference on Technology Enhanced Learning, EC-TEL 2018, Proceedings (pp. 531-536). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11082 LNCS). Springer. [DOI] [Portal]
2017
Scholarly publications
Kos, W., Schraagen, M. P., Brinkhuis, M. J. S., & Bex, F. J. (2017). Classification in a Skewed Online Trade Fraud Complaint Corpus. In B. Verheij, & M. Wiering (Eds.), Preproceedings of the 29th Benelux Conference on Artificial Intelligence November 8–9, 2017 in Groningen, The Netherlands: BNAIC 2017 (pp. 172-183) [Repository]
Schraagen, M. P., Brinkhuis, M. J. S., & Bex, F. J. (2017). Evaluation of Named Entity Recognition in Dutch Online Criminal Complaints. Unpublished. In ICAIL 2017 workshop on Discovery of Electronically Stored Information (DESI VII) [Repository]
Omta, W. A., de Nobel, J., Klumperman, J., Egan, D. A., Spruit, M. R., & Brinkhuis, M. J. S. (2017). Improving Comprehension Efficiency of High Content Screening Data Through Interactive Visualizations. Assay and Drug Development Technologies, 15(6), 247-256. [DOI] [Repository]
Schraagen, M. P., Brinkhuis, M. J. S., & Bex, F. J. (2017). Evaluation of Named Entity Recognition in Dutch online criminal complaints. Computational Linguistics in the Netherlands Journal, 7, 3-16. https://clinjournal.org/clinj/article/view/65 [Repository]
2016
Scholarly publications
Coomans, F., Hofman, A., Brinkhuis, M., Van Der Maas, H. L. J., & Maris, G. (2016). Distinguishing fast and slow processes in accuracy - Response time data. PLoS One, 11(5), Article e0155149. [DOI]
2015
Scholarly publications
Brinkhuis, M. J. S., Bakker, M., & Maris, G. (2015). Filtering Data for Detecting Differential Development: Detecting Differential Development. Journal of Educational Measurement, 52(3), 319-338. [DOI]
2014
Scholarly publications
2012
Scholarly publications
Hox, J. J., De Leeuw, E. D., Brinkhuis, M. J. S., & Ooms, J. (2012). Multigroup and multilevel approaches to measurement equivalence. In S. Salzborn, E. Davidov, & J. Reinecke (Eds.), Methods, Theories, and Empirical Applications in the Social Sciences (pp. 91-96). Springer. [DOI]
2010
Scholarly publications
Hox, J. J., De Leeuw, E. D., & Brinkhuis, M. J. S. (2010). Analysis models for comparative surveys. In J. Harkness, M. Braun, B. Edwards, T. Johnson, L. Lyberg, P. Mohler, B. E. Pennell, & T. W. Smith (Eds.), Survey Methods in Multicultural, Multinational, and Multiregional Context (pp. 395-418). Wiley.