Matthieu Brinkhuis
Biographic Data
| ID | 6839618 |
|---|---|
| NAME | Matthieu Brinkhuis |
| GIVEN NAMES | Matthieu |
| FAMILY NAME | Brinkhuis |
| SIGNATURE | BRINKHUIS M |
| AFFILIATIONS | Utrecht University |
| ORCID | 0000-0003-1054-6683 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Towards a Framework for Digital Governance Curricula: What Skills and Knowledge do Governance Students Need
Digital technologies are rapidly becoming deeply entrenched in society. These technologies provide challenges and opportunities for democratic and organizational processes, and social interactions between governments and citizens. In this study, we focus on the skills governance students need to obtain to fully grasp the opportunities and challenges raised by digitalization in the public sector and society at large. Using a design approach, we fi…
Properties and performance of the one-parameter log-linear cognitive diagnosis model
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due to useful measurement properties like sum score sufficiency and invariance properties. We demonstrat…
Understanding validity criteria in technology-enhanced learning: A systematic literature review
Technological aids are ubiquitous in today's educational environments. Whereas much of the dust has settled in the debate on how to validate traditional educational solutions, in the area of technology-enhanced learning (TEL) many questions still remain. Technologies often abstract away student behaviour by condensing actions into numbers, meaning teachers have to assess student data rather than observing students directly. With the rapid adoptio…
Diagnostic Classification Models for Actionable Feedback in Education: Effects of Sample Size and Assessment Length
E-learning is increasingly used to support student learning in higher education. This results in huge amounts of item response data containing valuable information about students’ strengths and weaknesses that can be used to provide effective feedback to both students and teachers. However, in current practice, feedback in e-learning is often given in the form of a simple proportion of correctly solved items rather than diagnostic, actionable fee…
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Diagnostic Classification Models for Actionable Feedback in Education: Effects of Sample Size and Assessment Length
E-learning is increasingly used to support student learning in higher education. This results in huge amounts of item response data containing valuable information about students’ strengths and weaknesses that can be used to provide effective feedback to both students and teachers. However, in current practice, feedback in e-learning is often given in the form of a simple proportion of correctly solved items rather than diagnostic, actionable fee…
Properties and performance of the one-parameter log-linear cognitive diagnosis model
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due to useful measurement properties like sum score sufficiency and invariance properties. We demonstrat…
Understanding validity criteria in technology-enhanced learning: A systematic literature review
Technological aids are ubiquitous in today's educational environments. Whereas much of the dust has settled in the debate on how to validate traditional educational solutions, in the area of technology-enhanced learning (TEL) many questions still remain. Technologies often abstract away student behaviour by condensing actions into numbers, meaning teachers have to assess student data rather than observing students directly. With the rapid adoptio…
Towards a Framework for Digital Governance Curricula: What Skills and Knowledge do Governance Students Need
Digital technologies are rapidly becoming deeply entrenched in society. These technologies provide challenges and opportunities for democratic and organizational processes, and social interactions between governments and citizens. In this study, we focus on the skills governance students need to obtain to fully grasp the opportunities and challenges raised by digitalization in the public sector and society at large. Using a design approach, we fi…
Computer Science (3 works) · Psychology (3 works) · Data science (2 works) · Machine learning (2 works) · Mathematics (2 works) · Statistics (2 works) · Applied Mathematics (1 works) · Artificial Intelligence (1 works) · Bayesian Modeling and Causal Inference (1 works) · Cognition (1 works)