Ilja Cornelisz
Biographic Data
| ID | 2010311 |
|---|---|
| NAME | Ilja Cornelisz |
| GIVEN NAMES | Ilja |
| FAMILY NAME | Cornelisz |
| SIGNATURE | CORNELISZ I |
| AFFILIATIONS | Faculty of Behavioral and Movement Sciences Amsterdam Center for Learning Analytics Vrije Universiteit Amsterdam Amsterdam the Netherlands |
| ORCID | 0000-0002-9948-7861 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Predicting dropout in Higher Education across borders
Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students’ dropout based on an integrated comparative study of two universities located in two different European countries: Politecnico di Mil…
Combating effort avoidance in computer adaptive practicing
Effort is key in learning, as evidenced by its omnipresence in both empirical findings and educational theory. At the same time, students are consistently found to avoid effort. In this study, we investigate whether limiting effort avoidance improves learning outcomes. We also examine differences in learning outcomes for a substantive typology of students: toilers (practice many problems), skippers (skip many problems), and rushers (provide fast …
Raising student engagement using digital nudges tailored to students' motivation and perceived ability levels
Participation in educational activities is an important prerequisite for academic success, yet often proves to be particularly challenging in digital settings. Therefore, this study set out to increase participation in an online proctored formative statistics exam by digital nudging. We exploited targeted nudges based on the Fogg Behaviour Model, highlighting the relevance of acknowledging differences in motivation and ability in allocating nudge…
Computer or teacher
Introduction Machine learning algorithms use data to identify at-risk students early on such that dropout can be prevented. Teachers, on the other hand, may have a perspective on a student’s chance, derived from their observations and previous experience. Are such subjective perspectives of teachers indeed predictive for identifying at-risk students, and can these perspectives help increase the prediction performance of machine learning algorithm…
Early warning systems for more effective student counselling in higher education
Early Warning Systems (EWS) in higher education accommodate student counsellors by identifying at‐risk students and allow them to intervene in a timely manner to prevent student dropout. This study evaluates an EWS that shares student‐specific risk information with student counsellors, which was implemented at a large Dutch university. A randomised field experiment was conducted to estimate the effect of EWS‐assisted counselling on first‐year stu…
The effects of implementation barriers in virtually proctored examination
Virtual proctoring technology is credited with increasing the accessibility of exams by enabling students to participate in exams at any time and place. In this field experiment, students were randomly assigned to virtual proctoring or traditional on‐campus examination to evaluate the effect, nature and timing of implementation barriers for online proctoring in higher education. The results show that the uptake in the traditional examination sett…
The consequences of academic dismissal for academic success
Academic dismissal policies are increasingly implemented to promote academic success, with existing empirical evidence mostly restricted to short-run outcomes. This study examines long-term academic outcomes of academic dismissal for two cohorts (N=1707) of first-year bachelor students in Economics and Business at a Dutch university. Using administrative records, regression discontinuity design estimates suggest that academic dismissal does not r…
Does educational privatisation promote social justice?
Social justice in education refers to the expectation that the education system provides fairness in its access to opportunities and results. Proponents of educational privatisation believe this would not only open up opportunities for those that otherwise are restricted from attending good schools, but that it would also improve overall efficiency in the education system through pressures of market competition. This article first provides a fram…
Predicting dropout in Higher Education across borders
Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students’ dropout based on an integrated comparative study of two universities located in two different European countries: Politecnico di Mil…
Does educational privatisation promote social justice?
Social justice in education refers to the expectation that the education system provides fairness in its access to opportunities and results. Proponents of educational privatisation believe this would not only open up opportunities for those that otherwise are restricted from attending good schools, but that it would also improve overall efficiency in the education system through pressures of market competition. This article first provides a fram…
The consequences of academic dismissal for academic success
Academic dismissal policies are increasingly implemented to promote academic success, with existing empirical evidence mostly restricted to short-run outcomes. This study examines long-term academic outcomes of academic dismissal for two cohorts (N=1707) of first-year bachelor students in Economics and Business at a Dutch university. Using administrative records, regression discontinuity design estimates suggest that academic dismissal does not r…
The effects of implementation barriers in virtually proctored examination
Virtual proctoring technology is credited with increasing the accessibility of exams by enabling students to participate in exams at any time and place. In this field experiment, students were randomly assigned to virtual proctoring or traditional on‐campus examination to evaluate the effect, nature and timing of implementation barriers for online proctoring in higher education. The results show that the uptake in the traditional examination sett…
Computer or teacher
Introduction Machine learning algorithms use data to identify at-risk students early on such that dropout can be prevented. Teachers, on the other hand, may have a perspective on a student’s chance, derived from their observations and previous experience. Are such subjective perspectives of teachers indeed predictive for identifying at-risk students, and can these perspectives help increase the prediction performance of machine learning algorithm…
Early warning systems for more effective student counselling in higher education
Early Warning Systems (EWS) in higher education accommodate student counsellors by identifying at‐risk students and allow them to intervene in a timely manner to prevent student dropout. This study evaluates an EWS that shares student‐specific risk information with student counsellors, which was implemented at a large Dutch university. A randomised field experiment was conducted to estimate the effect of EWS‐assisted counselling on first‐year stu…
Combating effort avoidance in computer adaptive practicing
Effort is key in learning, as evidenced by its omnipresence in both empirical findings and educational theory. At the same time, students are consistently found to avoid effort. In this study, we investigate whether limiting effort avoidance improves learning outcomes. We also examine differences in learning outcomes for a substantive typology of students: toilers (practice many problems), skippers (skip many problems), and rushers (provide fast …
Raising student engagement using digital nudges tailored to students' motivation and perceived ability levels
Participation in educational activities is an important prerequisite for academic success, yet often proves to be particularly challenging in digital settings. Therefore, this study set out to increase participation in an online proctored formative statistics exam by digital nudging. We exploited targeted nudges based on the Fogg Behaviour Model, highlighting the relevance of acknowledging differences in motivation and ability in allocating nudge…
Predicting dropout in Higher Education across borders
Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students’ dropout based on an integrated comparative study of two universities located in two different European countries: Politecnico di Mil…
Psychology (7 works) · Computer Science (6 works) · Online Learning and Analytics (5 works) · Mathematics education (4 works) · Political science (4 works) · Applied Psychology (3 works) · Higher education (3 works) · Medical education (3 works) · Medicine (3 works) · Online and Blended Learning (3 works)