Publications en collaboration avec des chercheurs de KU Leuven (12)

2023

  1. Field-based upper-body motor variability as determinant of stroke performance in the main tennis strokes

    Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology

  2. Predicting Effortful Control at 3 Years of Age from Measures of Attention and Home Environment in Infancy: A Machine Learning Approach

    Children, Vol. 10, Núm. 6

2022

  1. Fronto-parietal homotopy in resting-state functional connectivity predicts task-switching performance

    Brain Structure and Function, Vol. 227, Núm. 2, pp. 655-672

  2. Modeling the Contribution of Genetic Variation to Cognitive Gains Following Training with a Machine Learning Approach

    Mind, Brain, and Education, Vol. 16, Núm. 4, pp. 300-317

  3. Personality and mental health: Factors impacting perceived health risks and protective behaviors during the early COVID-19 quarantine

    Cognition, Brain, Behavior. An Interdisciplinary Journal , Vol. 26, Núm. 1, pp. 37-65

  4. Predicting attribution of letter writing performance in secondary school: A machine learning approach

    Frontiers in Education, Vol. 7

2021

  1. Artificial neural networks in academic performance prediction: Systematic implementation and predictor evaluation

    Computers and Education: Artificial Intelligence, Vol. 2

2020

  1. Identifying Reliable Predictors of Educational Outcomes Through Machine-Learning Predictive Modeling

    Frontiers in Education, Vol. 5

  2. Predicting key educational outcomes in academic trajectories: a machine-learning approach

    Higher Education, Vol. 80, Núm. 5, pp. 875-894

2019

  1. Individual differences in basic cognitive processes and self-regulated learning: Their interaction effects on math performance

    Learning and Individual Differences, Vol. 71, pp. 58-70

2014

  1. Modelling for understanding and for prediction/classification-the power of neural networks in research

    Frontline Learning Research, Vol. 2, Núm. 5, pp. 67-81

2013

  1. Predicting general academic performance and identifying the differential contribution of participating variables using artificial neural networks

    Frontline Learning Research, Vol. 1, Núm. 1, pp. 42-71