H.J. Pijeira Diaz | Maastricht University

Pijeira-Diaz, H. J., Subramanya, S., van de Pol, J., & de Bruin, A. (2024). Evaluating Sentence-BERT-powered learning analytics for automated assessment of students' causal diagrams. Journal of Computer Assisted Learning, 40(6), 2667-2680. https://doi.org/10.1111/jcal.12992

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Pijeira-Diaz, H. J., Braumann, S., van de Pol, J., van Gog, T., & de Bruin, A. B. H. (2024). Towards adaptive support for self-regulated learning of causal relations: Evaluating four Dutch word vector models. British Journal of Educational Technology, 55(4), 1354-1375. Article 13431. https://doi.org/10.1111/bjet.13431

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Braumann, S., van de Pol, J., Kok, E., Pijeira-Díaz, H. J., van Wermeskerken, M., de Bruin, A. B. H., & van Gog, T. (2024). The role of feedback on students’ diagramming: Effects on monitoring accuracy and text comprehension. Contemporary Educational Psychology, 76, Article 102251. https://doi.org/10.1016/j.cedpsych.2023.102251

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Braumann, S., van Wermeskerken, M., van de Pol, J., Pijeira-Diaz, H. J., de Bruin, A. B. H., & van Gog, T. (2024). Causal diagramming to improve students' monitoring accuracy and text comprehension: Effects of diagram standards and self-scoring instructions. Applied Cognitive Psychology, 38(1), Article e4170. https://doi.org/10.1002/acp.4170

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Pijeira-Diaz, H. J., van de Pol, J., Channa, F., & de Bruin, A. (2023). Scaffolding self-regulated learning from causal-relations texts: Diagramming and self-assessment to improve metacomprehension accuracy? Metacognition and Learning, 18(3), 631-658. https://doi.org/10.1007/s11409-023-09343-0

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Malmberg, J., Saqr, M., Järvenoja, H., Haataja, E., Pijeira-Díaz, H. J., & Järvelä, S. (2022). Modeling the Complex Interplay Between Monitoring Events for Regulated Learning with Psychological Networks. In The Multimodal Learning Analytics Handbook (pp. 79-104). Springer International Publishing. https://doi.org/10.1007/978-3-031-08076-0_4

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Malmberg, J., Fincham, O., Pijeira-Diaz, H. J., Jarvela, S., & Gasevic, D. (2021). Revealing the hidden structure of physiological states during metacognitive monitoring in collaborative learning. Journal of Computer Assisted Learning, 37(3), 861-874. https://doi.org/10.1111/jcal.12529

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Malmberg, J., Järvelä, S., Järvenoja, H., Haataja, E., Pijeira-Díaz, H. J., & Cini, A. (2020). Designing and implementing multimodal data collection in classroom to capture metacognition in collaborative learning. In CrossMMLA in practice (Vol. 2610, pp. 23-29)

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