Abstract
Cognitive Diagnostic Models (CDMs) provide diagnostic information about a subject’s skill profile by specifying relationships between the student’s latent skill profile, item characteristics, and student responses to those items. In this study, we analyze the ASSISTment Math 2004–2005 dataset to explore whether latent skill profiles estimated at one assessment point are predictive of latent skill profiles at a subsequent assessment point. In addition, we wanted to investigate the hypothesis that latent skills evolve independently. We found that latent skills estimated at subsequent assessment points were predicted by latent skills at previous assessment points when these were spaced at least six weeks apart. In addition, we found evidence that latent skills may not independently evolve despite the fact that this is a common assumption in longitudinal modeling. Some comments are then provided regarding how such results might inform the design of new longitudinal cognitive diagnostic models of student learning in semester-long courses.
Keywords
- Longitudinal cognitive diagnostic models
- Cognitive diagnostic assessments
- Latent transition analysis
- Diagnostic classification models
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This project was partially funded by the University of Texas at Dallas Office of Research through the Social Sciences SEED Program.
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Sudheesh, A., Golden, R.M. (2021). Exploring Temporal Functional Dependencies Between Latent Skills in Cognitive Diagnostic Models. In: Wiberg, M., Molenaar, D., González, J., Böckenholt, U., Kim, JS. (eds) Quantitative Psychology. Springer Proceedings in Mathematics & Statistics, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-030-74772-5_23
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DOI: https://doi.org/10.1007/978-3-030-74772-5_23
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