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Predictive performance of prevailing approaches to skills assessment techniques: Insights from real vs. synthetic data sets.

, и . EDM, стр. 409-410. International Educational Data Mining Society (IEDMS), (2014)

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Другие публикации лиц с тем же именем

Item to Skills Mapping: Deriving a Conjunctive Q-matrix from Data., , и . ITS, том 7315 из Lecture Notes in Computer Science, стр. 454-463. Springer, (2012)The refinement of a Q-matrix: Assessing methods to validate tasks to skills mapping., , и . EDM, стр. 208-311. International Educational Data Mining Society (IEDMS), (2014)Improving Matrix Factorization Techniques of Student Test Data with Partial Order Constraints., и . UMAP, том 7379 из Lecture Notes in Computer Science, стр. 346-350. Springer, (2012)A Partition Tree Approach to Combine Techniques to Refine Item to Skills Q-Matrices., , и . EDM, стр. 29-36. International Educational Data Mining Society (IEDMS), (2015)Linear models of student skills for static data., , и . UMAP Workshops, том 872 из CEUR Workshop Proceedings, CEUR-WS.org, (2012)Goodness of Fit of Skills Assessment Approaches: Insights from Patterns of Real vs. Synthetic Data Sets., и . EDM, стр. 368-371. International Educational Data Mining Society (IEDMS), (2015)Methods to find the number of latent skills., , и . EDM, стр. 81-86. www.educationaldatamining.org, (2012)Predictive performance of prevailing approaches to skills assessment techniques: Insights from real vs. synthetic data sets., и . EDM, стр. 409-410. International Educational Data Mining Society (IEDMS), (2014)