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Download full textGalyardt, April; Goldin, Ilya – Journal of Educational Data Mining, 2015
In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…
Descriptors: Achievement Rating, Performance Based Assessment, Bayesian Statistics, Data Analysis
Pardos, Zachary A.; Heffernan, Neil T. – International Working Group on Educational Data Mining, 2009
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collected in many ITS systems consist of answers to a group of questions of a given skill often presented in a random sequence. Following work that identifies which items…
Descriptors: Data Analysis, Bayesian Statistics, Statistical Analysis, Problem Sets
Peer reviewedFeinstein, Ellen; And Others – Evaluation and the Health Professions, 1983
Written clinical simulation problems in forced-choice and essay formats were used to compare the performance of medical students with varying levels of clinical experience at the conclusion of their pediatric rotations. Clinical simulation problems failed to demonstrate responsiveness to development and maturation in the problem-solving approach…
Descriptors: Clinical Experience, Essay Tests, Forced Choice Technique, Higher Education
