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…

Bayes's theorem is notorious for being a difficult topic to learn and to teach. Problems involving Bayes's theorem (either implicitly or explicitly) generally involve calculations based on two or more given probabilities and their complements. Further, a correct solution depends on students' ability to interpret the problem correctly. Most people…

In the natural world, learning emerges from the joy of play, experimentation, and inquiry as part of everyday life. However, this kind of informal learning is often difficult to integrate within structured educational curricula. This report describes an educational program that embeds naturalistic learning into formal high school, college, and…

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…

"Gedankensimulation" is a term adapted from Einstein's "thought experiments" to indicate mentally created simulations that can help conceptualize ideas. Presents seven examples of simulations that can be utilized to solve problems or illustrate concepts in probability and statistics. Problem contexts include games of chance,…