New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

Increasing college participation rates, and diversity in student population, is posing a challenge to colleges in their attempts to facilitate learners achieve their full academic potential. Learning analytics is an evolving discipline with capability for educational data analysis that could enable better understanding of learning process, and…

Argues that selecting data according to expected information gain, as proposed by M. Oaksford and N. Chater (1994, 1996), leads to suboptimal performance in Bayesian hypothesis testing. Procedures are presented that are better justified normatively, their psychological implications are explored, and a number of novel predictions are derived under…

Argues that Klauer's proposal (1999) and proposal presented are equally well justified from a normative perspective and that, where the predictions of the two approaches diverge, the existing empirical evidence is consistent with the information gain approach. Recommends that more empirical research is required to decide between these two…