Patrick Chipman

TL;DR: Grounded in constructivist learning theories and tutoring research, AutoTutor achieves learning gains of approximately 0.8 sigma (nearly one letter grade), depending on the learning measure and comparison condition.

TL;DR: McDaniel et al. as mentioned in this paper used facial features to detect the affective states (or emotions) that accompany deep-level learning of conceptual material, including boredom, confusion, delight, flow, frustration, and surprise.

TL;DR: For instance, Graesser et al. as mentioned in this paper investigated the relationship between emotions and learning by tracking the affective states that college students experienced while interacting with AutoTutor, an intelligent tutoring system with conversational dialogue.

TL;DR: Serious games are designed with the explicit goal of helping students learn about important subject matter, problem solving strategies, and cognitive or cognitive or social skills as discussed by the authors, and they have been shown to help students learn more than reading a textbook, listening to a lecture or interacting with a conventional computer-based training system.

TL;DR: The relationship between emotions and learning was investigated by tracking the emotions that college students experienced while learning about computer literacy with AutoTutor, which revealed that post-test scores were significantly predicted by pre- test scores and confusion, but not by any of the other emotions.