Introduction

Learning is accompanied by episodes of success and failure that inevitably invoke a host of associated affective responses. While, the last decade has been ripe with research investigating the interplay between emotions and learning, there are several open challenges hindering progress in this area. These include empirical and theoretical questions such as: (1) What are the emotions that are important to learning? (2) How are they linked with cognition and meta-cognitive processes (e.g. self-regulation and goal orientation)? Additionally, the effectiveness of one-on-one tutoring in promoting active knowledge construction has extended the role of affective modeling beyond traditional classroom environments and into the arena of integrated learning environments. This transition requires innovative computational approaches to construct online affect-sensitive learner models and utilize these models to detect and respond to the learner's affect to potentially optimizing learning.
 

Researchers interested in these challenges range from multiple disciplines associated with the learning sciences such as psychology, education, cognitive science, computer science, artificial intelligence, and neuroscience. Since many of these researchers share the same goals of developing learning environments that effectively coordinate pedagogy with the learner's emotions, the proposed workshop seeks to create cross talk between the areas.