The current level of development in Intelligent Tutoring Systems (ITS) ensures successful cognitive support. However, a number of studies suggest that learning outcomes are significantly influenced by a complex interaction between cognitive and affective states of learners. Little research has been done to investigate the effectiveness of learning with the help of affect-aware ITSs. Recently used approaches to affect recognition rely on facial feature tracking and physiological signal processing, but there is no clear winner among them because of the complexity and ambiguity associated with the task and the low-level data interpretation. The goal of our project is to develop a robust way of affect recognition for creating affect-aware pedagogical agents with the view to improve learners' engagement, motivation and learning outcomes.
|Number of pages||8|
|Publication status||Published - 2007|
|Event||5th New Zealand Computer Science Research Student Conference, NZCSRSC 2007 - Hamilton, New Zealand|
Duration: 10 Apr 2007 → 13 Apr 2007
|Conference||5th New Zealand Computer Science Research Student Conference, NZCSRSC 2007|
|Period||10/04/07 → 13/04/07|