Improving student models by reasoning about cognitive ability, emotions and gender

Abstract

We explore how cognitive, socio-biological and emotional conditions of the student help predict behavior within an ITS, and how instruction should be adapted depending on these variables to improve educational outcomes. Cognitive, social and emotional factors tend to be more permanent in nature than student’s knowledge. Our approach is to diagnose them with pre-tests before the user starts using the system.