Helping Students Manage Personalized Learning Scenarios

In personalized learning scenarios, students have control over their learning goals and how they want to learn which is advantageous since they tend to be more motivated and immersed in what they are learning. However, they need to regulate their motivation, affect and activities so they can learn effectively. Our research deals with helping students identify the long-term effects of their learning behavior and identify effective actions that span across learning episodes which are not easily identified without in depth analysis. In this paper, we discuss how we are trying to identify such effective learning behavior and how they can be used to generate feedback that will help students learn in personalized learning scenarios.