Open Social Learner Models for Self-Regulated Learning and Learning Motivation

Abstract

Open Learner Models (OLM) have demonstrated a multitude of benefits supporting metacognition and engaging learners. Although researchers have study different representations of OLM, a broader view that situates OLM in Self-Regulated Learning (SRL) is missing. An important element in SRL that can bring a better understanding of these tools and their effects concerns to learning motivation theories. In this work I connect these aspects and propose to study the effects of OLM and motivational factors drawn from learning motivation theories. To account for a broader spectrum of OLM representations, I proposed to explore the addition of social information and different levels of granularity in the OLM. I propose to evaluate different designs and then to evaluate the resulting interface in field studies. With the proposed work I expect to gain a deeper understanding of the effects of OLM tools which can be used to guide the development of better tools, better personalization and adaptive mechanisms, better use of such tools in supporting Self-Regulated Learning, and ultimately impact positively in learning.