Learning analytics supported goal setting in online learning environments

The rapidly increasing role of technology in education has resulted in large amounts of data being collected about student learning and behavior, and as a result, has given rise to the field of Learning Analytics. Although much research in this field has focused on offering insights to educators, researchers have suggested learning analytics may be most effectively employed when they focus on insights which can be offered directly to students. Furthermore, researchers have called for more focus on research driven by educational theory and given the highly self-directed nature of higher education in general, and online learning environments specifically, self-regulated learning can be highlighted as an important theoretical framework to consider in future studies. Self-regulated learning (SRL) can be viewed as a cyclical process in which goal setting and monitoring play an integral role in driving behavior, and prior research has shown that SRL skills are positively related to academic performance. However, prior research on how learning analytics can support goal setting to enhance SRL is extremely scarce. The aim of this project is to explore the question of how learning analytics can support the goal setting process in online learning environments to improve SRL and performance? In this project several studies have been designed to (a) examine the effectiveness of a learning analytics supported goal setting and monitoring tool to improve academic performance, (b) consider the influence of individual student characteristics on the effectiveness of this learning analytics tool (c) consider whether personalizing learning analytics tools to support goal setting can increase the efficacy of the tools. Overall, the aim is to be able to offer guidelines for how learning analytics tools can be designed and personalized to increase the effectiveness of goal setting interventions to optimize SRL and performance in online learning environments.