In Conversation: Bannert, Molenaar, & Winne – Multiple Perspectives on Researching and Supporting Self-Regulated Learning via Analytics

Understanding processes in self-regulated learning (SRL) and tailoring appropriate instructional support to help students become more productive self-regulated learners has been on the agenda of SRL researchers for decades. New data modalities and analytic methods are becoming increasingly available to augment existing methodologies, enhance SRL measurement, test theoretical assumptions about SRL and inform future instructional support. Though promising, this research direction is yet to be fully explored. To learn more about how multimodal learner data and analytic methods can be used to improve research and support for SRL, we invited for a conversation Professors Maria Bannert, Inge Molenaar, and Phil Winne, three prominent scholars who have been extensively researching SRL over the past few decades. The conversation included two parts (1) Studying SRL via Analytics and (2) Supporting SRL via Analytics. The discussion identified several major areas for future research, including integrating multiple data channels in a meaningful way to improve theoretical understanding of SRL, and supporting learners by offering them options on what to do next, rather than by saying that they missed an opportunity to engage in a particular SRL process. Following the polyphonic research methodology, the lead authors and the interviewed SRL scholars co-authored this chapter. A podcast of the conversation is available at https://spotifyanchor-web.app.link/e/NwvHdDh3MMb.