Abstract
The aim of this paper is to introduce our current research design to study socially shared regulation processes in a science classroom where a collaborative learning design is implemented. The design is based on a self-regulated learning framework that provides opportunities and support for self-initiated regulation among individual learners and collaborative groups. It utilizes modern technology to structure and support regulated learning in the groups. The paper focuses on elaborating the research design, particularly from the perspective of motivation and emotion, by presenting the dual relationship between designing learning scenario that supports learners’ motivation and emotion regulation with technology and researching the multifaceted role of motivation and emotion as they occur in collaborative learning. To do this, the paper first describes the entire collaborative learning design while paying attention to how technology can be utilized to support the awareness of motivation, emotion, and their regulation. Then, the focus shifts to considering the methodological principles and implementation of multimodal data gathered in relation to authentic collaborative learning tasks. A case example from a secondary school science classroom demonstrates possibilities for multimodal data use in analyzing motivation, emotion, and their regulation in collaborative learning. It also illustrates the dual role of the implemented technological 6Q support tool by showing how data collected from the students’ use of the tool can be utilized in scientific analysis. The paper concludes by providing a short discussion about the current advancements of emerging technology in motivation and emotion research in the learning sciences highlighting the significance of sharing the theoretical premises of the research design as well as practical experiences from implementation of these designs for future research.
Highlights
Collaboration-based instructional approaches promote learning techniques for active and agentic learning (Hmelo-Silver, 2004)
We have argued that an advanced understanding, of motivation and emotion regulation and its various factors, is essential to harness the benefits of technology in supporting these processes in collaborative learning
This provides possibilities for data collection that corresponds to educational change and, to a need for ecologically valid analyses and results related to regulation in collaborative learning (Belland et al, 2013; Wise and Schwarz, 2017; Järvenoja et al, 2018a)
Summary
Collaboration-based instructional approaches promote learning techniques for active and agentic learning (Hmelo-Silver, 2004). Prior to beginning the study, the participating students responded to trait-type selfreports about their SRL strategies and task interest (Cleary, 2006), metacognitive awareness (Schraw and Dennison, 1994), self-efficacy (Usher and Pajares, 2008), and group assignment appraisals (Volet, 2001), each validated and used extensively in earlier research (see Table 1 for the different measures utilized and their features) The purpose of these measures was to gain an overall understanding of the students’ motivational traits and emotional and regulatory underpinnings. Multimodal data provide systematic ways to combine quantitative datasets with qualitative ones to profoundly analyze motivation, emotion, and their regulation as context- and situation-specific and as a part of the wider process of regulated learning
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