Connecting expert knowledge in the design of classroom learning experiences

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Learning analytics in the classroom: Translating learning analytics research for teachers, 2019, pp. 111 - 128
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Learning Analytics technologies provide new ways to log, evaluate and provide feedback on learning activity. Consequently, it is clearly desirable that strong connections are forged with research and practice in established disciplines such as educational research (Gašević, Dawson & Siemens, 2015), learning theory (Friend Wise & Shaffer, 2015), learning designs (Lockyer & Dawson, 2011), tools design (Martinez-Maldonado, Pardo, Mirriahi, Yacef, Kay & Clayphan, 2016b), epistemology, pedagogy and assessment (Knight, Buckingham Shum, & Littleton, 2014). Learning, and in particular, design for learning, has been conceptualised in terms of complex networks of learners, instructors, designers, and researchers integrating physical and digital spaces (Carvalho, Goodyear & de Laat, 2017). In contemporary learning environments, learning designs must consider the role of tools in both physical and digital learning environments, and how these tools can connect to support learning and teaching. The learning design process now needs to take into account the affordances present when digital environments are capable of producing highly detailed digital traces of learner engagement. In contemporary learning environments, there is also a pressing need to explore a tighter interdisciplinary approach in which learning sciences, learning analytics, and classroom experts develop learning designs to take full advantage of the potential benefits of this new data. Accessing data to inform teaching and learning is increasingly common during the design of learning experiences. However, how this data is interpreted will vary depending on the purpose for which it is being accessed (e.g. accountability, teaching-evaluation, or providing feedback to students, etc.) and the role of the accessor in developing or delivering the learning task (e.g. learning technologist, learning designer, tutor, lecturer, etc.). This chapter uses a case study to explore one such design scenario. In this chapter we draw on research about interdisciplinary team science (Pennington, 2011; Pennington et al., 2015) to explore a design problem from the perspective of a team of experts in learning sciences, classroom practice, and learning analytics. Focusing on assessment, we explore the process of connecting disciplinary perspectives during the design process and the relationship between these emergent connections and the final learning design. We make this distinction to move beyond the individual connections between learning analytics and design, teaching or research, instead viewing relationships between these perspectives as inextricably linked in the design process. The many stakeholders in learning situations commonly have different and, sometimes, competing needs for the data. A design session between some of the co-authors was used to explore this question. We draw on multimodal data (including video, audio, and design artefacts) collected during the session, as the experts engaged in the design of a graduate course to equip teachers for interdisciplinary Science, Technology, Engineering, Arts and Mathematics (STEAM) education
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