Epistemology, assessment, pedagogy: where learning meets analytics in the middle space. Knight, S., Buckingham Shum, S., & Littleton, K. Journal of Learning Analytics, 2014.
Paper abstract bibtex Learning Analytics is an emerging research field and design discipline which occupies the ‘middle space’ between the learning sciences/educational research, and the use of computational techniques to capture and analyse data (Suthers and Verbert, 2013). We propose that the literature examining the triadic relationships between epistemology (the nature of knowledge), pedagogy (the nature of learning and teaching) and assessment provide critical considerations for bounding this middle space. We provide examples to illustrate the ways in which the understandings of particular analytics are informed by this triad. As a detailed worked example of how one might design analytics to scaffold a specific form of higher order learning, we focus on the construct of epistemic beliefs: beliefs about the nature of knowledge. We argue that analytics grounded in a pragmatic, sociocultural perspective are well placed to explore this construct using discourse-centric technologies. The examples provided throughout this paper, through emphasising the consideration of intentional design issues in the middle space, underscore the “interpretative flexibility” (Hamilton & Feenberg, 2005) of new technologies, including analytics. Ke
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title = {Epistemology, assessment, pedagogy: where learning meets analytics in the middle space},
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year = {2014},
keywords = {Learning analytics,discourse analytics,educational assessment,epistemology,pedagogy,social learning analytics},
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abstract = {Learning Analytics is an emerging research field and design discipline which occupies the ‘middle space’ between the learning sciences/educational research, and the use of computational techniques to capture and analyse data (Suthers and Verbert, 2013). We propose that the literature examining the triadic relationships between epistemology (the nature of knowledge), pedagogy (the nature of learning and teaching) and assessment provide critical considerations for bounding this middle space. We provide examples to illustrate the ways in which the understandings of particular analytics are informed by this triad. As a detailed worked example of how one might design analytics to scaffold a specific form of higher order learning, we focus on the construct of epistemic beliefs: beliefs about the nature of knowledge. We argue that analytics grounded in a pragmatic, sociocultural perspective are well placed to explore this construct using discourse-centric technologies. The examples provided throughout this paper, through emphasising the consideration of intentional design issues in the middle space, underscore the “interpretative flexibility” (Hamilton & Feenberg, 2005) of new technologies, including analytics. Ke},
bibtype = {article},
author = {Knight, Simon and Buckingham Shum, Simon and Littleton, Karen},
journal = {Journal of Learning Analytics}
}
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