New [paper out on ORO]1. This is the accepted [Journal of Learning Analytics]2 version (i.e. some changes might still be made) of the paper we wrote up from our [LAK13 presentation]3, and we anticipate it being in publication in the 2nd issue. I was happy with the LAK13 paper, but it was written right at the start of my PhD (within the first two months!) and since then we’ve engaged in some deeper reflection on the the issues raised, their relationship to wider context (including interpretive flexibility) and of course we’ve had feedback from 5 or 6 anonymous reviewers, a conference audience, seminars, and so on (and my thanks go to all of those people). Further feedback on the paper is of course welcome and I’m looking forward to developing the work further/seeing if/how people pick up on elements of it. For interest, I’ve pasted the two abstracts below. You’ll see the original was far more about pressing our own perspective, with a slightly narrower focus. The new paper gives a more nuanced take I think. # New Abstract (2014 paper) 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. # Original Abstract (2013 paper) There is a well-established literature examining the relationships between epistemology (the nature of knowledge), pedagogy (the nature of learning and teaching), and assessment. Learning Analytics (LA) is a new assessment technology and should engage with this literature since it has implications for when and why different LA tools might be deployed. This paper discusses these issues, relating them to an example construct, epistemic beliefs – beliefs about the nature of knowledge – for which analytics grounded in pragmatic, sociocultural theory might be well placed to explore. This example is particularly interesting given the role of epistemic beliefs in the everyday knowledge judgements students make in their information processing. Traditional psychological approaches to measuring epistemic beliefs have parallels with high stakes testing regimes; this paper outlines an alternative LA for epistemic beliefs which might be readily applied to other areas of interest. Such sociocultural approaches afford opportunity for engaging LA directly in high quality pedagogy.