{"id":4450,"date":"2015-01-30T08:30:09","date_gmt":"2015-01-30T08:30:09","guid":{"rendered":"https:\/\/newsletter.alt.ac.uk\/?p=4450"},"modified":"2015-08-20T11:44:53","modified_gmt":"2015-08-20T10:44:53","slug":"learning-analytics-threats-and-opportunities","status":"publish","type":"post","link":"https:\/\/altc.alt.ac.uk\/blog\/2015\/01\/learning-analytics-threats-and-opportunities\/","title":{"rendered":"Learning Analytics: Threats and opportunities"},"content":{"rendered":"

Update:<\/strong> There is now a\u00a0report by\u00a0Graham McElearney from\u00a0this White Rose Learning Technologists’ event<\/a>\u00a0(this report includes a recording of the presentation by Martin Hawksey).<\/p>\n

I was recently\u00a0invited to ALT\u2019s White Rose Learning Technologists’ SIG<\/a> to talk about Learning Analytics (LA). I first started getting interested in Learning Analytics in 2011 but I was initially reluctant to talk on the topic as I’ve recently realised how much I don\u2019t know about this area. Another factor was my fear that learning analytics is being eroded by \u2018counts\u2019 rather than actually caring about the learner. With this in mind I decided that sharing my fears and areas I’ve struggled with would be useful for the audience. A great source of inspiration for my presentation was a talk given by Dragan Gasevic a\u00a0recording of which is currently here<\/a> and Dragon\u2019s slides are on Slideshare<\/a>.\u00a0While Dragon focused on Learning Analytics for MOOCs transfer into other modes of learning and teaching.\u00a0My own\u00a0\u00a0slides are available online<\/a> and a recording may be available soon. Here are some of my personal notes and reflections that supplement the slides:<\/p>\n

Absence of theory<\/h3>\n

Amazon cares not a whit *why* people who buy german chocolate also buy cake pans as long as they get to the checkout buying both – Mike Caulfield – Short Notes on the Absence of Theory<\/a><\/p><\/blockquote>\n

I was fortunate to be in the bar<\/span> room when \u2018absence of theory\u2019 was being discussed at MRI13. The thing that hit me hardest was the reflection that throughout my career there has been an absence of theory. Like many other learning technologists I jumped into this area from another discipline, in my case structural engineering. Consequently I started in this area with more knowledge of the plastic analysis or portal frames than\u00a0 educational theory. Being a curious person has taken me down numerous avenues and often along the way I\u2019ve been lucky to work and learn with some of the best. For example I was fortunate to work with Professors David Nicol and Jim Boyle at the University of Strathclyde, Jim arguably being responsible for importing Peer Instruction to the UK. So while I have some theory I don\u2019t have enough and whilst I have connections to some of the best people in LA my job isn\u2019t aligned. But enough about me, without theory the danger is you have data but no actual insight to what it means.<\/p>\n

Visualizations<\/h3>\n

Graphs can be a powerful way to represent relationships between data, but they are also a very abstract concept, which means that they run the danger of meaning something only to the creator of the graph \u2026 Everything looks like a graph, but almost nothing should ever be drawn as one. – Ben Fry in \u2018Visualizing Data\u2019<\/p><\/blockquote>\n

The consequence is \u2018every chart is a lie\u2019, a representation of data defined by it\u2019s creator. One option here is to turn the learner into the creator. With modern web browsers it\u2019s becoming even easier for someone to become the explorer of their own data. Dashboards, which appear to have the same appeal as Marmite, can also be personalised to give more meaning to the learner. Even with personalisation and customisation there is a danger of misinterpretation which Dragon highlighted with Corrin, L., & de Barba, P. (2014). \u2018Exploring students\u2019 interpretation of feedback delivered through learning analytics dashboards\u2019.<\/p>\n

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Ethics and privacy<\/h3>\n

The worlds of privacy and analytics intersect \u2026not always happily \u2013 Stephen Downes<\/p><\/blockquote>\n

I was browsing some slide decks by Doug Clow as part of the LACEProject<\/a> and he captured the sentiment nicely highlighting that there needs to be transparency when using learning analytics. He contextualised this around guidance and support rather than\u00a0 surveillance and control. Given the varying degrees of apathy I see around data and privacy this is a conversation always worth having. There is clear outline of ethical considerations in the Analytics for Education chapter<\/a> penned by my co-authors Sheila MacNeill and Lorna Campbell:<\/p>\n

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Ethical Issues<\/h4>\n

As institutional managers, administrators and researchers are well aware, any practice involving data collection and reuse has inherent legal and ethical implications. Most institutions have clear guidelines and policies in place governing the collection and use of research data; however it is less common for institutions to have legal and ethical guidelines on the use of data gathered from internal systems (Prinsloo & Slade, 2013<\/a>). As is often the case, the development of legal frameworks has not kept pace with the development of new technologies.<\/p>\n

The Cetis Analytics Series paper on Legal, Risk and Ethical Aspects of Analytics in Higher Education<\/em> (Kay, Korn, & Oppenheim, 2012<\/a>) outlines a set of common principles that have universal application:<\/p>\n