This post is a copy of the course syllabus for week 6 as of 17:15 GMT 15/03/2013 (licenced under a CC attribution licence) https://learn.canvas.net/courses/33/wiki/week-6-epistemology-and-pedagogy George Siemens runs the course, and Simon Buckingham Shum and I wrote the material for this week. I’ll try & update it to reflect the course page but the course page is the ‘definitive’ source.

Introduction to the week

This week we want to highlight some of the implications of analytics for learning, assessment, and how we understand ‘knowledge’ – what does the content we assess, and the way we assess imply about how we understand learning and knowledge? Picture1.png There is a well-established literature examining the relationships between epistemology (the nature of knowledge), pedagogy (the nature of learning), 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 week we will introduce these issues,since we cannot be naive about what agendas learning analytics may be deployed to achieve. Assessment regimes are the subject of intense debate within education and politics, and since these drive (and strangle) educational innovation and reform, we need to develop a very clear account of the different kinds of analytics, and the assumptions they make about what ‘good’ looks like. Incisive criticisms of Big Data hubris need to be taken seriously, as do concerns about the limits of analytics. Thinking in terms of Epistemology, Pedagogy and Assessment should help us tease apart some of the quite legitimate concerns. Perhaps it is the case that the easiest forms of data to collect and analyse at scale also correspond to relatively conservative, traditional epistemologies, pedagogies and assessments? Is learning analytics a-theoretical in its efforts to derive bottom-up predictors that correlate with ‘good’ student outcomes, or does theory still have an important place?

Week Activity/Output

We’d like to provide you with some analytics from the week, and we’re hoping to use the Evidence Hub as a key tool this week.  While you’re free to use any tool you like (share in the forums!) you may also find the Evidence Hub a useful tool for mapping your understanding of Learning Analytics and exploring the Logics of Enquiry (two of the LAK13 assignments). We’ll be keeping an eye on the forums, tweets, and blogs.  We’ve also put some resources into the [Evidence Hub]1 to start people off.  Anyone can add to this – please do add your own resources, and ‘chat’ contributions as we go on.

Sunday-Monday 17/18 March – pre-reading/video

  1. Reading: You might like to look at a brief [introduction to epistemology and pedagogy]2 and an [introduction to epistemology introduction]3 which [Simon Knight]4 wrote for this week and provides some further detail 2. [Denmark video]5 – the way we conceptualise knowledge is tied to assessment (or, the way we assess implicates particular epistemologies) (We’re building some ideas around this on the evidence hub [here]6).  We argue that LA is an instantiation of assessment and should thus consider these issues. 3. To prepare for the week’s activities, take a look at the [Evidence Hub tutorial]7

Tuesday 19/03 – live session 20:30-22:00 GMT (what time for me?) (<a

href=”https://sas.elluminate.com/m.jnlp?sid=2008104&amp;password=M.797B6BE96971DE398B7069E3AFAC2B” target=“_blank”>held here in Collaborate)

We’ll be holding a live session on Tuesday March 19th, introducing the week and then giving two takes on the topic.  More detail about each speaker is available on the ‘Live Sessions’ page.

  1. Simon Knight and Simon Buckingham Shum– brief introduction to epistemology, and the week’s activities.
  2. George Siemens – connectivism and its implications for epistemology and assessment (using LA?)
  3. David Williamson Shaffer – epistemic games and learning analytics

Optional READING: You might like to read the report on the Danish experiment with using the internet in exams (Google translate into English ), there’s also an English language fact sheet available [pdf]) The talks this week are centred on the themes discussed in: Epistemology, Assessment, Pedagogy, Learning Analytics, open access available [here]8

Tuesday – Activity: Assessment, Pedagogy and Epistemology for your profession

Think of a profession you know a bit about (perhaps your own, we think ‘lawyer’ is a good example if you’re stuck for ideas!)  Think about the demonstration of knowledge in that profession using the APE acronym below.  You might like to start adding ‘chats’ to issues in the Evidence Hub to help everyone in making sense of the problems you’re considering. 1. How could we assess this?  (Assessment) 2. What implications does that have for the teaching/pedagogy? (Pedagogy) 3. What epistemology does your proposed assessment implicate? (Epistemology)

Wednesday – Activity: Reflection and Development

Using the reflection from yesterday, post “issues” raised in your APE analysis to the [Evidence Hub]9. Use the ‘chat’ function (click the ‘gear’ icon) in the Evidence Hub to discuss issues. Conduct some research on the web – share your results in the ‘issue’ chats,explain how you found your resources too – what did you search for, were you looking for people, keywords, organisations, etc.  You should feel free to add issues, evidence, solutions, and resources as you go along, but if you want a starting point we’ve picked out some issues relevant to this topic, take a look at the first one for an example knowledge tree – this should give you an idea how to use the Evidence Hub to develop your ideas around all of the issues. 1. [Can learning analytics give insight into the quality of discussions?]10 Chat [here]11 2. [How can learning analytics help us get closer to ‘authentic’ learning? What does ‘authentic’ mean (is it an epistemological claim?)? ]12 Chat [here]13 3. [Can learning analytics give insight into the quality of collaboration?]14 Chat [here]15 4. [How can we present learning analytics best for formative assessment?]16 Chat [here]17 5. [How can we assess research skills in the internet age?]18 Chat [here]19 As your discussions develop, we encourage you to “convert” discussion posts into Evidence Hub nodes (using the ‘gear’ icon to change them into solutions, evidence, new issues, etc.).

Friday – Activity: Reflecting on Analytics

You can use the Evidence Hub analytics as an assessment for participation in this week.  View your homepage and view the global analytics, you should get to a page that looks like this: [Simon Buckingham Shum’s EH analytics]20 With an APE lens, reflect on the questions provided in the [EH Tutorial Part 5]21 and post anecdotes, issues, examples to the EH meta-theme on Analytics on these analytics in the forum, or to the EH [meta-theme on Analytics]22 1. How does it assist pedagogy and assessment?  What sorts? 2. What current LA can do this? How can they be improved? 3. What are the implications of this for epistemology/what constraints does it place on our conceptualisation of knowledge? READING: If you haven’t read it for one of the other weeks, you might like to look at boyd and Crawford’s “six provocations for big data”, and/or SK’s reflections on this article for learning analytics: [6 provocations for LA]23

Footnotes

  1. http://solar.evidence-hub.net/explore.php?id=1371081452500307806001301388177 ↩

  2. http://www.ucdoer.ie/index.php/Education_Theory/Epistemology_and_Learning_Theories ↩

  3. http://sjgknight.com/finding-knowledge/2013/03/introduction-to-epistemology/ ↩

  4. http://sjgknight.com/finding-knowledge/ ↩

  5. http://news.bbc.co.uk/1/hi/education/8341589.stm ↩

  6. http://solar.evidence-hub.net/explore.php?id=137108145390970739001360857531#widget ↩

  7. http://evidence-hub.net/tutorial/ ↩

  8. http://oro.open.ac.uk/36635/ ↩

  9. http://solar.evidence-hub.net/index.php#home-list ↩

  10. http://solar.evidence-hub.net/explore.php?id=137108254760577525001361476385#linear ↩

  11. http://solar.evidence-hub.net/explore.php?id=137108254760577525001361476385#chat ↩

  12. http://solar.evidence-hub.net/explore.php?id=137108145400879697001363277357#linear ↩

  13. http://solar.evidence-hub.net/explore.php?id=137108145400879697001363277357#chat ↩

  14. http://solar.evidence-hub.net/explore.php?id=137108145400831695001363018472#linear ↩

  15. http://solar.evidence-hub.net/explore.php?id=137108145400831695001363018472#chat ↩

  16. http://solar.evidence-hub.net/explore.php?id=137108145400353660001363005481#linear ↩

  17. http://solar.evidence-hub.net/explore.php?id=137108145400353660001363005481#chat ↩

  18. http://solar.evidence-hub.net/explore.php?id=137108145400787195001363004787#linear ↩

  19. http://solar.evidence-hub.net/explore.php?id=137108145400787195001363004787#chat ↩

  20. http://goo.gl/vkzmT ↩

  21. http://evidence-hub.net/tutorial/part5/ ↩

  22. http://goo.gl/7D2Xf ↩

  23. http://sjgknight.com/finding-knowledge/2013/01/six-provocations-for-learning-analytics/ ↩