GoogleTranslate Service


Workplace Learning and Learning Analytics

April 15th, 2015 by Graham Attwell

I have been looking hard at Learning Analytics in the last month. In particular, as part of the European EmployID project application, as a bit of a not really thought through objective, we said we would experiment with the use of Learning Analytics in European Public Employment Services. this raises a series of issues which I will come back to in future ports. It seems to me that whilst there is much talk around the potential of  Learning Analytics in the workplace, there is very limited research and actual applications.

One of the reasons for this is that so much learning in the workplace in informal. As Boud and Hager (2012) say:

learning is a normal part of working, and indeed most other social activities. It occurs through practice in work settings from addressing the challenges and problems that arise. Most learning takes place not through formalized activities, but through the exigencies of practice with peers and others, drawing on expertise that is accessed in response to need. Problem-solving in which participants tackle challenges which progressively extend their existing capabilities and learn with and from each other appears to be common and frequent form of naturalistic development.

I would also add that much workplace learning is also driven through personal interest – a fact that is largely ignored and which has considerable economic implications in terms of workplace competence development. Although we can dream of a world where water cooler conversations are recorded by smart devices and sensors and added to other traces of digital activity, I am not sure this is a desirable outcome. So we have a challenge. most (university and formal education based) learning analytics focus on analysing digital interactions in, for example, a VLE. How can we sensibly and ethically extend data capture and analysis to informal workplace learning?

Please follow and like us:

One Response to “Workplace Learning and Learning Analytics”

  1. I’m not sure I know of any strong examples of, or research on, the use of learning analytics in the workplace. As you indicate, learning at work is tightly integrated with work, therefore any analytics would have to monitor the tools and software the individual uses to do their job, not any separate learning environment. This is fraught with difficulty, esp. in an era of BYOD and blurred boundaries between professional and personal activities in twitter, facebook, linkedin, etc.

    While not focused on learning analytics, we’ve written about how informal learning might be supported in the workplace through lightweight tools that integrate closely into workspaces but facilitate learning. See:
    Milligan, C., Littlejohn, A., and Margaryan, A. (2014) Workplace learning in informal networks. Journal of Interactive Media in Education, North America, 0, mar. 2014. Available at: http://jime.open.ac.uk/article/view/325 . Date accessed: 5 March. 2015.
    and
    Milligan, C., Margaryan, A., & Littlejohn, A. (2012). Supporting goal formation, sharing and learning of knowledge workers. In Ravenscroft, A. et al. (Eds.), Proceedings of European Conference on Technology-Enhanced Learning (EC-TEL), LNCS 7563 pp. 519—524. Heidelberg: Springer. [post-print from ResearchGate: https://www.researchgate.net/publication/262316404_Supporting_goal_formation_sharing_and_learning_of_knowledge_workers ]

    By creating tools that support learning at work we begin to get a little closer to something we might want to measure!

    In a similar vein (and research, rather than just writing), Melody Siadaty, Jelena Jovanovic and Dragan Gasevic wrote a chapter for us a year or so ago that explored the potential of the social Semantic Web to support learning, drawing on (amongst other things) their experience of developing and implementing tools in the Intelleo EU project.

    Siadaty, M., Jovanovic, J., & Gasevic, D. (2014) The Social Semantic web and workplace Learning, in A. Littlejohn, & A. Margaryan (eds) Technology Enhanced Professional Learning: Processes, practices and tools. (pp. 132-143). London: Routledge.

    That book also contains a chapter by Bettina Berendt and Rina Vourikari discussing the use of platform based learning analytics in the eTwinning teacher network.
    Berendt, B., Vuorikari, R., Littlejohn, A., & Margaryan, A. (2013). Learning Analytics and their application in technology enhanced professional learning. In Littlejohn, A., & Margaryan, A. (Eds.). Technology-enhanced professional learning: Processes, practices and tools (pp. 144-157). London: Routledge.

    Hope some of this is helpful.

  • Search Pontydysgu.org

    Social Media




    News Bites

    Cyborg patented?

    Forbes reports that Microsoft has obtained a patent for a “conversational chatbot of a specific person” created from images, recordings, participation in social networks, emails, letters, etc., coupled with the possible generation of a 2D or 3D model of the person.

    Please follow and like us:


    Racial bias in algorithms

    From the UK Open Data Institute’s Week in Data newsletter

    This week, Twitter apologised for racial bias within its image-cropping algorithm. The feature is designed to automatically crop images to highlight focal points – including faces. But, Twitter users discovered that, in practice, white faces were focused on, and black faces were cropped out. And, Twitter isn’t the only platform struggling with its algorithm – YouTube has also announced plans to bring back higher levels of human moderation for removing content, after its AI-centred approach resulted in over-censorship, with videos being removed at far higher rates than with human moderators.

    Please follow and like us:


    Gap between rich and poor university students widest for 12 years

    Via The Canary.

    The gap between poor students and their more affluent peers attending university has widened to its largest point for 12 years, according to data published by the Department for Education (DfE).

    Better-off pupils are significantly more likely to go to university than their more disadvantaged peers. And the gap between the two groups – 18.8 percentage points – is the widest it’s been since 2006/07.

    The latest statistics show that 26.3% of pupils eligible for FSMs went on to university in 2018/19, compared with 45.1% of those who did not receive free meals. Only 12.7% of white British males who were eligible for FSMs went to university by the age of 19. The progression rate has fallen slightly for the first time since 2011/12, according to the DfE analysis.

    Please follow and like us:


    Quality Training

    From Raconteur. A recent report by global learning consultancy Kineo examined the learning intentions of 8,000 employees across 13 different industries. It found a huge gap between the quality of training offered and the needs of employees. Of those surveyed, 85 per cent said they , with only 16 per cent of employees finding the learning programmes offered by their employers effective.

    Please follow and like us:


    Other Pontydysgu Spaces

    • Pontydysgu on the Web

      pbwiki
      Our Wikispace for teaching and learning
      Sounds of the Bazaar Radio LIVE
      Join our Sounds of the Bazaar Facebook goup. Just click on the logo above.

      We will be at Online Educa Berlin 2015. See the info above. The stream URL to play in your application is Stream URL or go to our new stream webpage here SoB Stream Page.

      Please follow and like us:
  • Twitter

  • Recent Posts

  • Archives

  • Meta

  • Categories