Mentoring analytics LAK 2012


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The language of mentoring has become established within the workplace and has gained ground within education. As work-based education moves online, we see an increased use of e-mentoring. This presentation explores some of the challenges involved in forming and supporting mentoring relationships virtually, and the solutions afforded by online social learning and Web 2.0.

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  • Preliminary work Thinking about mentoring in a new context Thinking about how analytics could be used to support it.
  • Distance university withsdtudents worldwide SocialLearn promoting social and interpersonal connections How can we best support mentoring relationships on a social learning platform? Do we know what ‘mentoring’ means in a Web 2.0 environment?
  • Previous research that OU students seek out unofficial mentors amongst their friends, relations and colleagues. They seek out someone who can act as a sounding board and provide support, ideas, and guidance. Is there a way of providing this support on a social learning platform – and can analytics help?
  • Literature based on face to face mentoring: three main models Apprenticeship: learn through observing and copying Competency: mentor provides feedback on performance Reflective: mentor seeks to develop self reflection in mentee.
  • Mentors are unlikely to be chosen at random. Depending on the context, any or all of these elements are likely to be relevant Social learning platform needs to provide ways of assessing these elements if successful mentoring relationships are to develop.
  • Online tool to support mentoring Implied a committed relationship that didn’t tally with our experience of receiving support in social media environments. Did not provide personal information that allows you to select a mentor Should be a role for learning analytics in supporting the mentoring relationship Developed by Thomas Ullmann (Open University) in partnership with the University of Bristol
  • Multiple overlapping relationships May be open and freely available Does not require a face-to-face relationship This example is on Twitter, but it is incidental to Twitter – so how could it be incorporated in a platform tuned for learning? So we can see that Web 2.0 mentoring is not necessarily like F2F mentoring – and may be challenging what you think of as mentoring. Our students were looking for someone who can act as a sounding board and provide support, ideas, and guidance.
  • Online, profiles provide a simple way of collecting some of this information. Site analytics can recommend new connections They aren’t recommending learning relationships . Friends of friends may not be the people who will introduce new ideas, evaluate your ideas, challenge your ideas…
  • Developing the prototype We wanted to put our work on social learning and its requirements Together with our ideas on mentoring This would require a platform which allowed people to: provide support, supply ideas, offer guidance, act as sounding board
  • Work on social networks suggested the importance of the role of mediating artefacts These can act to strengthen weak ties And to activate latent ties
  • Pilot studies with SocialLearn Participants looking for different types of connection
  • Analytics bring together these sets of information about how learners are doing this now. Suggest other iterations – relevant people, relevant content and relevant actions. Begin to play a mentoring role themselves - providing support, ideas, and guidance. This model developed by Haiming and Ronald
  • Actions are keys to the development of mentoring. Provide personal information that allows us to judge a potential mentor or mentee Provide hooks that help link people with potential mentors
  • These have been built into the system
  • Lots of actions allow you to engage with people, to engage with content, to engage through content
  • Wire frames of the next stage – developed by Haiming and Ronald Analytic powered recommendations Available on site and through tool bar
  • In summary
  • Here we are on SocialLearn
  • Mentoring analytics LAK 2012

    1. 1. Using analyticsto establish e-mentoringrelationships in anonline social environmentHaiming LiuRonald MacintyreRebecca Ferguson
    2. 2. 2
    3. 3. OU students adopt mentorsBouncing ideas off my manager has helped becausehe has been able to relate some of the theories to our business, therefore making it easier to understand.I found discussing this course with work colleagues and friends the Mentors provide:most helpful, they were able to help • Support me relate the assignments to my • Ideas job and gave alternative • Guidance suggestions and their varied • Sounding opinions help to widen my view. board 3
    4. 4. Classic mentoring models CompetencyReflective Apprenticeship 4
    5. 5. Personal factors are significant More technical experience Same language Different statusSimilar interests 5
    6. 6. Model 1: Elliment developed by Thomas Ullmann 6
    7. 7. How is online mentoring different?• Support• Ideas• Guidance• Sounding board 7
    8. 8. Mentoring analytics• Shared interests• Shared contacts• Profiles• Activity history• Analytics 8
    9. 9. Users need to be able toExpand contactsLocate relevant groupsObserve mentoring in actionIdentify opportunities to engage • Provide support • Supply ideas • Offer guidance • Act as sounding board 9
    10. 10. Building & strengthening linksMediating objects can• strengthen weak ties• activate latent ties 10
    11. 11. User study • Camtasia • Talk aloud • Interviews 11
    12. 12. 1 Connect with content3 Connect through content 2 Connect with people 4 Employ different actions 5 Recommendations 12
    13. 13. Connecting with content • Bookmarking • Collecting • Commenting • Rating • Tagging 13
    14. 14. Connecting with people • Connecting • Following • Friending • Helping 14
    15. 15. Connecting through content• Added to content• Created content• Engaged with content• Evaluated content 15
    16. 16. Model 2: Analytics based 16
    17. 17. Mentoring in social mediaMultiple overlapping relationshipsMay be open and freely availableDoes not require a face-to-face relationshipKey data for analyticsActions connecting with peopleActions connecting with contentActions connecting through contentPotential for analyticsStrengthen inter-personal linksProvide opportunities for mentoringProvide a form of mentoring 17
    18. 18. Haiming LiuRonald MacintyreRebecca Ferguson