What research questions the project addresses, aims & themes
Escalation of social groups self-organising learning results in a) learning focused around concepts of interest to groups and b) social influence of individuals on the discourse. The ability to self-assemble and participate in online, informal learning events can be viewed as a basic human right. In a democracy everyone should have the ability /responsibility to set up informal, open learning events to learn and to and facilitate the learning of others).
Informal learning events (such as an Editathon) can be categorized as deliberative learning (Eraut, 2004), where individuals specifically dedicate time and effort to think about a certain topic and contribute to the pool of information and insights of a larger group. An assumption underlying deliberative learning is that is that individual learners have the skills and dispositions necessary to learn autonomously and socially. However, learners differ in their ability to self-regulate their learning in online, informal learning contexts (Milligan, Littlejohn and Margaryan, 2014). Self-regulation is positively associated with academic achievement (Zimmerman & Schunk, 2001; Bernacki, Aguilar & Byrnes, 201; Azevedo, & Cromley, 2004). Self-regulation has been defined as ‘self-generated thoughts, feelings and actions that are planned and cyclically adapted to the attainment of personal goals’ (Zimmerman, 2000). Zimmermann’s theory positions self-regulation of learning across these three phases - forethought, performance and self-reflection - within which a range of cognitive and socio-cultural sub-processes have been shown to influence learning, such as motivation, interest, self-efficacy, goal-setting, critical thinking, help-seeking, learning strategies, self-evaluation and self-satisfaction. These metacognitive strategies can be used to increase learning effectiveness.
Under these circumstances, the concept of social capital plays an increasingly prominent role in analyzing and identifying the possible benefits and opportunities of SNS for (informal) learning. This research is examining the dissemination of social capital and professional learning in an informal learning setting, asking the questions:
1. How do learners self-organise to exchange information online? (method: social network analysis)
2 How do professionals self-regulate their learning in an editathon? (method: interview, theory: social capital theory)
3 Whether and to what extent are individuals able to accumulate social capital in the edititathon to learn? (method: interview/ survey, theories: social capital theory and self-regulated learning theory)
The research is underpinned by self-regulated learning theory, drawing on Zimmermann’s sub-factors (motivation, task analysis, self-evaluation etc) and social capital theory. We define social capital as “relational resources embedded in cross-cutting personal ties that are useful for the personal development of individuals" and self-regulation as ‘self-generated thoughts, feelings and actions that are planned and cyclically adapted to the attainment of personal goals’ .
The method integrates quantitative (Social Network Analysis, self-regulated learning quantitative survey) with qualitative (interview) methods. The instruments used have been adapted from previous validated research tools and include:
- a survey instrument with questions around sub factors of self-regulated learning and social capital.
- a semi-structured interview transcript.
Findings and outputs
Qualitative Interview Analysis: Emerging themes from Editathon Interviews
There were two key motivators for participation: (1) a desire to develop technical skills related to Wikipedia – how to write, post, reference, edit etc; (2) being invited asked by other participants/organisers to attend.
Participants displayed high levels of self-efficacy/confidence. Self-efficacy was related to one (or more) of three factors: (1) familiarity with/prior experience with technical skills required; (2) prior connections with other participants/pre-existing social capital; (3) confidence in ability to learn.
Social capital tended to be developed through person-to—person interaction. People tended to people seek help from others in the room when encountering a problem or issue when learning. Conversations were helpful for the sharing of information and for the validation of knowledge.
The presence of an “expert” (i.e. the Wikimedian) was an important component in facilitating learning.
While collaboration may have occurred offline, collaboration was less evident online, as one participant would be responsible for making edits to Wikipedia. None of the interview participants had edited other participants’ pages during the Editathon.
There was clear evidence of informal learning, even though participants did not necessary view themselves as learning. Even though learning was informal, there was a certain level of curation to the activity/learning and this was important. The structure of the sessions, where there was more formal training in specific skills at the beginning and then the ability to implement supported learning. Similarly the presence of the list of pages/people was useful to scaffold learning, as were the resources – books, newspapers etc – that were provided. There were tangible outputs/outcomes of learning. People could see what they had achieved and this was motivating. People felt that what they were learning/doing had an impact. It was an empowering activity for some.
Social capital continued to be disseminated after the editathon event. About half of the interviewees continued to contribute actively to Wikipedia. Most participants discussed the editathon with other colleagues who had not attended.For several people, participation had strengthened their professional social capital by introducing them to new people with whom they now connect/interact.
uctural dimension - we identified three types of social capital formation among participants: leaders (or initiators), collaborators and lone workers.
We also discovered participant activity was influenced by a number of factors, some of which were not detected via the digital traces. For example some of those who worked on one page not connected to other people/ pages picked the page that no one else was doing because the list encouraged them to.
These findings will be presented at OER16 at the University of Edinburgh
People involved / Project partners
The Open University, Institute for Educational Technology (IET), UK
Professor Allison Littlejohn and Dr Bart Rienties with Lou McGill
The University of Edinburgh, UK
University of Duisburg-Essen, Germany
Dr Martin Rehm
University of Auckland, New Zealand
Dr Nina Hood and Heli Kaatrakoski
The University of Edinburgh
Start date and duration
March 2015 – March 2016, 1 year