Open networks and bounded communities: Tensions inherent in releasing Open Educational Resources
Bibliographic record
Abstract
The ubiquity of networked and social technologies provides an environment within which new approaches to knowledge sharing and co-construction have flourished. This trend in knowledge co-construction is taking place within a society that increasingly is open. \nOne of the most visible manifestations of emerging approaches to knowledge sharing within the formal education domain is the discourse around Open Educational Resources (OER). OER have been defined as, “digitised materials offered freely and openly for educators, students and self-learners to use and reuse for teaching, learning and research” (OECD, 2007). \nIdeas around OER originated around 2002 through the Education Program strategic plan of the Hewlett Foundation on Using Information Technology to Increase Access to High-Quality Educational Content (Atkins, Brown, & Hammond, 2007) and the MIT Open CourseWare initiative (see the chapter by Vale and Littlejohn in this volume). OER has been informed by concepts around open and distance learning, open access to knowledge, free sharing and peer collaboration. Activity around Open Educational Resources has been prolific over the past decade: from a standing start 10 years ago, a Google search on open educational resources now produces over 163million results. \n \nThe origins have focused OER activity around content production, release and use in education, rather than the wider use and benefits of OER for learning in general. While potential benefits of OER have been recognised (OECD, 2007; McGill, Beetham, Falconer, & Littlejohn, 2010; Yuan, MacNeil, & Kraan, 2008), OER release and use are not widespread professional practices, even within the education sector, and understanding of the impact on teaching and learning is limited. While it is recognised that the release of OER in itself does not automatically lead to use by others (Lane & MacAndrew, 2010; McGill et al., 2010), the contexts within which OERs can impact on the learning practice and/or the professional practice of academics are unknown. \nOn the surface, educational communities of practice such as subject communities seem ideal settings to encourage and support the release and sharing of Open Educational Resources. However, earlier studies have flagged inherent difficulties in the community release of online resources – for example to create economies of scale (Margaryan & Littlejohn, 2008). Firstly, academics dealing with day-to-day, immediate work issues tend to focus on short-term goals, missing potential longer term gains associated with releasing resources that can be used by (unidentified) others (ibid). Secondly, academics place importance on contextual factors that conflict with the idea of open reuse of resources across a range of contexts (ibid). Thirdly, although communities provide a trusted environment for changing professional practice, long-term these communities can become inward facing, inhibiting potential growth, creativity and innovation (Littlejohn, Beetham, & McGill, 2012). These underlying tensions inherent in the enterprise of OER release and the role of communities may undermine successful implementation of OER initiatives yet are often overlooked by policy makers and practitioners (Littlejohn & Margaryan, 2010). \nThe characteristics of bounded communities, where people have tight links with colleagues and learners, are at odds with the diverse needs of a wider group of (often unknown) users in open networks (Margaryan & Littlejohn, 2008). Bounded communities – for example groups of academics working within a single subject discipline - tend to be more tightly knit than dispersed groups, such as industry subject experts who are seeking resources to teach a specific concept. Academics, particularly those who are used to teaching within conventional ‘closed’ courses, often fail to consider the wider groups of people who may benefit from the resources released. \nDimensions affecting communities include the purpose (shared goal and interests), interaction (modes of participation and communication), roles and responsibilities, coherence (whether the community is close-knit or loosely confederated and transient), context (the broader ecology within which the community exists), rules (implicit and explicit rules that govern the functioning of the community) and practices (predominant approaches used in the community) (Margaryan & Littlejohn, 2008). These characteristics vary across different user communities, which may cause problems if OER are designed for a specific group of users, making them less adaptable by individuals and groups across a range of diverse communities. \nThe aim of this chapter is to surface intrinsic problems in the release of OER within communities bounded by common expectations, practices or other parameters. We focus on emerging rules and roles relating to new professional practices. These were identified within the context of the UK Higher Education Academy and Joint Information Systems Committee’s (JISC) UKOER pilot programme.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".