Open Ed Formal Learners

Editor's Notes

• #15: Most responses came from the USA (n=862) or the UK (n=473) though India (n=117) Canada (n=87) and Brazil (n=84) also contributed significant amounts of data. Most countries were represented and people from every continent contributed information. Excluding Africa, only Bolivia, French Guyana, Greenland, Kyrgyzstan, Suriname, Turkmenistan, Uzbekistan, and Venezuela were not represented. Most countries recorded between 5 and 40 responses.
• #16: Users of iTunesU showed a much lower average age profile with 71.8% of their users aged below 35. By contrast, OpenLearn users tended to be older, with 69% aged 35 or over and relatively few younger users. The pattern of user age profiles was closer to a standard deviation for Saylor users (perhaps reflective of a larger sample size).
• #17: Saylor users were more evenly split between male and female (and had a greater proportion of users who identified as transgender) while iTunesU users were more slightly more likely to be male. OpenLearn showed the largest difference in the gender of their users, with female users outnumbering male users by approximately half.
• #18: As is perhaps to be expected given the age profiles associated with the different repositories (Figure 3) iTunesU users, generally younger, were most likely to report holding a school leaving qualification as their highest. But as Figure 3 shows, the general trend was that users of these platforms tended to report already holding a degree. 59% of Saylor users held at least an undergraduate degree. The proportion of university graduates for OpenLearn and iTunesU were 46% and 38.2% respectively
• #19: Saylor users were much more likely to be in full time employment (52%, n=2300) while the majority of iTunesU users (43%, n=110) were in full time education. iTunesU also had the highest proportion of users who volunteer part time (15%, n=110). Approximately 40% of OpenLearn users were in full-time employment, and OpenLearn had the highest proportion of retired users (14%, n=732).
• #20: 10% of users disclosed a disability (n=3160). OpenLearn had the highest proportion of users who identified as disabled (15.7%. n=737) while Saylor reported the lowest proportion of disabled users (7.9%, n=2298). The relatively high rate of declaration by OpenLearn students may reflect similarities to the approach taken to improving accessibility at The Open University through an inclusive framework which covers human and technical elements from course production through to evaluation (McAndrew, Farrow & Cooper, 2012). Figure 7 provides more information on the types of disability reported, and shows that long term or chronic illnesses and mobility impairments were more commonly reported by OpenLearn users while mental health problems more likely to be reported by iTunesU users. iTunesU users were also much more likely to declare a speech disability. It should be noted that some respondents declared more than one disability.
• #23: Across the entire sample (n=2356) the most popular subjects for OER were computing (31.1%, n=732) and economics (30.4%, n=716).
• #24: Saylor users were marginally more likely to cite the flexible and online nature of the resources while OpenLearn users were more likely to state that the chance to try university level content was important to them.
• #25: YouTube is the most popular place to find open resources, with over 50% of each sample reporting that they used it to find OER. iTunesU and TED talks were also popular across the samples, as was Khan Academy (though less so with users of OpenLearn).   Saylor users were much more likely than the other groups to be studying via MOOC platforms (41.7%, n=751).
• #26: We see a striking similarity between the responses given across the two samples. The most important criterion (for approximately 70%) was relevance to a particular need; i.e. OER were sought to plug a specific gap in knowledge or skills. The reputation of the OER creator (whether an individual or repository), clarity around learning outcomes or objectives, and ease of download or access were all cited as important. Less important were reviews of OER or personal recommendations. Open or Creative Commons licensing allowing adaptation was only thought important by a minority of 12-16% which is interesting given the high level of adaptation rates reported elsewhere (see Fig. 12). It may be that non-formal learners adapt OER without paying much attention to licensing permissions.   The least important factors appear to be the attractiveness of the presentation of a resource and whether an OER has previously been used in an institutional context. In the case of the latter it should be noted that despite this, more than 50% of the samples thought that the reputation of the resource creator was important and this reputation is often closely associated with institutional affiliation. Both Saylor (20%) and OpenLearn (21%) users identified a resource being required for formal study as important, suggesting that some of these learners may be using OER in lieu of non-open materials required for their formal studies.
• #27: Between 16% and 25% of each sample believed that lack of support from a teacher or tutor was a challenge to their learning with OER. This could be seen to reflect a general level of confidence around independent, non-formal study among these groups, but still identifies a significant proportion who feel that they would benefit from more support of this kind.
• #28: The general pattern suggests that most non-formal learners on these platforms are not using many of the techniques described. Saylor users were more likely to report using a calendar or journal to organize their study as well as using specialized note-taking software; no OpenLearn user reported using either of these. Writing study notes was in general more common among Saylor users (60.2%) while OpenLearn users were more likely to use a blog to record and organize their learning. Significant proportions of both samples said that they discussed their learning with others either face-to-face, via online forums, on social networks, or, less commonly, through micro-blogging platforms like Twitter or Tumblr.
• #29: Saylor users were much more likely to report engaging in processes that support OER production and evaluation. Although the sample size for this question was smaller, it is remarkable that more than 80% of Saylor users who answered claim to have adapted open materials for their own purposes as non-formal learners. (iTunesU users were not asked this question.) This is an interesting and counterintuitive result, possibly affected by different understandings around the concept of adaptation
• #32: . Between 69% and 74% would recommend the repository to others and approximately half would share them directly with others (though the figure was slightly lower for OpenLearn at 44%). High proportions across all samples indicated that they would download further materials from the repository and feel empowered to undertake further study in a related area. Polarization with regard to likelihood of formal study. In each case those who answered ‘more likely’ or ‘less likely’ to this were about equal in number. OpenLearn users reported slightly greater likelihood of going on to formal study; this is perhaps reflective of the structured pathways leading from OpenLearn to degree programme course credits. The vast majority of those surveyed said that they would continue to use OER in the future – 84.8% across the three samples as a whole. 
• #35: http://cdn.xl.thumbs.canstockphoto.com/canstock18561873.jpg