Using the data from the OER Research Hub
Given the topicality of the OER Research Hub recent research outputs we are pleased to be able to reproduce on our blog a post from Robert Schuwer on how he is using the data that the OER Research Hub has generated, especially that on formal learners and educators.
The post was authored by Robert Schuwer and edited on to the blog by Paul Bacsich. For Robert’s original posting see http://robertschuwer.nl/blog/?p=1213
Dr Robert Schuwer is Lector (Professor) OER at Fontys University of Applied Sciences, School of ICT in Eindhoven, the Netherlands. Since 2006 the majority of his work is about OER and Open Education. His experiences and research interests are in open policies, business models for OER and adoption of OER-based processes, on institutional, cross-institutional and national level. He is chairman of the Dutch Special Interest Group Open Education, established by SURF – and chairman of the Information Center Committee of the Open Education Consortium. He was an active researcher on the POERUP project and for that wrote the OER policy options brief on the Netherlands.
In the previous weeks, the OER Research Hub published results of their latest surveys on OER. In total 7500 responses were received. The results were presented for the categories Informal learner, Formal learner and Educator. Instead of creating large reports with results, they made short summaries of each category and published infographics. The full dataset is available for further analysis (in CSV-format or Excel-format).
In this blogpost I focus on formal learners (and educators. Using the infographics, I have compared some results and using the dataset, I created some cross-links between different data in the dataset.
The following table gives a break-down of responses on being US-resident or not and having English as first language or not for both educators and formal learners. Blank responses on either item are not counted.
Formal learners | Educators | ||||||
US | Non-US | Total | US | Non-US | Total | ||
English | 595 | 675 | 1270 | 398 | 551 | 949 | |
Non-English | 169 | 660 | 829 | 39 | 491 | 530 | |
Total | 764 | 1335 | 2099 | 437 | 1042 | 1479 |
Because of the stimulation programs in the US to adopt open textbooks, I was interested in comparing the use of open textbooks by both educators and learners in the US and outside of the US, and if having English as the first language influences this (assuming most open textbooks are in English). Related to the break-down the following percentages of use are extracted:
Use of open textbooks | |||||
Formal learners | Educators | ||||
US | Non-US | US | Non-US | ||
English | 76% | 54% | 48% | 38% | |
Non-English | 86% | 77% | 51% | 50% |
It seems open textbooks are more used by formal learners than by educators, more in the US than outside and more by non-English speaking users.
On the impact of using OER, a comparison between the infographics reveals that both learners and educators agree on the top-2 (educators counting (strongly) agree):
On challenges for educators when using OER, I was interested in the effect of teaching experience and subject area. The following table shows the percentage of educators per subject area that consider Finding suitable resources in my subject area a challenge. The column Total displays the total number of educators having indicated they use OER for that subject area (more than one subject area is possible per educator)
Total | #Challenge | % Challenge | ||||
Math | 233 | 96 | 41,2% | |||
Science | 434 | 162 | 37,3% | |||
Languages & Linguistics | 200 | 71 | 35,5% | |||
Social Science | 201 | 71 | 35,3% | |||
Literature | 155 | 52 | 33,5% | |||
Computing & information science | 175 | 57 | 32,6% | |||
Health & Social Care | 102 | 33 | 32,4% | |||
Psychology & Philosophy | 194 | 60 | 30,9% | |||
History & Geography | 172 | 51 | 29,7% | |||
Medicine | 88 | 26 | 29,5% | |||
Education Studies | 201 | 59 | 29,4% | |||
Applied science & engineering | 148 | 41 | 27,7% | |||
Physical Education | 57 | 15 | 26,3% | |||
Special Education | 46 | 12 | 26,1% | |||
Arts | 153 | 39 | 25,5% | |||
Economics, Business & Management | 134 | 34 | 25,4% | |||
Religious studies | 74 | 13 | 17,6% | |||
Total | 2767 | 892 |
This result surprises me a bit. Considering Math and Science as two areas with a lot of OER available, I would have expected finding suitable resources less a challenge. Maybe the wealth of resources, poorly described by metadata, is an explanation. Overall, support for finding suitable resources is very useful because for most subject areas more than 25% have difficulties with this.
The last two analyses I have performed is to find out about the influence of teacher experience. The following figure displays experience vs the way OER is used by the educator.
It seems the more experience an educator has, the more activities with OER are undertaken. Furthermore, community-based activities like adding comments to a repository are less common than creating and publishing resources.
Finally, the next two figures displays challenges in using OER, related to teaching experience of an educator. The first one considers the challenges related to doubt and difficulties with OER.
It seems that educators having >10 years of experience encounter more challenges in finding the right resources and judging the quality of them than educators with less teaching experience. The previous figure indicates that the latter category uses OER less, and therefore did not encounter these challenges.
The next figure displays the challenges in using OER, posed by the environment of the educator.
Again, educators with the most teaching experience encounter the most challenges, with not having enough time to look for suitable resources as the largest challenge. This can be overcome to both provide this time by the institution and to improve support on findability of the right OER.
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