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The Open University

Qualified, self-regulated learners follow parts of a MOOC that helps them solve a problem

Posted by on Apr 27, 2015 in Higher Education, Professional Learning, Sustainable Learning | 0 comments

Understanding learning in Massive Open Online Courses is difficult, partly because methods and instruments for data collection are under-developed. Published work tends to be from data samples that are too small or skewed. Dropout rates in MOOCs mean that the learners who participate in studies show persistence, therefore samples are not representative. Even if this problem can be reduced, the environment is distributed and varied, so there are multiple variables making data difficult to analyse.

Published research shows that the research methods used tend to analyse registration, participation, retention & progression, completion or assessment data, but none of these conventional course metrics measure learning in a MOOC. The reason is rooted in learners’ motivations for participating in a MOOC. Some learners want to complete the course and gain the certificate, others want to learn specific knowledge or gain skills. Learners in a MOOC don’t have direct instruction from a tutor. The courses have a self-guided format that requires learners to regulate their own learning. Therefore we should expect learner behaviour to vary.

This is particularly true for learners who are working in an area related to the MOOC. Professionals already have (at least baseline) qualifications and tend to have learned how to self-regulated and are motivated. Employers are interested in MOOCs for professional training and learning, yet little is known about how people learn in these open, online environments.

Colin Milligan and I were funded by the Bill and Melinda Gates Foundation MOOC Research Initiative to examine how professionals learn in MOOCs. Data was gathered and analysed with help from Lou McGill, Paige Mustain and Nina Hood. We used self-regulated learning theory as a framework to examine cognitive, affective and behavioural factors influencing learners. These factors range from motivation, interest, confidence and goals to interest-enhancement, learning strategies, critical thinking, help-seeking, self-reflection and self-evaluation. http://www.gcu.ac.uk/academy/pl-mooc/

We wanted to test the hypothesis that learners with high self-regulation have different cognitive, affective and behavioural responses to learning in a MOOC than those displaying low self-regulation. Self-regulated learning is not a ‘learning style’. Rather, it’s a response to a learning situation. Many of the cognitive, affective and behavioural factors can be transformed towards good self-regulation ability. Some factors are relatively easy to influence (for example help-seeking or learning strategies) while others (for example confidence) are more difficult. Nevertheless there is opportunity here to gain insight from both learning and teaching perspectives.

We studied in detail how people learned in two MOOCs: Introduction to Datascience (Coursera and the University of Washington) and Fundamentals of Clinical Trials (edX and Harvard University).

Introduction to Datascience was run by the University of Washington from September to December 2014 using the Coursera platform. There were 40,000 registered learners, though only around one-tenth of these users were active within the MOOC. The research design involved quantitative data gathering using a psychometric survey instrument, designed to measure learners’ perceived self regulation on the course. The MOOC participants were contacted via a course announcement in week 2 (of 8). 280 individuals completed the survey. Participants were asked whether they would agree to a follow-up interview. The quantitative data was combined with qualitative data gathered through semi-structured interviews with 35 participants.

Introduction to Datascience was run by the University of Washington from September to December 2014 using the Coursera platform. There were 40,000 registered learners, though only around one-tenth of these users were active within the MOOC. The research design involved quantitative data gathering using a psychometric survey instrument, designed to measure learners’ perceived self regulation on the course. The MOOC participants were contacted via a course announcement in week 2 (of 8). 280 individuals completed the survey. Participants were asked whether they would agree to a follow-up interview. The quantitative data was combined with qualitative data gathered through semi-structured interviews with 35 participants.

Learners who perceived themselves as exhibiting low self-regulation tended to be focused on completing the course and gaining the certificate. By contrast, highly self-regulated learners wanted tended to link their participation in the MOOC to work performance or personal interest:

“The most important factor… is not even how much I learn, but how big the impact of my work can be to the outside world” (HSRL, 119)

This motivation impacted learners’ goal-setting, self-evaluation and self-satisfaction. Highly self-regulated learners tended to link learning goals with work and were more strategic about where they focus effort:

“The way to approach it [learning] is to follow what interests me and not worry too much about trying to keep a complete overview of the area… I plan to complete all of the assignments[but] I won’t be too worried if I don’t.”(HSRL, 428)

We found evidence that highly self-regulated learners self-evaluate against their own benchmarks and identify progress in relation to intended aims. Learner satisfaction may be high because the learners are self-evaluating their progress against their own goals and ambitions:

“I’m… very satisfied with what I did during the course and what I’ve got out it at the end.” (HSRL, 247)

“Well now I’m feeling more powerful, I can do some things, I am confident in finding solutions for problems that are too big for me right now” (HSRL, 670).

By contrast low self-regulators are focussed on following the instructional pathway and completing the course. Self-evaluation is more difficult for these learners because they are trying to evaluate against externally enforced benchmarks set by instructional designers. This situation impacts on self-satisfaction. When asked about self-evaluation, low self regulators responded:

“It’s hard for me to gauge how much I’ve understood something… sometimes we have a blindness about it ourselves” (LSRL, 236)

“Yeah that’s a difficult question because I don’t perceive my own learning” (LSRL, 396).

These factors impact on learners’ task-strategies (the ways learners approach learning and performance by reducing a task to its essential components and reorganizing these parts meaningfully). Learners who perceive their learning as low-self-regulated try to carry out all (or most) of the MOOC activities, in contrast to high self-regulators who are more strategic about where they focus effort. When asked about whether and how he followed the course pathway, one high self-regulated learner responded:

“Carefully curated parts. So not as a whole, I’m going to be picking through what nuggets are of use to me in particular contexts” (HSRL 505).

Fundamentals of Clinical Trials was one of the first Harvard University MOOCs. It was developed by the Harvard Medical School, Harvard School of Public Health and Harvard Catalyst and ran on the edX platform from November 2013 until April 2014. The MOOC had

24,000 registered learners. The research design used the same method and instruments as used in the Introduction to Datascience study. Learners were invited to participate in the research via a course announcement in week 5 (of 14). 350 learners responded and completed the psychometric Questionnaire. 30 participated in semi-structured interviews. These learners were located in various countries around the world, with 5 in the US and 6 in India (see Figure 1):

In this course we observed a shift in the motivations of those who viewed themselves as highly self-regulated, with both the high and low self-regulated groups being motivated to gain a Harvard certificate. Although both high and low self-regulated groups had the same overall motivation, their approach to goal-setting and learning strategies was different.

Similar to the Introduction to Datascience Course, low self-regulators tended to follow the course ‘pathway’ set out by the instructional designers:

“I do download the study material which is provided by the course website, but while I watch the video I do not have a habit of making notes and I am a person who is organised in a mess. So even if I make a note I don’t recollect and read those notes.” (LSRL, 295)

“I’ve tried to go through the questions first and then go back and review the text to see…and that forces me to kind of focus on the topics a little bit more as opposed to if I go to the lecture and then try to do the questions I find myself zoning out during it.” (LSRL, 360)

However the high self-regulators tended to be more strategic about where they focused their effort:

“I don’t put too much effort into what I’m learning, but this course – looking at the videos I get to take my time to understand. Sometimes I watch the video twice, which has really helped me to have a better understanding when I’m learning.” (HSRL, 284)

In summary we have evidence that in both courses learners who are already qualified and self-regulated tend to follow parts of a MOOC that helps them solve problems. Conventional course metrics, such as progression & retention or completion rates, are poor measures of potential learning gains for professional learners in MOOCs. We need a rethink of certification, completion and measures of success in MOOCs.


For further discussion see the panel discussion led by Yishay Mor and Laia Canals at the #OER15 Conference tinyurl.com/q7ormnl and also littlebylittlejohn/mooc-measures



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#MOOC certification, completion, and measures of success

Posted by on Mar 30, 2015 in Professional Learning | 0 comments

In April 2015 am participating in a panel session at #OER15 led by @YishayMor and Laia Canals.  MOOCs enable new forms of organisation mediated by digital technology. However, governments, universities, educators and even learners still apply conventional metrics around learning, assessment, completion which limits the potential of #MOOCs.

MOOC providers seem to be concerned with completion rates – but are learners content to drop in (and out) to learn the knowledge they need? (eg see our paper on Patterns of Engagement in Connectivist MOOCs http://jolt.merlot.org/vol9no2/milligan_0613.htm)

During our panel session we will debate important questions such as

In the spirit of openness, we invite you to participate in this event by contributing to the online discussion. During the conference, we will conduct a live panel with some of the contributors which will be joining us in person or virtually. Panelists will refer to the contributions online, and we will use social media to facilitate live interaction with the audience outside the room. So you dont need to be at the conference to join in.

We invite you to participate in the debate by leaving your comments or video responses on the following 4 discussion spaces:

  • Certification, completion, and measures of success: while some MOOCs participants and employers see certification as important, others are happy with their own sense of achievement, getting what they want and moving on. MOOC providers seem to be concerned with completion – but are learners happy dipping in and getting the bits they need? Some learners find certification attractive, even if they don’t need the formal proof – perhaps as an indicator of the MOOC’s quality.

  • What makes an effective MOOC learner? Is effectiveness in the eyes of the provider identical to effectiveness in the eyes of the learner? What do employers see as effective learning? Are some learners more “qualification effective” and others more “growth effective”? Is lurking sometimes an effective strategy? Do analytics capture effectiveness?

The event’s online space is: http://openeducationeuropa.eu/en/node/167498 and we will use tags  #OER15 and #webmoocs.

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Professional Learning in Massive Open Online Courses

Posted by on Apr 3, 2014 in Higher Education, Professional Learning | 0 comments


  • A study by researchers at Glasgow Caledonian University and Harvard University published April 2014 found that massive open online courses (MOOCs) encourage passive learning among professionals.
  • MOOCs miss the opportunity to exploit the knowledge and expertise diverse groups of healthcare professionals bring to the course.
  • The research recommends that MOOC designers focus on capitalising on the diversity of MOOC participants and professionals are encouraged to link MOOC learning with their everyday work practice.
  • The study, funded by the Gates Foundation, was the first to examine learning behaviours of professionals in MOOCs.
  • Findings are available from: http://www.gcu.ac.uk/academy/pl-mooc/findings


As healthcare knowledge grows exponentially, health professionals around the world need to continually engage in high quality learning. Health professionals seeking ways to upskill their knowledge are participating Massive Open Online Courses (MOOCs); free, online courses with unlimited participation offered by some of the world’s leading universities. MOOCs enable access to thousands or hundreds of thousands of co-learners, opening up opportunities for new forms of learning.

A recent study found employers generally viewed MOOCs positively for recruiting, hiring and training employees. However, a study by researchers at Glasgow Caledonian University, funded by the Gates Foundation, was the first to examine the learning behaviours of professionals in MOOCs.  The findings show MOOCs may encourage passive learning, missing opportunities to exploit the knowledge and expertise diverse groups of professionals bring to the course.

“MOOCs have quickly grown in popularity, but we know very little about whether MOOCs improve learning,” said Professor Allison Littlejohn, (PhD), principal investigator and Director of the Caledonian Academy, a research centre at Glasgow Caledonian University. “Our knowledge of learning in MOOCs is based mainly on anecdotal accounts. The lack of scientific evidence around how people learn in MOOCs is risky, considering the investment of public resources being channeled into MOOCs by universities and governments. We wanted to know if MOOCs allow health professionals to improve their learning and whether there is any impact on their professional practice.”

The researchers from Glasgow Caledonian University worked with educationalists from the Harvard Medical School, Harvard School of Public Health, and Harvard Catalyst, the Harvard Clinical and Translational Science Center. Between November 2013 and February 2014 they surveyed almost 400 participants of ‘Fundamentals of clinical trials’, a MOOC for health professionals offered via the edX platform. The team measured participants’ capability to self-regulate their learning, then interviewed 35 health professionals in 23 countries to investigate their learning behaviours. Lou McGill, a Caledonian Academy researcher, explained, “While MOOC designs take a variety of shapes and forms, the Fundamentals of Clinical Trials MOOC represents a course design typical of the key MOOC providers, therefore we could build some generalizable conclusions.”

“We had an indication of each individual’s capacity to self-regulate their learning and were interested in exploring whether high ability would make a difference in terms of their qualitative learning behaviours within the MOOC,” said Dr Colin Milligan (PhD), co-investigator on the project and researcher within the Caledonian Academy. “We’ve observed that the highly structured MOOC design focuses on content provision, which the participants are very positive about. However the structure does not encourage learners to actively self-regulate their learning. If anything, participants, even those with high self-regulated learning ability, tend to limit their activity to reading and interacting with course content, overlooking opportunities to use the theory they’ve learned to improve their practice.”

Participants had a range of reasons for signing up for the MOOC, ranging from filling gaps in their current knowledge to preparing for future career opportunities. The researchers found that highly self-regulated learners articulated more precise learning goals and expectations compared with low SRL participants, even where their motivations for joining the MOOC were the same. However, when they participated in the course, there were few differences in the behaviours of high and low self-regulated learners. All learners exhibited fairly passive behaviours in the highly structured MOOC environment.

Learners focused on activities such as watching videos and taking tests, with little evidence of learners relating new knowledge into practice, or of connecting to their peers though the discussion board. To be effective, professional learning should provide opportunities to integrate theoretical and practical knowledge. But even those learners who said they wanted to improve their professional practice did not integrate the scientific knowledge they learned through the MOOC with practical, on-the-job learning.

We need a cultural shift around conceptions of learning and teaching and of learner and teacher roles to capitalise on the experience and expertise that professionals bring to their learning.

The data provides a basis for recommendations for the design of MOOCs to support professional learning. The first three focus on improving the link between theory and practice while the second three capitalise on the diversity of the people participating in the MOOC environment, encouraging the development of regulatory expertise.

These recommendations are available from:  http://tinyurl.com/PL-MOOC-recommendations

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Digital resources for open, online learning: its in the use

Posted by on Jan 7, 2014 in Higher Education | 0 comments

In examining the usefulness of open, online resources for learning, we have to look not only at the resource but also relationships between resources, users, and the ways resources were used  (Engestron, 2007: Littlejohn, Falconer & McGill, 2008; ).

Use is critical because online resources do not encapsulate the scientific and instrumental  knowledge needed to support learning and development (Francis, 2013; Falconer & Littlejohn, 2007). Scientific knowledge is (generally) explicit and codified while instrumental knowledge  involves solving specialist, practical problems (Boshuizen & van de Wiel, 2013). Learning scientific and instrumental knowledge requires open interactions with other people (teachers, experts, peers) (Engeström, 1999). Paavola & Hakkarainen’s (2005) work illustrates learning interactions around online resources to gain scientific and instrumental expertise through collaborative knowledge construction. In these examples open, online resources serve as a focal point for the co-ordination of learning (either by a teacher or expert, or by learners themselves), rather than as ‘learning materials’ in the conventional sense.

As learners gain expertise there is a qualitative change in the way they use resources to realise activities, moving from rule-based actions to fluid, self-directed activities (Dreyfus and Dreyfus, 2000). Therefore expertise is illustrated by the ways an individual uses the resources and how they relate to other people in their environment (Holland et al, 1998, p121; Edwards, 2010a, p25).

While working on a new book exploring the reuse of open, online resources for learning (Littlejohn & Pegler, 2014) I’ve been reflecting upon the different types of digital resources available for learning in networks, revisiting the idea of use.

Resources serve different purposes depending on how they are used, therefore resources could be characterised by use. Use can be viewed broadly at three levels: knowledge, experiential and analytic resources:

The education domain has pioneered the open release of knowledge resources often created by teachers or experts for learners.  With these resources, users are largely are unknown to the resource creators, since users can be anyone, anywhere, using the resource in any context; students registered for a course, professionals learning for work or lifelong learners. Knowledge resources are typified by (though not limited to) Open Educational Resources (OER), Open CourseWare (OCW) or Open Courses, including Massive Open Online Courses (MOOCs). Thee resources are available in a range of media, from textual materials (articles, e-textbooks, blogs, micro-blogs) to images, videos, audio and aggregations of these, generally sourced via search engines. Resources were created and released by universities, notably MIT (USA) and the Open University (UK), though many other universities, companies, charities and professional bodies are now producing and releasing resources, often under Creative Commons licences (McGill et al, 2013; Falconer et al, 2013). Materials are purposefully created to support learning, however open learning resources can also include dynamic resources that form and morph in a less predictable way than traditional educational resources. Knowledge resources can be created or co-created and adapted by learners themselves.  Beyond this are other types of open, online information resources that are routinely created and shared with others (or contributed to the collective) in ways that enable their reuse. For example the creation and development of a base of common or shared knowledge for professional learning or learning for work (Johnson et al, 1999). Professionals create codified resources as an output of work activity. Some resources have restricted access (emails, classified reports, and so on) but other resources are open, including reports, blogs, microblogs (for example hosted on Twitter or Yammer), images (for example Flickr, Slideshare), videos (for example YouTube), audio files and bookmarks (for example Delicious).

Experiential resources are widely used for professional and lifelong learning. These resources support the development of expertise that underpins practice. Experiential resources range from simulations in serious games or virtual worlds to digitally mediated interactions with people with relevant expertise. Interactions around these sorts of resources are sometimes qualitatively different than with knowledge resources. For  example the linux community – a community of people distributed around the world who share programming expertise by working collaboratively on the linux kernel computer code – use code as an experiential resource (Moon & Sproull, 2002). The openness of the kernel and fragments of code serve provide resources supported by community forums and others as learning resources for people who want to extend their programming expertise.

Analytic resources support learners in planning and instantiate their learning. As learners interact online, learning choices and behaviours can be captured, analysed and released as analytics data to allow individuals to plan and manage their learning. Systems and tools based on analytics provide an organising focus for learning (Littlejohn, Milligan and Margaryan, 2011). Each learner can manage his/her interaction with the people and resources that are important for learning, developing a personal view of learning which, in turn, relates to the learning of others. The significance of this sort of open system is that it brings together the individual with the collective in ways that are impossible with conventional closed (restricted access) learning resources. These data resources include user identity data generated through direct entry by the user, cross-referencing of identity information from different sites or from user behaviour. These resources can be used to support learners in expanding their relational expertise – or their capacity to understand who or what to connect to accelerate their learning – capitalizing on the collective expertise of people and knowledge resources within the network (Littlejohn, Milligan and Margaryan, 2012). Though relational expertise extends beyond the rational decision-making afforded through systems based on Artificial Intelligence and involves human interactions with the environment medicated by expertise (Edwards, 2010, p21).

Learners use and reuse open resources in and across these diverse contexts –  education, work and lifelong learning- which provide the framework for exploration of reusing open learning resources in the ‘Reusing Open Resources’ published in May 2014 (Littlejohn & Pegler, 2014).


Dreyfus, H., & Dreyfus, S. E. (2000). Mind over machine. Simon and Schuster.

Edwards, A. (2010b). Being an expert professional practitioner: The relational turn in expertise. Dordrecht, The Netherlands: Springer.

Engeström, Y. (2007). Enriching the theory of expansive learning: Lessons from journeys toward coconfiguration. Mind, Culture, and Activity14(1-2), 23-39.

Falconer, I., and Littlejohn, A. (2007). Designing for blended learning, sharing and reuse. Journal of Further and Higher Education, 31(1), 41–52

Falconer, I., McGill, L., Littlejohn, A., & Boursinou, E. (2013). Overview and Analysis of Practices with Open Educational Resources in Adult Education in Europe Review, JRC Scientific and Policy Reports, C. Redecker., J. Castaño Muñoz., & Y. Punie (Eds.). European Commission http://tinyurl.com/pk6nuvt

Johnson, B., Lorenz, E., & Lundvall, B. Å. (2002). Why all this fuss about codified and tacit knowledge?. Industrial and corporate change11(2), 245-262.

Holland, D., & Lachiocotte, W. D., & Cain, C.(1998). Identity and agency in cultural worlds.

Littlejohn, A.,  I. Falconer & L. McGill (2008) Characterising effective eLearning resources, Computers and Education 50 (3), 757–771 http://tinyurl.com/63okour

Littlejohn, A.  Milligan, C. & Margaryan, A. (2011). Collective learning in the workplace: Knowledge sharing behaviours. International Journal of Advanced Corporate Learning (iJAC) Available from: http://online-journals.org/i-jac/article/viewArticle/1801

Littlejohn, A., Milligan, C., & Margaryan, A. (2012). Charting collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24(3), 226–238.

Littlejohn & Pegler (in press) Reusing open resources, Routledge, New York.

McGill, L., Falconer, I., Dempster, J.A., Littlejohn, A. & Beetham, H. (2013). Journeys to Open Educational Practice:  UKOER/SCORE Review Final Report. Retrieved from https://oersynth.pbworks.com/w/page/60338879/HEFCE-OER-Review-Final-Report

Moon, J. Y., & Sproull, L. (2002). Essence of distributed work: The case of the Linux kernel. Distributed work, 381-404.


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Conflicting perspectives on MOOCs

Posted by on Dec 6, 2013 in Higher Education, Professional Learning, Sustainable Learning | 0 comments


Katie Vale and I  recently wrote a chapter on Massive Open Online Courses: a traditional or transformative approach to learning which will be published in 2014 in Reusing Open Resources (Routledge) http://www.taylorandfrancis.com/catalogs/educational_technology_e-learning/2/2/. In the chapter we explore the conflicting opinions and perspectives around MOOCs. These perspectives are rooted in the diverse origins of the concept of open education and open learning. Ideas around open courses emerged from three different arenas: universities, open learning researchers and the Open Access social movement.

The Open Access movement is a global network of people who support the transformation of work and learning practices towards free sharing and peer collaboration in society through open sourcing, open resources and the (re)use of open knowledge (Kaiwen & Fang, 2005). A central aim is to change societal expectations of how, when and where people learn. One strategy has been to eliminate barriers of entry into university-level education through opening access to the ‘fundamental building blocks’ of learning (Seely-Brown, 2008). These building blocks are viewed as Open Educational Resources (OER) – digital materials that can be used, re-used and repurposed for teaching, learning or research, made available online through open licenses, such as Creative Commons (McGill et al, 2013). OER and open courses are a lever sometimes used by universities to attract learners to move from informal to formal learning programmes, encouraging them to pay for subsequent, follow-on courses (Gillet et al, 2010). Thus, motivations to develop and openly release OER are complex and can be placed on a spectrum ranging from ‘academic commons’ to the marketization of courses (Falconer et al, 2012).

A second arena promoting the open courses were learning researchers and advocates of a pedagogical approach termed ‘connectivism’. Connectivist principles emphasise that learning occurs through network connections, as learners connect with experts, peers and with knowledge resources (Siemens, 2005). MOOCs can be viewed as an instantiation of the pedagogic approach of ‘connectivism’ (Siemens, 2005; Downes, 2009), opening up opportunities for learning as part of a learning community or group of learners (Downes, 2008). Despite these key principles, discussions around informal open learning, emphasising the learner, are sometimes conflated with formal open education, highlighting the design of activities, environments, networks, tools and resources. Some MOOC designs can mimic university courses, rather than focusing on building learner autonomy (Milligan, Littlejohn & Margaryan, 2013; Nurmohamed et al, 2013).

A third origin  is the educational activity in the academy. Universities, often operating as consortia, have provided most open courses and open educational resources. An early example is the Open CourseWare Consortium (established in 2003), a consortium of universities committed to the open release of educational resources, often from contemporary, campus-based courses (OCW, 2013) This initiative has had significant impact in terms of opening access to a broad spectrum of resources, ranging from syllabi, lecture notes and supplemental materials to video materials (Forward, 2012). For example the founding partner, the Massachusetts Institute of Technology, has released resources from 1,800 courses that have been viewed by over 100 million people (MIT, 2013). Funding organisations such as UNESCO, the Bill and Melinda Gates Foundation and the William and Flora Hewlett Foundation collectively have donated millions of dollars to the development and release of Open Educational Resources. There are numerous examples of consortia and collections of educational resource materials around the world, including OER Africa , OER Asia , Open Education Europa , Latin America Learning , DEHub Australia , Nordic OER , MERLOT and JORUM UK Some MOOC design teams attempt to capitalise upon these resource collections by packaging OERs around specific learning objectives and activities, then sequencing these activities in orchestrated, synchronous courses with regular, automated assessments. Course design may be based on equivalent campus based courses. The design teams often recognise that exposure to the course’s resource materials is not a sufficient condition for learning. However, an assumption is that learners can self-regulate their own learning, utilising learning resources with limited instructor interaction. Interest in the potential of open courses to open access to universities led to a fourth origin of MOOCs: MOOC platform providers.

A number of MOOC platforms were established during the period 2011-13, mainly in the US and UK. Some are ‘for profit’ organisations such as Udacity (https://www.udacity.com) and Coursera (https://www.coursera.org). Others are organisations operated within non-profit universities, notably edX (https://www.edx.org/). and Futurelearn (https://www.futurelearn.com/). Thus, some of the perspectives around MOOCs can be expressed as follows. Universities –particularly elite institutions – recognise the competitive advantages of MOOCs on branding, marketization and extending reach. Their response is often to open up established courses to learners globally, seeking to imitate the ‘campus experience’.

Practitioners acknowledge the potential of MOOCs, viewing them as a sustaining rather than a disruptive innovation. They habitually align MOOC development and implementation within the confines of existing higher education models. Recognise that the student experience is changed and that their own workflow models are not sustainable in MOOCs, practitioners are concerned with problems of student engagement, feedback, quality and assessment, focusing efforts on improving the quality and engagement potential of educational content. Open Access activists are concerned that the view of MOOCs as a marketisation tool for traditional university education blocks alternative, viable futures for learning and learners. As MOOCs mature as a platform for learning, there is a growing acceptance that conventional metrics (completion rates, contributions to forums) are not useful to measure the effectiveness of open learning. Metrics and models have to be reconceptualised drawing on learning analytics (McNeill et al, 2014, this volume).

Learners (largely) have enthusiastically embraced MOOCs, signing up in their thousands to participate. Many act as passive observers or ‘lurkers’ (Milligan, Littlejohn and Margaryan, 2013), raising concerns amongst practitioners and universities around completion rates. However, motivations across diverse groups of learners are broadly defined and extend beyond gaining credit (OBHE, 2013). A more pressing concern are the baseline capabilities – literacies, skills and dispositions – of learners as they learn in a new environment (Mackness, Mak, & Williams, 2010; Kop and Fourier, 2011; Milligan, Littlejohn & Margaryan, 2013). Educational and learning researchers are sceptical of this learner enthusiasm, recognising that social expectations of ‘university schooling’ constrain transformative opportunities around learning (Fiedler, this volume). In their view recognition of what constitutes learning needs to be broadened (McGill et al, 2013). Governments hold pole position in cultural definitions of learning, but few seem willing to radically redefine learning and redraw business and workflow models. All the same, governments’ view that MOOCs merit serious attention because of their potential for significant disruption and, at the same time, widening access to higher education (OBHE, p53).


#mri13 #mooc

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OER and the Vision for Adult Learning

Posted by on May 2, 2013 in Higher Education, Professional Learning, Sustainable Learning | 0 comments

On April 28th 2013 the outcomes of OER4Adults provided policy makers within the European Commission with evidence on how to incorporate the use of OER into a Vision for Adult and Lifelong Learning to 2030. This Vision was drafted with the help of a group of over 20 experts from more than 10 countries who met at IPTS in Seville to discuss, debate and advise on the Vision. Our goal was to provide the EC with evidence of existing initiatives and practices to enable them to optimise the socio economic impact of OER.


In the OER4Adults survey, we identified over 170 OER Initiatives across Europe and other countries (mainly the US). Many of these initiatives – those who provide OER for adult and lifelong learning – are from the higher education, vocational and school sectors. These initiatives assume that the primary users of OER are teachers and registered students, but the might not necessarily think about ‘nonformal’ learners.


Many examples of open learning are within open fora (eg discussion groups around health or hobby areas). These groups are seldom recognised as having an explicit remit for learning. Also they are not associated with the sorts of formal institutions that MOOCs tend to be associated with (eg think about EdX, Coursera, Futurelearn and so on).


From the OER4Adults survey we know that little is known about what lifelong learners are doing with OER resources. Even the leaders of the major OER initiatives know little about the use of the OERs outside their immediate communities. Yet this knowledge is critical to planning future directions in open education, open learning, OER and MOOC.


We carried out a SWOT analysis (analysis of Strengths, Weaknesses, Opportunities and Threats, see http://oer4adults.org/highlights-of-the-oer4adults-swot-survey/) of OER and identified a number of tensions in the following areas:

OER Resources – We recognised a tension between open versus free resources. Use of the term ‘Open’ in MOOC is blurring the distinction between what is ‘free’ and what is ‘open’. While many MOOCs are free of charge, the resources within these courses are not always ‘open’. Will mass participation push forward on this area? In other words, will the large numbers of people involved in MOOCs make it irrelevant that the resources in a MOOC are not open?

Learning – The OER4Adults SWOT survey identified a tension between conventional pedagogy (largely teacher led) versus appreciation that learners should be able to take control of their own learning. Do resources have learner intentionality? Most don’t. OER tends to be viewed as a resource with a specific learning outcome. There are examples of ‘dynamic’ resources that evolve as learners use them. However, these resources don’t readily ‘fit’ with educational technical infrastructure (eg quality policy etc). In many aspects of society organisational infrastructures are becoming rapidly outdated, thus inhibiting progress –  and this is one example. The tension between pedagogy versus appreciation is exemplified in the papers for the EC Vision for Adult and Lifelong Learning in 2030 where none of the visions view teachers as having a traditional role in the future (the papers are at http://blogs.ec.europa.eu/openeducation2030/files/2013/04/OE2030_LLL_Booklet.pdf).

Motivations for releasing OER The SWOT survey surfaced a tension between two key motivations to release OER: altruism versus marketization, where ‘altruism’ is the desire to openly share resources and ‘marketisation’ is where institutions and individuals want to build a ‘brand’. Marketisation examples include EdX, Futurelearn, Khan Academy. Its possible that organisations pitch ‘marketisation’ to governments to gain funding, but, at the same time, institutions sometimes state altruistic motivations (such as sharing knowledge freely).

A previous study by Falconer, Littlejohn, McGill  and Beetham (2012) https://oersynth.pbworks.com/w/page/63710786/Motives%20and%20tensions%20in%20the%20release%20of%20Open%20Educational%20Resources  identified that the  stated motivations to release OER may be different from the real, underlying motivations. Real and stated motivations are complex and blurred. During the workshop discussions we found examples of complex/mixed motivations.

Workshop participants agreed that the focus of the vision for lifelong learning to 2030 should be on the socio cultural impact rather than on motivations to release OER. Yet they recognised that motivations ultimately determine peoples’ actions. Much of the focus of OER release has been on ‘introductory level learning’, rather than more specialist areas, and there has been lots of duplication. How do we create resources that are ‘done’ and translated – particularly in the introductory areas (for example look at alison.com which has been translated by volunteers).

Capacity building – There is an inherent tension between ‘community’ versus ‘openness’. During the workshop we had extensive discussion about ‘communities’ and how capacity it built. ALISON provides an excellent and relatively unique model where volunteers contribute their time to translate resources for adult and lifelong learning. Community building requires engendered trust – for example within the ALISON community there is a level of trust that spending time translating resources will not be exploited.

The workshop participants noted that ‘nothing is for free’. Voluntary action is funded, though the funding is from individuals, rather than governments and organisations.

Openness – A previous study (UKOER) we identified a tension between communities (which are important for capacity building) and openness (See http://www.slideshare.net/loumcgill/openedweek2013). This tension also emerged during the OER4Adults SWOT analysis. An effective way to develop resources is within a trusted and bounded community. The effort required to translate the resources for use within another community cannot be underestimated, however we found examples (from Athabasca University) where people overestimated the amount of time required to readapt a resource for reuse (eg teachers thought they had to change every detail within a resource, rather than using resources as they exist).

Numbers of learners – Organisational controls and norms break down in circumstances of mass participation. There is a tension between mass participation versus quality. Where large numbers of people learn, it is more difficult to retain ‘control’ around quality. Recommender systems don’t always help – a ‘massive stamp of approval’ doesn’t always signal quality. Lifelong learners don’t always understand how to assess or evaluate the quality of resources and tend to rely on ‘trusting’ the source. Learners were more inclined to use resources from another “trusted organisation” than “from a university”.  This finding raises questions around current quality systems. Should we change the current validation systems or should we try to ensure that learners have better developed digital literacies so they can evaluate quality? These questions are complicated by the fact that quality shifts as we move across disciplinary and cultural boundaries.

Sustainability – Another tension was around add-on versus embedded funding models. Most of the OER initiatives we identified were funded through governments or institutions. The adult and lifelong learning community are less concerned (than Higher Education groups) that government or institutional funding may diminish. These groups are more focussed on sustainable models, including ‘freemium’ models.


Key findings and questions:

1 Many examples of open learning are not recognised as learning.

Idea 1: change public perception of what they recognise as learning.


2 To move forward with lifelong learning,  we need a fundamental shift in the way society perceives peoples’ roles (eg learners, teachers, others, etc) and organisations’ roles (eg HES, companies, publishers, etc).

Idea 2: change public perception of the roles of learners and teachers – and of organisations more broadly.


3 Within the OER arena, there is little focus on the bigger societal issues. For example the tension between the public and private sectors which have different values and norms. We don’t have a clear idea of the outcome when these values and norms come into conflict.

Idea 3: consider the longterm impact of vested interests of various stakeholders in different sectors.


4 Little is known about what lifelong learners actually do with OER. OER initiatives have little concern about this and don’t view it as significant.

Idea 4: investigate how learners use OER to learn.


5 The focus of attention could shift from open resources (OER) or open courses (MOOC) to the ability of people/learners to learn in open environments.

Idea 5: change the focus of attention from  OER or MOOC to learners

Acknowledgements: These ideas were collated as part of the validation of the OER4Adults project (on April 29 and 30, 2013) and may not reflect the views of IPTS



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Four observations on how OER initiatives are modelled

Posted by on Apr 5, 2013 in Higher Education, Professional Learning, Sustainable Learning | 2 comments

Isobel FalconerLou McGillEleni Boursinou and I  have been commissioned by the EC to carry out a SWOT analysis of Open Educational Resource initiatives for adult learning. In 2012 we carried out a scoping of adult learning initiatives using OER. We identified over 150 different initiatives distributed across Europe.

In March we invited the leaders of the initiatives to fill in a structured questionnaire. We’re in the early stages of data analysis and plan follow up interviews. Here are four observations:

European OER initiatives are based (largely) on the traditional view of instructor using OER as content for teaching

  • Most leaders of initiatives view that their content is used by teachers (school teachers, HE teachers, adult educators).
  • There is some emphasis on students or lifelong learners using content (prioritisation given to ‘prospective students’ – emphasises marketisation motivation).
  • Though –responses suggested that future emphasis should be on communities.
  • The view was that OER users were mainly ‘teachers’ – with some divided views focusing on ‘students’ or ‘projects’ as key users.

2 Most European OER initiatives rely on government or institutional funding

  • Most OER initiatives are funded by governments or institutions (universities, colleges).
  • OER leaders view ‘lack of future funding’ as having the greatest potential impact.
  • Although sustainability was marked as a significant barrier (ie potentially likely to impact negatively on the initiative) there were few examples of sustainability models that move away from core funding from government/ institution – eg examples of OER self-funded, self-generated communities or networks.
  • Where we found examples of raising funding models, these tended to be through membership fees, fees paid by contributors for a hosting service, donations, or through bespoke funding models.
  • Perhaps it is not surprising that funding, staff, policy processes were marked as significant enablers.

 3. OER is often viewed as content curated by ‘experts’

  • The main focus of many initiatives is publishing content (45.7%).
  • Initiatives prioritise the creation/management of content with some focus on discoverability and accessibility.
  • Much of the initial setup effort was setting up the infrastructure and processes.
  • Respondents found it difficult to isolate key factors that make OER useful. However the key focus areas included metadata (80%), discoverability (88.7%), good search engine (88.7%). Medium focus areas included support for the user from teachers/ community.
  • Future directions planned by initiatives focus around creating more OER, either through projects being funded to create content or through nurturing various types of communities to create and release OER.
  • Currently there is little focus on ‘soft’ areas such as skills development. Yet there is recognition that research evidence, communities, ‘ecosystem’ are important.

Significant groups of people are not being considered as key users of OER

  • People outside formal structures (eg lifelong learners) were not considered key users of OER, yet learning is critical for this group of people.
  • Another key gap we identified are manual workers. These could be deemed a critical group of workers who could benefit from upskilling, yet only one initiative are considering this group.

These initial findings raise the question – how can we ensure OER initiatives are sustainable and are not locked into models of operation that exclude potential groups of learners or emerging forms of learning?

Our data analysis is ongoing so check oer4adults.org as the story unfolds.

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