Beyond MOOCs: Sustainable Online Learning in Institutions.

Below is the executive summary from our Cetis paper Beyond MOOCs: Sustainable Online Learning in Institutions, looking at the benefits that institutions might gain from  the recent MOOC mania.  I think the section on business models has the most to offer to institutions, but this was also the hardest part to explain in a way that would be helpful to Institutions.

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1.    Executive Summary

The key opportunity for institutions is to take the concepts developed by the MOOC experiment to date and use them to improve the quality of their face-to-face and online provision, and to open up access to higher education. Most importantly, the understanding gained should be used to inform diversification strategies including the development of new business models and pedagogic approaches that take full advantage of digital technologies.

The critical discourse emerging around MOOCs is providing an opportunity for institutions to develop a more strategic approach to online learning.  This includes enhancing existing classroom teaching practices, promoting institutional reputation and developing new revenue models. There are indications that some MOOCs are becoming more focussed on corporate training, which suggests that they may not pose a immediate threat to the existing pedagogical, revenue or business models of higher education institutions (HEIs). The number of Massive Open Online Courses (MOOCs) will continue to grow with the development of credit bearing courses likely to be a trend.

The findings from this report are summarised in three sections: key themes that have emerged from the MOOC experiment, opportunities that institutions should consider exploring, and longer-term strategic considerations and likelihood that this will happen for institutions.

Three key themes emerge from the MOOC experiment:

  1. Openness – new approaches to online learning, including models for scalable provision that may generate revenues, and promote open learning, which goes beyond institutional boundaries through the use of online communities. [Increasing impact & long term, likely for most institutions]
  2.  Revenue models – different revenue models taking the established ideas from technology start-ups, such as applying the concepts of freemium and premium offers into online learning, providing institutions with new ways of thinking about marketing and income generation. [High impact & medium term, more likely for institutions looking for new revenue streams]
  3. Service Disaggregation – experimentation with business models that include unbundling and re-bundling of courses and delivery related services, such as offering paid for assessment and/or teaching and support, on top of free online course content. This may have a wider impact across institutions in the future through better deployment of existing resources to add value to customers where there is greatest benefit and to reduce costs through outsourcing (unbundling is already happening independently of MOOCs). [High impact & short term, likely for most institutions]

Institutions should consider exploring a set of opportunities that have been brought to the attention of mainstream education by MOOCs, and experiment with new approaches for developing technology-enabled changes in teaching and learning to improve opportunities for individual learners. These include:

  1. Technology options – new platforms and services with different functions, terms and conditions for experimenting with the development of MOOCs and open online provision in institutions, including opening up an existing VLE, partnering with a commercial MOOC platform; or using an ad hoc collection of tools and services that are suitable for innovative experimentation. [Low impact & short term, likely for most institutions]
  2. Pedagogic opportunities – for educators to experiment and evaluate different online learning approaches by developing and using MOOCs that challenge the established roles of learner and teacher and offer more flexible forms of learning and assessment that include community as well as content-based models of learning. For some, experimentation will be at the level of the individual lecturer and for others it may be departmental or large-scale cross-institutional change projects. [Medium impact & medium term, likely for some types of institutions]
  3. Learner choices – developing new and affordable ways for learners to access courses and materials with the possibility of study for credits that are affordable and flexible. A starting point that is not based on existing courses can be a less constraining way of exploring new approaches. [High impact & short term, likely for some institutions]

Institutions are operating in an environment of increased marketisation and global competition, increasing student demand, reduced central government funding and affordability issues for students.  Institutions will have to make strategic choices about how they respond to the changing contexts in which they operate; depending on the starting point these will have short, medium and long-term implications:

  1. Mission, purpose and values - taking full account of the significant wider changes in HEIs’ business environments that may require institutions to review how they interpret their mission, purpose and values when developing their strategic response. [Variable impact & long term, likely for most institutions]
  2. Strategic directions  - using the new opportunities presented by rethinking MOOCs as a useful motivation for institutions to examine their current provision and think about ways in which they can change and diversify. However, failure to recognise the scale of this challenge may well derail any new strategic directions. For institutions with little experience of open and online provision, options for rapid development may be limited to forming partnerships with external organisations with the required capabilities. [High impact & long term, likely for most institutions]
  3. Capability building requirements - reviewing existing in-house capabilities including: technical infrastructure, academic and support staff working practices. If starting from a low base, these will require significant commitment to change and develop, in order to support new business models for online provision. [Variable impact & short term, likely for most institutions]
  4. Business model components – there is an opportunity for institutions to examine their current provision and think about ways in which they can change and diversify to develop new sustainable business models for open online provision that take as their starting point the needs of the learner rather than the interests of the institution. [High impact & medium term, likely for some institutions]

Small is beautiful: an antidote to Big Data (altc2013)

The above titled presentation was given at the recent altc2013 conference in Nottingham. It was based on work undertaken by the jisc cetis service in the production of the Cetis Analytics Series in 2012/13.  In addition, towards the end of the 2012-13 academic year we undertook a Survey of the State of Analytics in UK Higher and Further Education Institutions 2013.

Some reflections based on the comments by session participants:

  • there is significant interest around undertaking small scale analytics projects, that is ones that don’t depend on high level management support or significant amounts of resource
  • there is concern around the purpose to which analytics might be used, with a risk that crude interpretations made by administrators and managers may result in harm being done
  • the biggest barrier to making initial progress is modelling an institutions data: what data is collected; where is it held; and how can it be accessed
  • there are only the beginnings of an understanding of what benefits analytics might bring for learners better understnding out their own learning and the better organisation of institutions

MOOCs and Open Education: Implications for Higher Education (March 2013)

Below is the executive summary of this Cetis publication I wrote with Dr Li Yuan. Our best effort at summaring the phenomena that is MOOCs.

The focus of the report
This report sets out to help decision makers in higher education institutions gain a better understanding of the phenomenon of Massive Online Open Courses (MOOCs) and trends towards greater openness in higher education and to think about the implications for their institutions. The phenomena of MOOCs are described, placing them in the wider context of open education, online learning and the changes that are currently taking place in higher education at a time of globalisation of education and constrained budgets. The report is written from a UK higher education perspective, but is largely informed by the developments in MOOCs from the USA and Canada. A literature review was undertaken focussing on the extensive reporting of MOOCs through blogs, press releases as well as openly available reports. This identified current debates about new course provision, the impact of changes in funding and the implications for greater openness in higher education. The theory of disruptive innovation is used to help form the questions of policy and strategy that higher education institutions need to address.

Making sense of MOOCs
MOOCs are a relatively recent online learning phenomenon, having developed from the first early examples five years ago, they are now generating considerable media attention and significant interest from higher education institutions and venture capitalists that see a business opportunity to be exploited. They can be seen as an extension of existing online learning approaches, in terms of open access to courses and scalability, they also offer an opportunity to think afresh about new business models that include elements of open education. This includes the ability to disaggregate teaching from assessment and accreditation for differential pricing and pursuit of marketing activities.

Analysis of MOOC initiatives
The opportunity that MOOCs offer for massification of courses has generated significant interest from governments, institutions and commercial organisations. A number of bespoke MOOC platforms have been developed and offer courses independent of or in collaboration with universities. A growing number of institutions have been involved in engaging and experimenting with MOOCs for the purpose of expanding access, marketing and branding, as well as the potential of developing new revenue streams. Motivations for learners to participate in MOOCs are varied, and many struggle to engage with courses and keep motivated in the context of an online learning environment. The market value of certification of courses, short of credit as part of traditional institutional awards, has yet to be determined. Other potential business models are being developed but need further work to establish them.

Issues and Challenges for MOOCs
Over recent years there has been a significant change in societal adoption of Internet technologies with extensive proliferation and use in more economically developed countries. However, in terms of the proliferation of MOOCs as an educational approach, there is a risk that the current enthusiasm is being driven by a self selecting group of highly educated, IT literate individuals who are able to navigate the sometimes complex, confusing and intimidating nature of online learning. In general, there are concerns about the pedagogy and quality of current MOOC courses, with a clear distinction between process and content-based approaches. The motivation for some MOOCs is a philanthropic one and for others a business proposition. However, in both cases, there is the challenge of finding a viable model that allows for sustainability of MOOC provision.

MOOCs as disruptive innovations
The theory of disruptive innovation (Bower and Christensen, 1995) offers an explanation as to why some innovations disrupt existing markets at the expense of incumbent players. In this case, there is a significant question for higher education institutions to address: are online teaching innovations, such as MOOCs, heralding a change in the business landscape that poses a threat to their existing models of provision of degree courses? This possibility is brought about through the combination of wider societal adoption of communication and, particularly, Internet technologies, changing funding models and the development of new business models that leverage this opportunity. If this is the case, then the theory of disruptive innovation suggests that there is a strong argument for establishing an autonomous business unit in order to make an appropriate response to these potentially disruptive innovations.

Implications for higher education
The current UK political administration has continued the course set by the government with an even more radical agenda to allow new, for-profit providers to enter the higher education market. These include, changes to funding whereby students pay most of their tuition fees, through student loans, and changes to national quality assurance measures so that new players can enter the market place and offer new, differentiated provision including more for-profit universities. There is also an opportunity here for open education where less traditional lecturing and more facilitative and guided approaches to education can find a place in this new landscape of online learning where increased fees for established models may act as a deterrent to students.

Explaining Educational Data Analytics to Colleagues

For the purpose of the IEC Analytics Reconnoiter project I have been trying out ways of explaining the domain in ways that are readily understood by non-technical colleagues new to the ideas and staying clear of the different technical solutions that might need to be deployed. A key distinction here is that Educational Data Analytics takes a wider view than Learning Analytics using data about the the University as an enterprise.

The diagram below is based on two key dimensions that stand out for me based on readings, namely the time of use from collection dimension and a control and authority dimension (reminiscent to me of the Edinburgh Scenarios, Jonathan Star 2004). I think that a key point is to get across the potential in the top right hand quadrant and what it might mean for understanding the University as an enterprise (Educational Data Analytics ) beyond learning analytics and data mining that focus on pedagogical, learning and teaching aspects.

In addition, presenting the ideas as analytics for whom and for what purpose also appears useful:
learners: self reflection, cohort comparisons, automated learning, etc.
• teachers: retention, progression, student satisfaction/experience, etc.
• course developers: design for success – assessment, content, teaching strategies, etc.
• administrators: retention, progression, efficiencies, balancing HEFCE control numbers internally, etc.
• researchers: pedagogy, models, theory, etc.

On a more theoretical level the Viable System Model has potential application to better understand the central concept of feedback loops and how the different components of the systems in view interplay with each other and their external environments. For example, seeing that measures intended to address issues such as retention are inextricably wound up in the students wider environment where factors such as the need to work to fund studies may come into conflict with approaches like giving more contact time in the belief it will help students be successful. More work need on modeling this, but:

• real time feedback loop for learners & teachers – learning and retention are here and now issues;
• medium term for learners, administrators & teachers – universities plan, allocate resources & undertake quality processes in annual cycles. Progression is a medium term concern of academics and learners;
• long term for researchers & courses developers – the concern of theses groups tend to be more about aggregations of experience over a number of iterations.

An untidy thread that is niggling me and perhaps just needs more reading around is where Management Information Systems fit in all of this – they have been around for a very long time now and seem to occupy most of the Educational Data Analytics domain.

Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics (observations)

I found the “Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics” (Draft report US Department of Education, 2012) publication an interesting explanation and introduction to ‘educational data mining’ and ‘learning analytics’.

My simple interpretation, is that Data Mining advocates seek to automate learning through extensive analysis of previous learners behaviours captured in learning systems. Whereas advocates of Learning analytics emphasise not prediction but on providing information (often visual) to inform stakeholders for decision-making purposes.

This report seeks to combine these two traditions in the concept of an ‘adaptive learning system’, the model below being self explanatory and at first glance convincing, but I think too tidy in practical terms.

Three deficiencies that stand out for me are:
1. the limited view of learning as shown by the exposure of a ‘Student’ to ‘Content’ as generating ‘student learning data’ – learning as process?
2. the narrow distinction of the learning system – courses (instructional) designers (not the same as administrators or teachers) and the curriculum as expressed by learning outcomes/aims, professional body requirements, etc. which are a significant part of the system;
3. and the fact that online courses seem to be the focus – there are lots of data to be analysed on f2f courses.

I think that the letter point is a more general observation of work on learning analytics.

As someone new to this domain of knowledge, two organisations appear to represent the different traditions, see the Society for Educational Data Mining and the Society for Learning Analytics Research – SoLAR. In a previous post, I conflated both of these under the Analytics badge, but now see more clearly a difference.

Generic ‘canvas generator’ tool for Archi!

As part of our work on the JISC funded Coeducate Project, Phil Beauvoir has developed a ‘blank canvas’ feature as an addition to the Archi modelling tool that offers open source software for Archimate modelling.

A significant generic application of the canvas tool ( fully editable and lockable / un-lockable making them very powerful and flexible) is in support of face-to-face workshops. On creation, a new ‘canvas’ can also be exported as a .png or .jpeg, enabling it to be printed out on large A0 sheets. These can then be provided for workshops participants to use with post-its in the normal way. However, a rapporteur can additionally use the tool to capture the post-its as they are created, thus providing a record that can be shared, built on in future, &/or handled by other applications.

Our motivation for developing the tool was our use of the Business Model Canvas (BMC) which as its name suggests is designed to support thinking around business models, something that we are not particularly good at when we develop new degree programmes in the UK Higher Education sector.

Rather than simply building a ‘hard wired’ representation of the BMC into Archi, we hope that we have added new dimension for people who wish to try and tie together different approaches and techniques with the practice of Enterprise Architecture using Archimate modelling language. An important point, is that this isn’t just a visual representation, but the tool (built in Eclipse) captures relationships between objects with associated name-value properties so that more can be done with the data in an automated way.

We think this is a cool bit of work and expect to see the commercial vendors like BizzDesign following suit:^) Phil’s work will ship with the next release of Archi in early December 2011.

An early example of the tool in use…

Cybernetics for clean toilets

Cybernetic explanations are based on a systems analytical approach and are concerned with feedback loops between a system and its environment. The Viable System Model developed by Stafford Beer had at its heart the notion of real time feedback loops that would enable an operation to make corrections to match the requirement of its environment.

Traveling to New Zealand, I came across these cybernetic devices at Singapore Chang Airport which I haven’t seen or noticed before. You can rate the service of the particular toilet attendant by selecting the appropriate button (hard to see but excellent on the left, poor on the right) so that he (and presumably his managers) have pretty much real time information on his performance.

These things are everywhere in the airport and it would be good to speak to the designer/s behind the system to find out what the thought process and inspiration was!