MOOCs are so unambitious: introducing the MOOPhD

Massive Open Online PhDs

During my recent visit to Curtin University, Torsten Reiners, Lincoln Wood and I started brainstorming what we think might be an interesting idea. In brief, it is to build and design what should eventually become a massive, open, online PhD program. Well, nearly. This is a work in progress, but we thought it might be worth sharing the idea to help spark other ideas, get feedback and maybe gather a few people around us who might be interested in it.
The starting point for this was thinking about ways of arranging crowd funding for PhD students, which evolved into thinking about other crowd-based/funded research support tools and systems to support that. For example, we looked at possible ways to not only crowd-fund research projects but to provide structures and tools to assist the process: forming and setting up project teams, connecting with others, providing project management support, proposal writing assistance, presenting and sharing results, helping with the process of writing reports and papers for publication, and so on. Before long, what we were designing began to look a little like a research program. And hence, the MOOPhD (or MOOD – massive open online doctorate).
A MOOPhD is a somewhat different kind of animal from a MOOC. It is much longer and much bigger, for a start – more of a program than a course. For many students it might, amongst other things, encapsulate a variety of MOOCs that would help them to gain knowledge of the research process, including a range of research methods courses and perhaps some more specific subject-related courses.  This is quite apart from the central process of supporting the conduct of original research that would form the ‘course’ itself.
A MOOPhD will also attract a very different kind of learner from those found in most MOOCs, notwithstanding the fact that, so far, a lot of MOOC-takers already have at least a first degree, not uncommonly in the same subject area as the MOOC.
Perhaps the biggest difference between a MOOPhD and a MOOC, at least of the xMOOC variety, is the inevitable lack of certainty about the path to the destination. MOOCs usually have a fairly fixed and clear trajectory, as well as moderately fixed content and coverage.  Even cMOOCs that largely lack specified resources, outcomes and assessments, have topics and timetables mapped out in advance. While the intended outcomes of a PhD are typically pretty clear (the ability to perform original and rigorous research, to write academically sound papers and reports, to design a methodology, review literature, etc), and there are commonalities in the process and landmarks along the way, the paths to reaching those goals are anything but determined. A PhD, to a far greater degree than most courses and lower level programs, specifies a method and processes, but not the content or pathways that will be taken along the way. This raises some very interesting and challenging questions about what we mean by ‘course’ and the wisdom and validity of MOOCs in general, but discussion of that can wait for another post. Suffice to say, it is a bit different from what we have seen so far.
There are many existing sites and systems that provide at least some of the tools and methods needed. I have had peripheral involvement with a support network for students investigating learning analytics, for example, and have helped to set up a site to provide resources for graduate students and their supervisors. There are commercial sites like academia.edu and ResearchGate that connect academics, including graduate students. There are some existing MOOCs on research methods and crowd-funding sites to help with fees and kick-starting projects such as http://www.rockethub.com/ or www.razoo.com.  And, of course, there is the complete system of journal and conference reviewing that provides invaluable feedback for nascent researchers. Like all technologies, what we are thinking about involves very little if anything that is radically new, but is mostly an assembly of existing pieces. 
It is likely that, for many, a PhD or other doctorate would not be the final outcome. People would pick and choose the parts that are of value, helping them to set up projects, write papers or form networks. Others might treat it as a useful resource for a more traditional doctoral learning journey.
 

So what might a MOOPhD look like? 

A MOOPhD would, of necessity, be highly modular, offering student-controlled support for all parts of the research process, from research process teaching, through initial proposals, through project management, through community support, through paper writing etc. Students would choose the parts that would be of value to them at different times. Different students would have different needs and interests, and would need different support at different points along the journey. For some, they might just need a bit of help with writing papers. For others, the need might be for gaining specific skills such as statistical analysis or learning how to do reviews.  More broadly, the role of a supervisory team in modelling practice and attitudes would be embedded throughout.
Importantly, apart from badges and certificates of ‘attendance’, a MOOPhD would not be concerned with accreditation. We would normally expect existing processes for PhDs by publication that are available at many institutions to provide the summary assessment, so the program itself would simply be preparation for that. As a result of this process, students would accrue a body of research publications that could be used as evidence of a sustained research journey, and a set of skills that would prepare them for viva voces and other more formal assessment methods. This would be good for universities as they would be able to award more PhDs without the immense resources that are normally needed, and good for students who would need to invest less money (and maybe be surrounded by a bigger learning community).
 

Some features and tools

A MOOPhD might contain (amongst other things):
  • A community of other research students, with opportunities to build and sustain networks of both peers (other students) and established researchers
  • MOOCs to help cover research methods, subject specialisms, etc
  • A great deal of scaffolding: resources to help explain the process, information about everything from ethics to citation, means and criteria to self-assess such as wizards, forms and questionnaires, guidelines for reviewing papers, etc
  • Mentors (not exactly supervisors – too tricky to deal with the numbers)  including both experienced academics and others further on in the PhD process. Mentors might provide input to a group/action learning set of students rather than to individuals, and thus allow students to observe behaviours that the academics model.
  • Exemplars – e.g. marked-up reviews of papers. This is vital as one of the ways of allowing established academics to provide role models and show what it means to be an academic
  • Plentiful resources and links relevant to the field (crowd-generated)
  • A filtering and search system to help identify people and things 
  • A means to provide peer review to others (akin to an online journal submission system)
  • A means to have one’s own ideas and papers reviewed by peers
  • Tutorial support – most likely a variant on action learning sets to support the process. This would cover the whole process from brainstorming, to literature review, to methodology design, to conduct and analysis of research, to evaluation etc. Ideally, each set would be facilitated by a professional academic or at least an experienced peer.
  • A professionally peer reviewed journal system, with experienced academic editorial committees and reviewers (who would only see papers already ranked highly in peer review), leading to publication
  • Support for gaining funding – including crowd funding – for the research, particularly with regard to projects needing resources not already available
  • Support for finding collaborators
  • Support for managing the process – both of the whole venture as well as specific projects
  • Non-academic support – counselling and advice
  • Tools and resources to find accreditors – this is not about providing qualifications but preparing students so that they can easily get them

Some issues

There are some complex and significant problems to solve before this becomes a reality, including:

Accreditation

The main idea behind this is to prepare students for a PhD by publication, not to award doctorates. It is essentially about managing a research learning process and helping students to publish results. However, sustaining motivation over a long period without the promise of accreditation might be an issue.

Access to resources

One of the biggest benefits of an institution for a PhD student is access to closed journals and libraries. While it is possible to pay for such access separately from a course, and a system would certainly contain links to ways of discovering open articles, this could be an obstacle. Of course, while we would not and could not condone the use of the community to share closed articles, it is hard to see how we could police such sharing. 

Ethics

Without an institutional backdrop, there would be no easy way to ensure ethical research. Resources could be provided, action learning sets could be used to discuss such concerns, and counselling might be available (perhaps at a price) to help ensure that a process would be followed that wouldn’t pose an obstacle to gaining accreditation, but it would be difficult to ensure an ethically sound process was followed. This is an area where different countries, regions and universities follow different procedures anyway, and there is only broad uniformity around the world, so some flexibility would be needed.

Governance

Beyond issues of ethics, there is a need to find solutions to disputes, grievances, allegations of cheating etc. This might be highly distributed and enabled through crowd-based processes. A similar issue relates to ‘approvals’ of research projects: there would probably need to be something akin to the typical review processes that determine whether a student’s progress and/or proposed path are sufficient. It is likely that action learning sets could play a big role in assisting this process.

Subject specificity

The skills (and resources) needed for different types of PhD can vary enormously – the skills and resources needed by a mathematician are worlds away from those needed by someone engaged in literary criticism, which are worlds away from those needed by a physicist, astronomer or biologist. It would probably be too big a task to cater for all, and some might be all but impossible (e.g. if they require access to large hadron colliders or telescopes, or are performing dangerous, large scale or simply complex experiments). To some extent this is not the huge problem it first appears to be. It is likely that most of those interested in pursuing this process would already be either working in a relevant field (and thus have resources to call upon) or already be enrolled in an academic program, which would reduce some of the problem, but the chances are that the most likely areas where this process could successfully be applied would be those requiring few resources beyond a good brain, commitment and a computer. There are opportunities for multiple instances of this process across multiple subject areas and disciplines. Given our interests and constraints, we would probably aim in the first instance for people interested in education, technology, business, or some combination of these. However, there is scope for a much broader diversity of systems, probably linked in some ways to gain the benefits of common shared resources and a larger community.

Cold start

As the point of this is to leverage the crowd, it will be of little value if there is not already a crowd involved. The availability of high-quality resources, links and MOOCs might be sufficient to provide an initial boost to draw people to the system, as would a team of interesting mentors and participants, but it would still take a while to pick up steam.

Trust

In some fields, students are already reluctant to share information about their research, so this might be especially tricky in an open PhD process. Building sufficient trust in action learning sets and across the broader community may be problematic. Already, the openness needed for many MOOCs poses a challenge for some, but this process would require more disclosure an an ongoing basis than normal. This might be the price to be paid for an otherwise free program. However, the anticipated high drop-out rate would make it difficult to sustain tight-knit research groups/action learning sets over a prolonged period, and we would probably need to think more about cooperative than collaborative processes, so this may be difficult to manage. 

Start-up costs and maintenance

This will not be a cheap system to build, though development might be staggered. Resources would be needed for building and maintaining the server(s), creating content, managing the editing process for the journal, and so on. Potential funding models include start-up grants, company sponsorship (the value to organizations of a process like this could be immense), crowd-funding, subscription, advertising/marketing, etc. Selling lists of participants bothers me, ethically, but a voluntary entry onto a register that might be passed on to interested companies for a fee might have high value. While we might not award doctorates, those who could stay the course would clearly be very desirable potential employees or research team members.

Encouraging academics to participate

Altruism and social capital can sustain a relatively brief open course, but this kind of process would (unless a different approach can be discovered) require long term commitment and engagement by professional academics. There may be ways to provide value to academics beyond the pleasure of contributing and learning from students. For instance, students may be expected/required to cite academics as co-authors where those academics have had some input into the process, whether in feedback along the way or in reviewing/completing papers they have written, or may be granted access to data collected by students. This would provide some incentive to academics to help ensure the quality of the research, and help students by seeing an experienced academic’s thinking processes in action.

Summary

This is a work in progress and there are some big obstacles in the way of making it a reality. We would welcome any ideas, suggestions or expressions of interest!