A manifesto for online teaching, 2016 – good, bad and sometimes a bit daft.

As I have said in previous posts, I am convinced that the most pressing educational challenge for the 21st century is to develop effective and efficient ways of adult continuous education. Without these, we will consign an increasing number of our citizens to the ‘digital scrapheap’ as they are replaced by ever-more powerful digital technologies.

To provide this type of education, I see no alternative to using digital learning technologies to provide the educational experience that people need. Face to face delivery simply does not scale to this challenge.

UK Universities have, disgracefully in my view, largely disassociated themselves from both the delivery of adult continuous education and research in this topic. There are, of course, obvious exceptions to this such as the OU, but in general the ‘market-driven’ approach to higher education has driven universities to focus almost exclusively on full-time education for people under 25.

There seems very little research in the general area of adult continuous education so we have to turn to more general research on digital education to try and get some clues how to tackle this problem. A research team that is active in this area is the digital education group at Edinburgh University. They have been researching digital education issues for a number of years and have recently updated their ‘manifesto for online teaching’, which was first proposed in 2011.

Manifestos, by their nature, have to be quite generic (OK, waffly) but I think this is (or could be) a useful document that provides a framework for people working in this area to reflect on what they are doing and plan to do.

However, as I suggest in the title of this post, what has been produced is a bit of a mixed bag. Some statements get it absolutely right, some are, in my experience, quite wrong and some are really just a bit daft.

I won’t go through this manifesto statement by statement but will pick out some examples of the good, the bad and the bonkers.

“There are many ways to get it right online. ‘Best practice’ neglects context.”

This is spot-on and really important. When we are dealing with heterogeneous groups of learners, I don’t think ‘best practice’ makes much sense. Even less so when this ‘best practice’ is derived from work with children and young adults and we try and apply it in an adult learning context. However, I would add ‘and culture’ to this statement.

“Aesthetics matter: interface design shapes learning.”

This is so important and so hard to do. Sadly, the designers of the digital learning systems that I have seen for higher education don’t seem to understand this. Unfortunately, good interface design is very expensive and time consuming and clashes somewhat with agile, iterative systems development that has become the norm for this type of software.

“Contact works in multiple ways. Face-time is over-valued.”

I have no idea what the first clause here means but I think that the second is absolute nonsense. Face time is certainly NOT over-valued although it might be argued that ‘face time’ spent delivering material is of dubious value. But when students have understanding problems, simply talking face to face and understanding their concerns beats all digital interactions. Of course, it doesn’t scale – but that’s not the same thing.

“A routine of plagiarism detection structures-in distrust.”

This is wrong and, in fact, using plagiarism detection promotes trust in the fairness of assessment (I taught courses with plagiarism detection for more than 10 years). The vast majority of students do not plagiarise and resent their peers who do and are rewarded for doing so. Plagiarism detection reassures this larger group that there is a level playing field for everyone. I don’t recall any student ever complaining about plagiarism detection, even those who it detected.

“ Algorithms and analytics re-code education: pay attention!”

This strikes me as complete gibberish – I don’t know of any educational practitioner – teacher or university lecturer – who would have the faintest idea of what this means?

“Automation need not impoverish education: we welcome our new robot colleagues.”

I don’t know if the author here has swallowed some of the more ludicrous statements about AI but really, were are a very long way from having robot colleagues in the sense that I understand the word ‘colleagues’. Automated systems can make some data-driven decisions but they can’t understand the concepts of policy, culture, empathy, tolerance and politics that are an inherent part of both working with colleagues and involving them in learning processes.

In themselves, these odd statements are not that harmful. However, the danger with including such statements is that educational practitioners who read this manifesto will simply dismiss this as the eccentric ramblings of academics who are divorced from the real world of learning. This would be a pity as digital education can only succeed if we bring together (sceptical) practitioners and researchers at all levels.

I have been thinking for some years about how we can use digital learning effectively for adult learners, specifically on how to learn computer programming. This manifesto, in spite of its flaws, was helpful as it articulated some of the issues that I have struggled with. I don’t have any answers here but when I finally get round to creating something, I will turn to it as a checklist to help me assess how I’m getting on.

2 thoughts on “A manifesto for online teaching, 2016 – good, bad and sometimes a bit daft.

  • August 16, 2016 at 1:49 pm

    hi Ian, thanks a lot for your really interesting response to the manifesto! It’s great to hear different perspectives and interpretations of the points – your experience of plagiarism detection as promoting trust, for example. I wanted to offer a follow up to the automation and algorithm statements – the coding/learning book from the Code Acts in Education ESRC seminar series says more about what we were getting at in our reference to ‘recoding’ learning, the influence of algorithms, and so on. In that collection is a piece by my manifesto co-author, Sian Bayne, about the ‘teacherbot’ project that prompted our (deliberately playful) point about robot colleagues. https://codeactsineducation.wordpress.com/codinglearning-e-book/

    I think it’s worth pointing out (as we do in the manifesto itself) that everyone involved in authoring this manifesto is both a researcher AND an experienced online teacher (and often a learner, too), and we’ve successfully used the manifesto as a discussion prompt in a lot of different contexts, including with groups of teachers, students, learning technologists and researchers. There is lots of scope for debate about the statements, but we haven’t found disagreements to be based on any particular division between researchers and practitioners. So I’m not convinced that’s a relevant distinction here.

    Thanks again for your perspectives on the manifesto. If you don’t mind, we will link to this post from the site?

  • August 22, 2016 at 1:54 pm

    Hi Ian,

    Thanks for giving us your analysis of Edinburgh University’s manifesto for online learning. This is an area I have an interest in (I’m working as a software developer in a UK university that is currently looking at expanding their online presence, and I’m also about to start an online course at another UK university). I’ve been generally impressed by Edinburgh University’s work in digital learning (they’ve featured heavily in recent JISC podcasts on learning analytics). They appear to be further ahead of most UK universities at dealing with the issues associated with delivering online learning.

    I would certainly agree that online learning will never be able to completely replace face-to-face teaching. The best courses will be hybrid courses, with material delivered online, but having elements of in-person teaching (similar to many current OU courses). Face time is essential to be able to address individual students’ issues and questions. But as you say, it is not scalable and is also expensive, so is not palatable to many UK universities who are too focused on the bottom line, and not enough on delivering quality learning.

    I suspect that the phrase “Algorithms and analytics re-code education: pay attention!” is referring to the possibility that the algorithms used in learning analytics to detect issues with a student’s progression in a course may reflect implicit biases and assumptions from the course administrators. Not all learners will learn in the same way, or have the same progression through a course. But the analytics algorithm may penalise those who don’t progress in the same way as the majority of learners, or indeed may be gamed by the learner. This JISC podcast, featuring contributors from Edinburgh University & the OU, may be of interest:



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