E-Learning 3.0 : Graph

Graph is the Topic for Week 3 of Stephen Downes’ E-Learning 3.0 MOOC. Again, he has provided a good Synopsis – see https://el30.mooc.ca/cgi-bin/page.cgi?module=7. In the last three paragraphs in this synopsis he writes:

In connectivism we have explored the idea of thinking of knowledge as a graph, and of learning as the growth and manipulation of a graph. It helps learners understand that each idea connects to another, and it’s not the individual idea that’s important, but rather how the entire graph grows and develops.

It helps us see how a graph – and hence, knowledge – is not merely a representational system, but is rather a perceptual system, where the graph is not merely the repository, but a growing and dynamic entity shaped by – and shaping – the environment around itself.

Graphs and graph theory demonstrate in a concrete way how everything depends on something else, and helps us place our understanding of ourselves, or knowledge, and our work into a wider context. Hash graphs take this a step further by illustrating fundamental knowledge-creation mechanisms as cloning, forking, versioning and merging.

The task for this week requires creating a graph.


I am not very familiar with graph theory. I know some of the language – vertices and edges – and I have seen graphs, but have not known until now that they are called graphs, e.g. I am familiar with the work of Aras Bozkurt @arasbozkurt.  See for example the dynamic graph he has created of Twitter activity on this course – https://twitter.com/arasbozkurt/status/1059543856394485760  That’s the limit of what I know about them, because, to be honest, graphs do not ‘light my fire’!

However, I have completed the task, at a novice’s level, so no need to read on unless you too are a novice, in which case you might be interested. I now know a bit more, and made some interesting discoveries, the most important one being that the graph is only as reliable/trustworthy as the data that is put in.

I will respond to each of the three parts of the task in turn.

  1. Create a model graph of some aspect of the E-Learning 3.0 course (it doesn’t have to be an actual graph, only a representation of what an actual graph might look like. We’ve already seen, eg., graphs on the relations between people in the course. Could there be other types of graphs?

This is my graph – hand drawn, which takes longer, but was good for making me think.

Before drawing this I first read the reading recommended in the newsletter – A Gentle Introduction to Graph Theory and watched a video that I found on YouTube – Graph Theory – An Introduction.

As yet I have only skimmed the other references in the reading list, but have copied them at the end of this post for future reference.

Below, I will describe the tortured way I went about this task.

I was interested in blog posts, the number of posts each participant (who has submitted their blog feed) has made and the number of comments they have received.

I went to my Feedly RSS reader where I have 20 blog posts in my EL30 category and went through all the blog posts relating to EL30, noting down the name of the blog, the name of the author, the number of posts made, and whether each post had received a comment or not, at the same time identifying who the comment was from. I then labelled each blog from V1 to V20. Having done this I was able to pull out all the blogs that have received comments, and identify in terms of V1 – V20, who these comments were from.

At this point I made a number of observations:

  • This graph will not represent the activity on the course, because a number of participants have made posts but not received any comments
  • I decided to only include comments from people in the EL30 course, whereas participants who already have an established network and blog, have received comments from people not participating in the course.
  • I had to decide whether an invited speaker counts as a course participant for this activity. I decided No.
  • I had to decide whether Stephen counts as a participant. I decided Yes.
  • For simplicity’s sake I did not record the number of times someone commented on a single post. I counted them all as one comment. My main objective was to see who was commenting on which blogs.

Later I skim read this article – https://medium.freecodecamp.org/i-dont-understand-graph-theory-1c96572a1401 and now think that some of these decisions were wrong, e.g. all participants should be in the graph even if they have not posted, or commented, on a blog.

  1. In your model, consider how the states of the entities in that graph might vary. Consider not only how nodes might vary (eg., a person might have a different height over time) but also how the edges might vary (eg., a person might have a different strength of relation (calculated how?) with another person over time).

At first, I interpreted this as how nodes might vary from each other and noted:

  • This might be a first-time blogger or a newly created blog
  • The participant might lack the confidence to comment on other blogs
  • The participant might be an introvert
  • The participant might have joined the course late
  • The participant might be a very experienced blogger
  • The participant might already have expertise in the topic
  • The participant might already be recognised as having expertise in the topic.
  • The participant might have more social power

But on second reading I realised that the question was about how individual nodes might vary over time. Presumably the significance of this is to show that the graph is dynamic rather than static. Of course, the graph I have drawn does not show this. It is static. I would have to draw a series of graphs over time to show it changing. This would then show that each node might vary over time by, for example, changing blogging practice, i.e. writing more or less posts thus increasing or decreasing the likelihood of receiving comments, commenting on other posts more or less (is this a function of the node or of the edge??), creating more than one blog, deleting a blog.

At this point I realised that it is easier to think of each node as a blog rather than as a participant, so the blog might become more or less active, over time, more or less connected over time.

How might the edges vary:

  • They can be bidirectional or unidirectional
  • They might represent a changing number of comments
  • New connections might form over time
  • Connections might break down over time
  1. In your model, consider how knowledge about the changes in states in the graph might be used.

At any one time the graph will show:

  • which nodes are interacting, and which are not
  • which nodes are commenting on other blogs and which are not
  • which are the most active nodes and which the least active
  • which nodes post comments but don’t receive them
  • which nodes receive comments but don’t post them

To get more out of this it would be necessary to:

  • include all participants, even those who at the time of creating this graph are not posting or commenting
  • consider how to represent a chain of interactions between the same people, i.e. a comment on a comment
  • consider whether to include comments from non-course participants

Obviously all this becomes more obvious and easier with a graph that is automatically updated and changes in front of your eyes.

An outstanding question I have is about the limits you put around a graph. For this graph I only looked at blogs and comments tagged #el30. But supposing there was suddenly no activity from any #el30 participant because they had all moved into new blogs and were now interacting with a different set of connections. How would we know that from this graph?

I’m not at all sure that I’ve completed this task correctly. Given that this is a public post, it would be good if any errors were pointed out so that others can see them.

Resources provided by Stephen Downes

A Gentle Introduction To Graph Theory
Vaidehi JoshiBaseCS, 2018/11/05

This is a gentle introduction to graph theory. Graphs are data structures in which entities – called ‘nodes’ – are connected to other entities via some sort of a link – called an ‘edge’. In graph theory there are no limits on what can be connected, nor how they can be connected. Defining graphs in specific ways, however, creates the structures that underlie most of the modern web.

The Neural Network Zoo
Fjodor van Veen, 2018/11/05

Neural Networks are types of graphs. In the past I have stated that in order to be a network, a change of state in one entity in a graph must be capable of producing a change of state in another entity. Neural networks are therefore dynamic and interactive graphs. This resource describes a bunch of different neural networks. Different neural networks have different capabilities, and today are playing an increasingly important role in artificial intelligence.

Types of Machine Learning Algorithms in One Picture
Vishakha JhaTechLeer, 2018/11/05

The diagram in this resource describes some different types of neural networks. Take a look at the specific tasks they perform – neural networks are good at things like classification and recognition, as well as regression (that is, finding a trend or regularity in data). I got this image from this page, which has more resources on neural networks. Web:

Graph Data Structure And Algorithms GeeksforGeeks, 2018/11/05

Graphs are important types of data structures. Instead of thinking of things in rows and columns (the way we would in a spreadsheet or a database) we think of things as nodes and edges. This page has a very brief description of a graph data structure and then a long list of things that can be done with graphs – cycling, sorting, spanning, searching. This page is meant to explore, not to learn – follow the links, try running some of the code (click on the r’run in IDE button’).

What college students should learn about Git
Christopher JefferyMedium, 2018/11/05

You may have heard of GitHub – the open source software repository that was recently acquired by Microsoft for $7.5 billion. GitHub is important because it allows authors to release related versions of their software, to incorporate and merge contributions from many authors, and to allow people to create their own version (or ‘fork’) any application. To do this, GitHub is structured as a Directed Acyclic Graph, creating a series of relationships among code libraries.

What is uniquely human?

In this first week of the E-Learning 3.0 MOOC, Stephen Downes has shared a video introduction to the course (see https://el30.mooc.ca/course_activity_centre.htm ) and also recorded a video of a conversation he had with George Siemens. This was really enjoyable to watch.

It has been ten years since Stephen and George offered the first ever MOOC on connectivism, which for me (without wanting to sound too dramatic) was a life-changing experience. On the back of that course I established myself as an independent education consultant and researcher, which ultimately led to a PhD by publication. More important than this was that it led to connections with people with whom I am still in contact and who are now personal friends. As George said, that first MOOC, CCK08, The Connectivism and Connective Knowledge Course came at a time of mass explosion of technology, extensive innovation and the emergence of shared intelligence. But, as George said, after this initial excitement, the last five years has felt a bit like a wilderness and many of the initial aspirations for a democratic open web have not been realised.

However, neither George nor Stephen has given up on their initial aspirations to democratise learning. Both think we are now entering an era of deepening understanding of learning. Each has approached this differently, although they both feel that connectivism continues to be relevant, if not even more relevant, to how we learn in a technological age, as technology becomes more prominent.

Stephen asked George to tell us what is his current work focus. What are the issues that concern him? This was where the discussion became fascinating. It centred around what it means to be human and what is human intelligence in a world where machines can learn just as we do. For Stephen there isn’t anything that is uniquely human. Anything organised in the right way can learn. If we can learn, machines can too; if we can come up with ethics so can computers. Computers can always learn more than we can. Unlike us, they don’t get tired and improve with more data. Machines are equally as smart as us. So, George asked, why are we teaching in a counter-intuitive way when systems/machines can do it so much more efficiently and in 50 years time we will all be working with robots?

Grappling with these questions, George is looking for what is uniquely human. He sees this as ‘being-ness’. I have heard him talk about this before to Neil Selwyn, and earlier this year wrote a blog post about their discussion  – Skills for ‘Being’ in a Digital Age . Stephen thinks ‘being’ is too fuzzy a concept to be useful, although ‘being’ seems to have exercised the minds of many a past philosopher, not least Heidegger. Despite this, I think Stephen nailed it when he said, ‘the most consequential things can’t be measured’. Perhaps, as Stephen suggested, ‘being’ can be recognised (without being measured, defined or articulated) in such qualities as ‘goodness’. We can probably think of similar qualities that it is hard to imagine a machine learning. George suggested that to understand ‘being’ we might need to return to traditional contemplative practices.

My current thinking is that ‘being’ is one of those ideas that cannot be made explicit without losing its meaning. It is something that we ‘know’, intuitively and empathically, without having to articulate it, and this knowledge is unique to each and every one of us. It is this that makes us different from machines.

This was a great discussion to have at the start of the course.

E-Learning 3.0 : some initial thoughts

This is the topic of a 10-week MOOC being offered by Stephen Downes, which started this week. For the course outline see – https://el30.mooc.ca/course_outline.htm . Stephen said somewhere that he was trying to create an elegant site for the course. I think he has succeeded. I love this simple image and title.

On this site Stephen writes:

The premise of this course is that we are entering the third major phase of the world wide web, and that it will redefine online learning as it has previously. The first phase of the internet as it was originally developed in 1994, based on the client-server model, and focused on pages and files. The second phase, popularly called Web 2.0, created a web based on data and interoperability between platforms. In what is now being called web3, the central role played by platforms is diminished in favour of direct interactions between peers, that is, a distributed web.

I missed the beginning of the course (I’m not even sure which day it did begin), being away on holiday in the Trossachs, Scotland, where ironically it was very difficult to get an internet connection and was impossible to stream anything. Whilst we might assume that everyone everywhere is connected all the time, my experience this week suggests otherwise. Nevertheless, given the influence of Web 2.0 on what we understand by ‘truth’ and how to live ethically in this post-truth world, it seems important to me to ensure that we at least have an inkling of the developments which will lead to Web 3.0.

I am now back from the beautiful wilds of Scotland and connected again and have watched Stephen’s video introduction to the course, in which he provides an excellent overview of what the course will cover.

He told us that the course would be structured around the outline depicted in the figure below and then talked briefly about each element of the diagram.

The basic premise is that because we are moving from a world of documents to a world of distributed dynamic data, Web 3.0 will be based on a linked open data cloud. This means that the approach to learning will change. It will no long depend on remembering, but instead on pattern recognition. In this model, knowledge is pattern recognition.

So far, so good. Stephen then went on to discuss the significance of the Cloud and Graph elements of his diagram. Here he lost me. He told us that anyone could learn this if we put the effort in and that through this we would learn how to create new types of distributed and connected learning resources. I found myself thinking that I have always like driving; I know how to change a wheel, and when opening the bonnet where to top up the screen wash and oil. I can even jump start another car if necessary, but beyond this I am not interested. I take the car to the garage and let someone else with years of experience sort it out. Similarly with technology. I am simply not sufficiently interested to get into the nitty gritty. I am not interested in learning how to programme or learning different computer languages. I think there will probably be more people like me than technical experts (although maybe not on this course!), so I wonder what the implications of this are for a distributed model. Further, I like the fact that I can come to this course and know that Stephen has the experience, has done all the work and is willing to share this. I am grateful to him for this and his generous openness, but it does not make me want to learn programming 🙂

To return to his presentation, I was more interested in what he had to say about identity and community. I agreed of course that in social networks we are the product and that we are being exploited by large corporations such as Facebook and Twitter, who are selling and making a profit from our data, and I was encouraged by Stephen’s suggestion that in Web 3.0 the quantified self will give way to the qualified connected self, not measured by numbers but by our properties, affinities and things we have created. Our identity will be the thread that runs through an otherwise distributed, disconnected set of data.  This made sense to me and I was intrigued by the idea that we will each have a private key to access the web. No more passwords!

I also appreciated his discussion about community, which he suggested will no longer be based on sameness, but on consensus and being able to make decisions together. This seems such an important point for education and for this to be able to function, as informed citizens, we will need some fundamental critical literacies, which he suggests are:

  • Syntax – the ability to recognise patterns
  • Semantics – the ability to assign the meaning, importance and value of something
  • Context – being able to identify something in relation to its environment
  • Use
  • Cognition – inference, deduction, induction, for the best explanation
  • Change – processes of change, regressions, cyclic change etc.

There was more about each point in his diagram, and there will be even more as the course progresses, but the key point is that a decentralised system is needed – a system which focusses on consensus and being able to make decisions together.

Having first heard Stephen’s and George Siemen’s ideas on the need for a decentralised, distributed, connected web ten years ago, when they ran the very first MOOC on connectivism in 2008, it is great to see how these ideas might be developing ten years on.

Gardening in open learning environments

I spent most of yesterday in my garden, thinking about plants and how what I was doing in my garden might relate to my understanding of teaching and learning in open learning environments.

We have a large garden – ¾ of an acre. Over the years we have tried to organise the garden so that it is manageable. There is no way I can keep on top of it, even with help, and to be honest, much as I love my garden, and in particular the privacy it affords, gardening is not my first priority. The garden is too big for me to know what is going on everywhere and too big for me to manage all the plants. This is what one part of the garden looks like at the moment.

The Garden

Today I thought I would split some of the perennial plants and move them to fill up other gaps in the garden – such as the red and pink border plant (polygonum affine) you can see in the photo. But instead I found I spent my time thinking about dominant plants and how to deal with them, particularly Aquilegia, a deceivingly delicate, informal, pretty plant.


 Source of image

This year it has been all over our garden. I don’t remember ever planting Aquilegia in the 30+ years we have been living here. It seeds itself and pops up everywhere. But the problem is that it then, with its bushy leaf growth smothers every smaller plant around it and can crowd out even slightly larger plants. In other words it dominates and because it propagates itself, it is very easy, if you are not paying attention to your garden, to lose some lovely plants which it sits on top of. Aquilegia is the type of plant that is difficult to contain. It is everywhere. It is too much ‘in your face’! I spent much of yesterday either digging it up or moving other plants away from it.

The other plant I had to think about yesterday was Ground Elder. This is another plant which is everywhere is my garden. It is the worst kind of rhizome. What I really dislike about this plant, apart from the fact that it is almost impossible to eradicate, is that it springs up in the middle of another plant where it is definitely not wanted. This year I have had to constantly pick it out of the middle of my Hostas. To remove it completely from the Hostas, I would have to dig them up too.

Some plants seem to manage to seed themselves (or the birds seed them) and then grow into a self-contained shrub without causing too much bother to the other plants around them. An example of this that I really like in my garden and which is looking particularly lovely at this time of year is ‘sweet amber’ (hypericum androsaemum).

Garden plant

This plant is no trouble so long as you leave its berries alone, which are poisonous. If my children were still young I would be thinking seriously about digging it up too.

And then there are the trees. We have a number of large trees in our garden, such as beech and sycamore, which as they grow can create too much shade for other plants to thrive, but for me, they are much easier to manage than the Aquilegias and the Ground Elder. The trees seed themselves too, but it takes a long time for the seeds to get established, long enough to ‘nip them in the bud’.

So yesterday, whilst gardening I was thinking about the various approaches I could take to ensure that my garden thrives.

I could take a ‘hands off’ approach and leave it all to nature – let the self-seeding plants, rhizomes and trees dominate, take over and ultimately cause the death of many other plants. I’m sure the garden would survive, but what kind of garden would it be and what would happen to the diversity of plants? I’m not sure how attractive or interesting the garden would be as a result of this approach.

Or I could spend every waking hour, which is what I think it would take, to make sure every plant is growing exactly where I want it to, when I want it to. I think there is a lot to lose from taking this approach. First it would be a constant battle – nature has to be wooed rather than fought. And then there would be the loss of all those lovely unexpected surprises that a garden can bring.

But I think the only answer for me is somewhere in the middle of these two extremes. If I took a ‘hands off’ approach I would question why have a garden at all, when I only have to walk into the nearby countryside to experience the results of letting nature take over. Taking a super-managed approach wouldn’t work for me either. I think it would quickly become boring. I want my garden to be a pleasure, not a chore, but I also want it and the plants in it to survive and thrive. To ensure that they do, I can’t allow a free for all in my garden. It does require some management. In particular I feel that it is my responsibility to manage those dominant, self-seeding plants and rhizomes, otherwise I might as well not have a garden at all.

Of course, the little I did in my garden yesterday is far from the whole picture when it comes to creating a beautiful garden. Nurturing plants so that they show us their full potential requires knowledge and expertise. It’s related to getting the balance right between structure and agency which I wrote about in my last post. A garden near us that seems to have really achieved this is Gresgarth Hall Gardens.  There’s a lot to learn from this beautiful garden.


We only have to compare the photo of my garden with the photo of Arabella Lennox-Boyd’s garden, to see that there’s more to gardening than just management.

Evaluation of Open Learning Scenarios

Screen Shot 2014-08-04 at 10.18.10

In September Roy Williams and I will be giving the keynote for this conference in Graz, Austria, at the invitation of Jutta Pauschenwein and her colleagues. The title of the conference for those who do not speak German is Evaluation of Open Learning Scenarios.

The title of our keynote is:

Surfacing, sharing and valuing tacit knowledge

This is the first blog post in a series that we hope to write between now and September 17th. The aim is that these posts will act as advance organizers. We know from experience that some of the ideas that we will discuss in our presentation need more time and reflection to take in than will be possible at the conference itself. We also know that we won’t have time at the conference to cover everything we have thought about in relation to this presentation and all the work we have done on the Footprints.

This is a small annual conference (usually about 100 people). Last year the conference topic was very popular – Learning with Videos and Games; 150 delegates attended.

Jutta has told us that this is the 13th year this conference has been offered. It attracts a loyal group of delegates – university teachers, school teachers and trainers of companies, from Austria, Germany and Switzerland, some of whom attend year after year. Jutta has told us that unlike many of the German speaking conferences, which focus on scientific articles and presentations, this conference takes a more pragmatic approach and attracts an audience who ‘want to know how to do something’. Jutta has therefore invited us to speak about how we use our work on Footprints of Emergence to evaluate learning in open learning environments. She herself has been using our Footprints of Emergence drawing tool extensively since 2012.

Jutta and her colleagues recently used the Footprints for an assignment in their MOOC – Competences for Global Collaboration (cope14) and have often used them in their work in the past. Jutta blogs about them and has, with her colleagues, written articles and presented papers at conferences that make reference to the Footprints.

The conference presenters will also submit papers for review. Here is the programme for the conference – Programme for Graz e-Learning Conference

….. and here is the Abstract of our paper:

Surfacing, sharing and valuing tacit knowledge in open learning

Roy Williams

Jenny Mackness


This paper is situated within the paradigm of open, emergent learning, which exploits the full range of social and interactive media, and enables independent initiative and creativity. Open, emergent environments change the way we experience learning, and this has implications for the way we design and manage learning spaces, and describe and analyse them. This paper explores the ways we have engaged with these issues, as participants, designers, researchers, and as facilitators, and how we have reflected on, visualized, shared, and valued the rich dynamics of collaborative discovery. In particular, we explore how emergent learning can be enabled by using uncertain probes rather than predictable outcomes, by emphasizing tacit rather than explicit reflection, and by seeking ways to give the learners back a real voice in a collaborative conversation about the value of learning and teaching.

Key words: probes, Footprints, emergent learning, tacit knowledge, MOOCs

This paper will ultimately be published along with all the other papers, in an open e-book. For last year’s e-book see the FH/Joanneum Website

I don’t know how often the keynote for this conference has been given in English. Unfortunately neither Roy nor I speak German, but we welcome comments on this blog in either German or English. Most of the papers for the conference will be presented in German, but Jutta and I will run a workshop at the end of the day in both German and English.

It goes without saying that we are very much looking forward to meeting Jutta and all her colleagues and are grateful for this opportunity to present our work in Austria.

SCoPE Seminar: Digital Badges Implementation

Peter Rawsthorne  spoke to the SCoPE community about badge system design and implementation in a live webinar last night. See the SCopE site for a recording

Peter is a mine of information  about this subject (see his blog). It seems that digital badges are probably here to stay. Some pretty heavyweight organizations appear to be investing in them –  see Peter’s post An introduction to badge systems design. Some current key questions for those in the digital badges community seem to be around

  • how to come up with a common international standard for badges
  • how to develop the technology to easily design and issue badges

What has been most interesting for me during this seminar, is my own feeling of discomfort with all this discussion about badges. I have been reflecting on why.

First I was reminded in last night’s webinar of Etienne Wenger’s ‘purple in the nose’ story. When meeting a friend to share a glass of wine, he suddenly realized that his wine-tasting friend (who described wine using an unknown language – ‘purple in the nose’), was a member of a community to which Etienne did not belong. Etienne had to decide whether he wanted to belong to that community and learn that language. I have felt the same about this seminar. I feel ‘outside’ this community of digital badge enthusiasts.

Maybe those involved in designing and implementing badges have already been through the questions which remain for me; questions about the credibility of these badges, their value, their integrity, their status, what they represent, who they represent and so on.

A most telling comment for me in the SCoPE discussion forum has been

‘More hack, less yak!”

Our facilitator has clearly been frustrated that the group has been ‘yakking’ about the issues rather than getting on and completing the tasks. As he put it, with good humour, ‘Sheesh…. What a bunch of academics <big smile>’

So I still wonder whether the badge system will promote the ‘completion of tasks’ approach to learning, more than a focus on developing a depth of understanding.

The word that kept going through my head in last night’s webinar was ‘control’.  The discussion of the design and implementation of badge systems made me wonder whether this could ultimately disempower learners rather than empower them. Given that my current research interests are related to emergent learning, I am struggling to see where digital badges would fit with this.

There was a brief discussion at the end of the webinar about the possibility of individual self-directed learners designing their own badges and legitimizing them.  For me this was the most interesting aspect of the discussion. I would have liked more ‘yak’ on this 🙂 .

Finally I wonder whether the earning of badges will be more important to some learners than others and if so, what the reasons for this might be.  I say this because one member of my family is very keen to earn and collect badges, whereas I don’t seem to have much enthusiasm for it.

Emergent Learning Webinar – recording

I need more time to think about the outcomes of the webinar. We had a good turn out – about 30 people – and also lots of discussion in the chat. People were also very good about interacting and participating in the activities we had planned for the session.

For now I’ll just thank everyone and post up some links to information.

The power point we used is here Emergent Learning presentation (PPT) You will see that there is not a lot in it. We tried to plan the session to allow for emergent learning 🙂

The chat room transcript is here Emergent Learning Webinar Chat Transcript

This is The recording of the Elluminate session

We are hoping that there will be further discussion in ELESIG – some comments have already been posted

There is still lots to think about and discuss 🙂

New researcher

I finally managed to submit a research paper. I’m fairly new to this and I can’t say that it’s all been plain sailing. For a start the focus on ensuring that your research is based on evidence has given me qualms about blogging. I know that blogging is about opinions, but if you have an audience then you have some sort of responsibility to ensure that you’ve got your facts right – or is that the reader’s responsibility in blogging?

What did I enjoy about the research? Mainly the thinking and analysis. What did the data reveal? What were the implications of the data? Has anyone else had anything to say about it? Do I agree with them or not? Where is the evidence for my thinking? Yes, the thinking through was the best bit.

Collecting the data wasn’t too difficult as the idea for the paper came after we had collected the data  (a project evaluation). Analysing data is hard work, especially if it involves interviews.

So what was difficult? For me it was the writing and trying to get the most salient points down in a limited number of words. Worrying about whether I really did have the evidence for the content. Worry about whether I had understood other authors correctly and cited them accurately. Working collaboratively at a distance. Trying to keep the train of thought going whilst waiting for c0-authors. Trying not to get in a muddle when co-authors’ ideas came back. Worry about how the paper might be received.

What don’t I enjoy about research? All those submission requirements. All those references to type up. Questions about who should be first author ( I really hate this aspect of academic work). The fact that even if the paper is accepted for publication its unlikely to be read by many people unless you pay an exhorbitant amount to allow open access. The fact that even when you’ve submitted it you know it could have been better – if you’d just had a bit more time!

I suppose its all a learning curve.