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H818 feels quite different to either H800 or H817.

Both of my previous modules felt solidly academic even though the delivery, assessment and teaching was done differently. I basically knew that I had to do the activities, do some extra reading, write an assignment which answered the question and was internally logical and then I would succeed.

H818 feels, already, like it might present of a challenge. There is a very strong push to produce something to 'publish' rather than a piece of work which will demonstrate to your tutor that you have understood the course and grasped the relevant concepts.

The word 'networked' obviously provides a clue but the extent to which we are to be working as a group n H818 scares me a bit! Group work in H817 was difficult!

Plus I am having to get to grips with yet more OU resources which don't quite match proprietary equivalents in terms of usability, intuitiveness or appearance.

Argh.

What will all of this mean for me?

Human nature is essentially self-centred. Any new project, innovation, change or progress will be assessed by individuals by how it will affect them. However successful learning analytics promises to be in terms of creating better environments and activities to foster better learning - the individuals who will need to change their practices to accommodate change will, at least initially, think about what will change for them. Educators may have concerns about increased workload, they may have concerns about their own ability to manage the newly complex world of blended learning and fear that their inability to grasp and engage with it may have consequences for their own careers, they may not really understand what is being asked of them or why change is being implemented which will compromise their engagement.

Why are we doing this?

Changes in LMS or VLE in any institution is likely to be made at a high level but working out the nuts and bolts of the new technology and process falls to the educators at the 'coal face'. The coal face workers may have less understanding of the 'big picture' or long term aims and objectives but will have to make significant, time consuming and difficult changes to their own daily practice, Without a good understanding of the strategic aims it is hard to enthusiastically participate in the strategy.

Our ancient traditions must endure!

Universities have a 'model' which has endured for many centuries in some cases (and even in new universities the 'model' is often older than the institution). The accepted model determines the selection of students, the learning activities, the curriculum, the assessment methods. Any effort to radically change any part of the model meets resistance. University leaders are expected to inspire but not actually make any changes!

The opening paragraph of this paper by Dawson et al. neatly summarises a major weakness with learning analytics - that the data gathered is gathered incidentally rather than with pedagogical intent.

The obvious question to ask is 'what data would be more useful?' and then 'how can we collect that data?'

Social Learning Analytics is based on the premise that the answer to the first question is 'information about the interactions between learners' based on the observation that knowledge is increasingly distributed and learning has become less about learning knowledge from a 'wise sage' and more about connections and collectively held knowledge.

The second question - how can we collect that data? - presents a problem. It is not difficult to track forum contributions or similar within an institutions VLE. The interactions can be automatically tracked and the length, time of and words within those posts can be classified and codified but the assessing the quality of engagement requires human input. This is merely the first issue: most interactions between students don't happen within the VLE. However slick an institutions VLE is it is unlikely to be as intuitive, familiar and easy as platforms like Facebook and WhatsApp. Students will opt for easy for them over helpful for the institution.

The idea of any institution monitoring and analysing my Facebook and WhatsApp conversations is creepy!

I got stuck this weekend.

I grasped the concept that Lockyer et al. were communication. The checkpoint vs process comparison is simple but beautifully so. A major criticism of learning analytics, as we have studied to date, is that it necessarily uses the available data (which has not been collected with pedagogical advances in mind) rather than data being collected specifically with analytics in mind, Checkpoint data is the main data we have and shows us the easy to measure metrics - who clicked on the link? When and where? On what device? How long were they logged in to the VLE? How often did they post in the forum? When did they submit their assignment? How good was their assignment? How does any of this correlate with the socio-demographic data we hold about them?

The process data is more difficult to measure being more nuanced and essentially qualitative. Questions which might generate process data could include:

• What was the quality of the forum postings? Did they demonstrate real understanding and engagement with the materials?
  
• Did the individual make thoughtful comments about other people's work? Did those comments lead to a fruitful discussion about differences in perspective?
  
• Has the learner managed to apply any of their learning into a new context such as their own workplace? What were the results of this?
• Is there evidence of meaningful collaboration, knowledge sharing, discussion and debate between learners?

I know that we use Google Analytics at work but not for Elearning. I have never been involved in the discussions about Google Analytics nor have I seen the data. However - as a data junkie I now carry a strong urge to demand access to all the data sets because I can see how interesting this could be.

With regard to applying Google Analytics to learning I am initially struck by how this model is clearly designed with commercial applications in mind. The services which might be of benefit to a learner or an educator are only useful insomuch as they may enable better, more targeted and more appropriate, learning opportunities to be developed.

Google Analytics is, I believe, a commercial enterprise. As with all such enterprises - the principle aim is profit and other gains are incidental. Gains associated with learning are, therefore, mainly for the aspect of learning which is most associated with profit - the institution.

However - this data *could* be used to help the learner and the educator, The issues with using it that was are not only due to a profit motive of a private company but the way that big data may have to become much more specific to be useful in individual circumstances. I would, for example, be very interested to see how well I am doing in H817 compared to other students on the course, compared to students in previous cohorts. I'd be fascinated to know what expectations the OU may have had for me based on my simple socio-demographic information. I would like to see where I rank in terms of engagement with the material and I would be interested to learn of any aspects of H817 I had simply failed to grasp properly. I would love it if the curriculum I followed in H817 would shift and sway according to my interests, the pace I was most comfortable with and even my personal schedule. If I were to know all of this though it may be at the expense of the privacy of other students, it may be at the expense of the integrity of the course and it may be at the expense of my own work ethic!

Learning analytics is clearly a term which is used to describe a particular phenomena which can happen on a wide range of scales.

Personally I am interested in how my individual socio-demographic circumstances can predict my success (or otherwise) in any aspect of learning and how interventions can be targeted to assist me. I am not entirely selfish - I am also interested in how this can be applied to other people!

Professionally part of my role is to tutor aspiring medics and dentists for the UCAT exam (formerly UKCAT) which is an aptitude test which must be taken as part of an application to most medical / dental schools. Upon registration the UCAT consortium ask each applicant to complete a series of socio-demographic questions - racial group, gender, level of education reached by parents (the vast majority of applicants are 17 years old) and the job title of their parents (presumably used, alongside education, as a proxy for social class). They already have the applicants post code and know if the applicant lives in a household with low enough income to qualify for a bursary. This information is not supplied to universities but is reportedly used to improve the UCAT for future cohorts. Pilot questions are trialed with a view to ensuring they are as equitable as possible. I imagine that groups of statisticians gather around data sets and assess why various questions performed better with people who had parents with higher educational qualifications, or who shared a similar ethnic group. (Incidentally - I teacher friend of mine got very frustrated one year when the disadvantaged children who attended her inner city primary school were faced with SATS questions about going to the theatre, and using a honey dipper - two activities which were entirely unknown to most of the children she taught. A huge failing in learning analytics or a cynical attempt to maintain existing privilege? Who knows!)

The articles we read in this activity looked at early learning analytics on a national scale. I also find this very interesting. The variation between educational styles and ethos between different countries is driven by many factors including culture, politics, and resources and comparisons can be meaningful and meaningless depending on how well the complexities of the issues are understood.

The first paper compares the USA to other countries - noting not only a lack of progress when compared to nations of similar levels of development and wealth - but also an up and coming threat from developing nations with very large populations.

The second paper introduces the idea of using analytics to shape future US educational policy at the national level with a coherent and unified plan. Affordability and value are key values but a need to match education to likely economic requirements is also significant.

The basic premise of these discussions assumes that there is a direct correlation between graduate level education and national prosperity. There is, at least in these papers in this time, little discussion about what is being studied and to what end - merely that high levels of education are necessary for continued improvement.

As is pointed out - both papers were written before 'learning analytics' was a phrase and though they clearly are referring to a similar process the absence of 'big data' on quite the scale as it is available today means that it's not exactly the same thing being discussed. However - the idea of analytics is clearly here with a vision to use data to improve polcy.

As if often the case in Wikipedia, the article on Learning Analytics began as a quick summary and rapidly mushroomed into a far more extensive treatise on the subject. However - the initial definition has had few versions. It changed in the first day, then again a couple of years later, but the sentence written in 2013 is the same as the sentence which opens the article today. The difference is that in today's article this opening sentence is followed by over 4000 words of further information.

I usually like to begin my investigations about an unfamiliar subject with a read of the associated Wikipedia article. I realize that it's not a peer reviewed, 'reliable' source but it is often succinct, accessible (especially to to the non-expert) and well written with good clarity. The learning analytics article is none of these things and it reads as an article written by committee (which is, of course, exactly what it is!).

The impression that the whole article gives me is that the subject of 'Learning Analytics' is as vast, as nebulous, as complex and as multifaceted as the two words would imply. H800 challenged every internal impression and idea I had about the concept of 'learning' so I am keenly aware of how 'simple' ideas can become mosaic when investigated and the word 'analytics' gives us no expectation of a simple and easily defined concept! Put two big concepts together and the creation of a gargantuan concept seems also inevitable!

The simple sentences above describe aspects of learning analytics. My impression is not that those who change the definition claim what is stated is incorrect, but that it's incomplete and inadequate. The extra information, text, ideas and paragraphs don't detract from what has been previously written as much as adding to, augmenting and complementing it. There are a multitude of associated concepts which overlap with Learning Analytics but the edges of each concept is blurry and undefined.

I suspect a concise definition which will satisfy everyone is impossible to develop but by looking at the areas everyone agrees with we can draw some conclusions. Such commonalities include:

• Data - the data is described as 'intelligent' and processes related to collecting, collating and analysing this data are all part of the definitions. Data is an inescapable part of Learning Analytics. It's the key ingredient and without data there can be no analytics.
• Discover, understand - data can enable a great deal of knowledge to be amassed and that knowledge can lead to understanding of crucial patterns within learning and teaching
  
• Prediction, modelling, advising and optimising - four different but overlapping ideas in this context. The way in which the data is used is part of what makes Learning Analytics what it is. The purpose of LA is, at least in part, the improvement of the learning journey for the individual and the cohort.
  

I've honestly never heard the word heuristic before (and I know a lot of words!)

Once more I am up against an OU activity task which I barely understand and feel utterly ill equipped to complete.

Our group project has done what many projects seem to do - rapidly mushroomed from being something theoretical and distant into being a fully fledged and almost complete project. After weeks of discussions and foundation work the actual thing feels like it has suddenly appeared. And now I am supposed to go and use it and find everything I can which is wrong with it!

There are a number of problems with this!

1. My personality means that I neither like to receive or give anything which can be perceived as criticism! Rob, my team mate, has done a phenomenal job and the tool created is looking really good. Are there things I would change if I had both full creative control and vastly improved technical skill - of course. Is there a single thing that I think is sufficiently bad that I want to create extra work and further debate - NO!

2. The 'heuristic' templates are complicated! I am unsure - even having read them all a few times - whether we are looking for broken links, unclear instructions, design features we don't much like, things we wish were there but aren't, things we wish weren't there but are.... it seems we have to connect every little quibble with some theory. This is making the whole task seem impossible.

3. Time is short. We need to get this done so only small things can realistically be changed. But I don't know what is small and what isn't because I have not got the faintest idea how this tool was built! It is not an exaggeration to say my heart leapt when it became obvious that Rob was a Moodle expert. (Cut me some slack though - I made the original template of the website!)

4. The site looks good. Any issues I have with it don't seem to fit the dominant heuristic model about usability. (Again - what exactly does it mean?!)

Anyway - I shall try to work it out.... again! And I also want to get a bit more done on my personal reflections about this project. I keep reminding myself that this accounts for 72% of the overall grade! ha

I remember being so grateful when someone who knows this stuff (a psychology graduate and trained counselor) told me about Imposter Syndrome! I thought I was the only one!

Anyway - that's been the story this week. I made a case study spreadsheet which has, apparently, been very helpful. I got it done reasonably early in the week which was good as I have been ill for a few days and unable to do a lot more. It was also helpful because my work was a foundation for other tasks which needed to be done and I was off the hook for them!

But it couldn't last forever. We had another web conference in the week about which I remember little. I was taking codeine and whilst it all made sense at the time I don't really understand the next steps!

Nevertheless I had a go this afternoon at two activities. I have produced *something* for each of them but I am extremely cautious about them both and think (as ever) that it will all be wrong and I'll be found out as someone who simply does not have what it takes for post graduate studies! I've been expecting to hear this from my tutor at every assignment point for over a year... somehow hearing it from a class mate would be worse! Less private for a start!

Group work is getting better. I've made my peace with the fact that we won't all be equally active or productive. And that includes it being ok for me to have a light week once or twice. Overall I know I have been a useful team member (at least if judged by participation and output) and I must be satisfied with that. I am seeing that what we are collectively producing is actually pretty decent. Six heads are better than one.... thought I might argue that three heads are better than six but that's another blog post!

I'm a week behind on activities (I think the whole group is and I think we are ahead of some of the other groups).

The first page of the fortnight which began a week ago used the words 'take stock' of what we had done so far.

Distributed group work has been challenging but also satisfying. I have been forced to learn and adopt new things but have also had the opportunity to show what I could do already. So here's my top ten of the project so far.

1. I have learned how to use Google Docs. This is hopelessly tragic as I realise how ubiquitous it is. However - now I know I know. It's been quite intuitive and I'll definitely use it going forward in different contexts
2. I set up a website! It's merely a Google Sites one but using the power of...err.... Google I did it. I really did it as a scratch pad for my own experimentation and I fully expected someone else to come along with something flashier and better (which would have been fine) but the team are editing it and it's coming together
3. Working with people about whom I know essentially nothing has been surprising, frustrating, fun and difficult. In real life we often may have to work with people we don't know well but working with people we neither know nor can see brings up challenges I wouldn't have anticipated
4. A good team leader is the crux of a project like this. I think of myself as a natural leader but I am so SO grateful that Vicky has been the Team Leader. She was the obvious choice (though she graciously suggested to the others that I could do it) and she's done brilliantly. I can see how much she is having to do and co-ordinate.
   
5. Sometimes it feels like you need to be seen to be doing something more than actually doing something. I'm not proud of this but I am self conscious that anyone might think I am a slacker!
6. Waiting for other people to do their 'bit' is frustrating in the extreme when you can't do your bit until they're done. I blame no one for this - I am fully aware that all six of us have complicated lives and that we all fit our studies around the rest of it rather than fitting our lives around our studies but when I have free time but can't get on with much.... I get a bit antsy!
7. There is always something you can do! This flies in the face of the previous point I know! You can never have too much background information and reading on board (though you do need to know when to stop - there is an infinity of information and a finite word count and deadline). Reading around the subject - even if I don't directly feed it into the group - enables me to make suggestions and raise issues I would not have thought of otherwise
8. Choosing the first thing (in our case the context) can take ages. As can making any firm decisions later on. Everyone wants to have a say and wants everyone else to have a say too. It is all too easy to waste time trying to ensure you arrive at absolute consensus. Pragmatically this is almost impossible and agreeing to an acceptable, albeit imperfect, route forward enables movement.
   
9. Cross cultural and cross time zone working presents challenges which are hard to quickly overcome. Our team members are spread over 12 time zones - a conference altogether is not going to happen. This is simple logistics. What is less simple is the cultural mores, references and markers which are the stuff of daily conversation but which can inadvertently exclude people.
10. Reflection is so important in every area of learning. Just as I have found this blog crucial for chronicling my OU journey I can see how properly facilitated reflection could be invaluable to anyone embarking on a new profession, study path or adventure.
    

I was actually at a National Trust tea room when my WhatsApp started to buzz with the news of the TMA02 results being out. This could have gone either way - I could reward myself with a lovely cream tea if I did well, or I could console myself with a lovely cream tea if I didn't do well!

I couldn't get my feedback on my mobile phone but I could log in and get my score..... and I did well! So much better than I was expected - a full 20% higher than I was braced for. Celebratory cream tea it was!

I'd found TMA02 hard work - I had a good idea but I found it hard to demonstrate a good theoretical grounding for it and had struggled a LOT with the word count. I understand that the OU don't want to make their tutors mark 10,000 word essays but sometimes the word limit is so restrictive that keeping within in is only possible at the cost of good examples, ideas and quotes.

I got home and immediately got my feedback. In light of the word count issue I was someone bemused to find many suggestions for extra things I should have discussed or points I could have developed further! Absolutely no comments to indicate which bits were superfluous! OU marking protocols are clearly devoid of irony!

But either way it's been good. I calculated that I now have 17.64% of the 40% I need to pass H817 and 35.28% of the 40% I need to pass the OCAS. That is not a bad place to be in when I have only completed 21% of the overall work and 42% of the OCAS marks available. 

I cannot express how much better I feel having had a web conference with 5 our of 6 of our team at the weekend. Making decisions is easy when someone suggests something eminently sensible and everyone just agrees! In a forum setting people seem a little more tentative in making suggestions for fear of being forceful (I assume) but some decisions simply need to be made.

As we are inventing our context as well as our platform, pedagogy and learning design we are in an unusual situation.Most learning design is created by people for a context which they have been presented with - not one they've invented. Most pedagogy and platform debates are framed by the platform that is available and the pedagogical values in place rather than inventing it all from nothing.

This openness can be exciting but also daunting. It's oddly easier to create a meal from a set of ingredients than to scour reciple books, go shopping and then cook, Too many options slow the process.

Because of that it's such a relief when someone says 'so... medics or teachers?' and someone else says 'I'd prefer teachers' and everyone goes 'fine' because most of us have no preference but don't want to step on the toes of those who do. And then, when that is decided, we get a bit of homework so that we can have a further discussion in a few days.

And in the meantime I am doing stuff. Nothing massive but peripheral and potentially useful things. Reading papers, extracting relevant quotes and writing a brief precis followed by my own take on it. I have added some stuff to the website - nothing  expect to make the final cut necessarily but scaffolding on which more can be done. It's hard to work on things which I know to be peripheral but a well rounded project needs the periphery. And foundational efforts make the rest of the work stronger and more secure.

RULE 3: Just do something