Many of us have heard the quote that "Culture eats strategy for breakfast" which is often attributed to the famous management guru Peter Drucker. My recent reading for H817 reminded me that this quote applies to more than just businesses in the traditional sense but also to universities.

This week I have been reading a paper by Macfadyen and Dawson (2012) called "Numbers are not enough." In this article they discuss several reasons for why evidence, in the form of analytics, is not often taken on board at universities in a way that drives stategic change. They suggest two broad reasons for this:
1. The perceived attributes of innovation
2. The realities of university culture

When talking about the attributes of innovation, they raise the suggestion that staff workload often blocks innovation or change because people do not feel that they have the time to engage with innovation. I can completely agree with this - workload is one of the most heavily cited reasons for not adopting new practices, and quite frankly, for a lot of substandard educational offerings. But I think there is more to it that than. It is not as though academics and many academic-related support staff are adverse to working long hours; it is a case, however, that all innovation is not created equal. Let's take a hypothetical example. Consider a situation where someone works really hard to redevelop a VLE for their programme or create a comprehensive assessment strategy or innovative module - what is their reward? Now you can make various suggestions here including greater student satisfaction, respect from colleagues for their expertise etc. They may even get a peer-reviewed article out of it, but for the most part, the reward is intangible. But now lets look at another situation, one in which those same hours are put into writing a grant application, which is also successful - what is the reward for that? In many universities the reward is much greater and much more concrete. 

The other reasons cited by Macfadyen and Dawson (2012) related to the culture of universities and below I have given some thoughts on each of them:

1. The fact that they tend to operate on a consensus governance model, which in reality is rarely reached. The opposite of this of course would be a strict hierarchy - something which would result in cries of top-down control and extremely unhappy staff. Having seen this first-hand myself I don't think anyone gains with the strict hierarchy, least of all the students but on the other hand having a decision actually made at a university, can sometimes be refreshing.
2. Faculty control over teaching and research is also raised as a potential cultural blocker to adopting innovation. I partially agree with this but I also think this faculty control supports innovation because it allows for smaller scale testing grounds. Whilst this relates in difficulty gaining consistency, it also support grass-roots innovation. The blocker for me is actually communication of the grass-roots findings rather than the fact the grass roots exist.
3. An organisation culture that supports change by adding resources rather than re-allocating them. This paper was written in 2012, which in the UK was just before the fee hike that change the face of higher education and, in some cases, put a massive strain on university finances, at least in the short term. I think we are much more comfortable now with the idea of reallocation but - given the comments above research - I would be amazed if funding would ever be reallocated from research infrastructure to education.
4. A curriculum structure that makes false assumptions about heterogeneity. I suspect this one is still true and possibly even more of a problem than it was in 2012 as we see a greater diversity in students.

In addition to the four listed above, I would like to add Change Fatigue to the cultural reasons why innovation is not often adopted. In some universities there is a constant cycle of changes - so much so that things nearly always reach full circle but many small changes happening one after the other create feelings of uncertainty and the benefits are often too small to be realised. This means that people just get tired of change, which appears to happen just for the sake of it rather than for good reason and to good effect.

Having reviewed the suggestions as to why innovation is rarely adopted, even where there is evidence to support its implementation, I agree there are a range of factors but I suspect they still all come down to one thing and that is the culture of universities - because it is this that determines the value of innovation rather than the inherent properties of innovation.

In this blog I am reflecting on how analytics, such as those generated by Google Analytics could be useful in education, specifically, what would be most useful to the different people.  As always within education I want to start with the learner. 

What can numbers tell me about how I learn and about how other learn?
The first part of this question might sound logical but why should a learner care about how others learn as well. I think there are two reasons they should. Firstly, the truth is that often there is an element of competition - maybe not openly amongst peers but certain in the job market and it is therefore helpful to have a sense of where you are in the cohort. Secondly, knowing how a first class student works can provide insight for other students. The latter is something we often lament in neuroscience - when trying to understand how, for example, the brain learns, we look at what happens when it goes wrong. Now this can be truly insightful but it is strange that we do not consider looking at the brains of those who have it mastered! I think there are a number of analytics that could help a learner address these questions:

• User explorer - i.e. the individual learner behaviour on the VLE for example
• Cohort analysis - where the cohort could be defined as your whole class e.g. every one taking a set module or every one taking a set module who performed similarly to you on the pre-requisite course etc.
• User Flow - this would be very helpful if shown for an individual learner and then for a high performing cohort. This would enable the learner to see how the strongest learners navigate their learning and could give them tips for changing their behaviour.

What analytics can I use enhance my teaching?
I think there is lots of information that a teacher can use from analytics to enhance their practice but I also think that with a class of 200, for example, individual level data will be conflicting and unhelpful so I think for the educator designing material/learning activities group level data is key. For example, the following could help:

• Demographic data including location: This can be helpful because it tells you a little bit more about your cohort and diversity but it is also a way to make your learning more inclusive. Take Psychology for example; the traditional student in this discipline is the white middle class female, but the field is becoming increasingly diverse and having an awareness of this enables educators to choose relevant and appropriate examples in their teaching. This is particularly important in a self-reflective discipline.
• Cohort analysis: This can be helpful to allow comparisons before and after specific changes to a module but also to see if any particular cohorts require extra support e.g. those with or without a specific A-level subject may require extra help in the first year with certain modules.
• User behaviour: For example, looking at how often people are logging and for how long can be helpful if the VLE will be used for specific time limited activities.

Following on from these group level analytics, if an individual student requires additional help then it is useful to have information on them specifically, similar to the kind of information that the learner themselves may find helpful.

What about TEL support staff?
We were asked as part of the activity to consider administrators as well, but in my current role, administrators have little to do with the design of the programme or student support beyond processing attendance and dealing with mitigating circumstances around assessment so instead I chose to consider the role of TEL support staff. For this group there is some potentially useful data that could inform high-level design of the online learning resources we offer, such as:

• Mobile devices and technology: It is very helpful to know what kind of devices learners are using to access learning resources. This gives a sense of what minimum requirements must be met and also whether we are spending too much resource on, for example, creating a better mobile app, when most students log in from a laptop.
• Benchmark data: Knowing how we compare to other universities could be very helpful. 

I think the key with analytics is that all data should be available to any role but that it is sensible to first provide the relevant data to specific individuals. If they then wish to delve a little deeper then it may be appropriate to share, for example, data you would normal reserve for TEL support staff with the educator. Of course, this would probably not be necessary if teaching and learning was co-constructed by all three of these key roles.

In the last two weeks I have attended two teaching related conferences. This is quite rare for me, partly because I am often too busy teaching to attend, but also because these events are rarer that the ubiquitous research conference.  During this period I have also been working on a collaborative project as part of my MA in Online and Distance Education with the Open University and drafting some module materials for the OU. These events have consolidated for me the belief that the best educational experiences arises from team work and that this team must include an effective manager and I wanted to use this space to explain why:

Why teams create the best educational experience? 
I remember my first experience on module production at the Open University, the module SDK228 - it was a baptism of fire. I drafted my chapters and sat in a meeting while they were systematically torn apart by my colleagues - and then I re-drafted them, and braced for some more tearing apart, which came in a slightly smaller dose...and so on until the final product emerged. It was far better than my first efforts. With every production that followed over the next six years, I grew in ability and confidence as I learnt the OU craft for top quality teaching materials. That is not to say I mastered it, but just that the critique was less savage as time went on and I began to appreciate it for what it was - the route to developing resources that supported students in learning to the highest possible degree. 
Fast forward a few more years and the need for team teaching has again emerged from the MA project where six of us have had six weeks to create a teaching resource for reflective learning in postgraduate medical fellowships. The best ideas appear to have emerged from the team rather than any one individual.
In my day job, I am now based at a conventional university where formal team teaching does not exist (at least in my programme). I draft my resources and finalise them alone - no one checks my learning outcomes and my assessment tally up and no one checks my resources are inclusive or appropriate for the level and context. This gives me an immense amount of freedom and, of course, I do talk to colleagues, informally bat ideas around and pick up interesting ideas at conferences that sometimes these cause me to change a plan or tweak things here and there but the level of team work is less and, I suspect, the quality of teaching is less. I think there are several reasons for this.

• Firstly, I can be as creative I am able to be but sometimes that different perspective is only there when a second, third or fourth person gets involved.
  
• Secondly, however much we check and double check, one person is always going to miss something, especially when the thing under review is a labour of love like your new module.
• Thirdly, I am only accountable to me. Yes the students give feedback (although response rates to surveys is often low) but ultimately, if the module is ok it is up to me to decide what to with it. 

All this is not to say that team working is brilliant, it brings immense challenges of working with a range of people - I always found it required the diplomacy I was not too hot on and it takes a while to understand the different team members. The module leader/chair is always over-involved; it is their baby after all. Then you have those who are 'comfortably reliable', they will produce great work when you need it. This is the ideal team player. Or the 'creative risk takers' - you and they know they can produce something brilliant but only if they can reign in the vision for long enough to work out the substance before the deadline.  You want one of these but probably no more! And then there are others who you do not really want at all, for example, the 'only half in the room' players - who give you something usable at the last minute ignoring much of what has already been agreed in meetings.  The diversity of academics on a team, often focused on the content and involved with other teaching and research projects as well, makes the management of the process very challenging and takes me to the next point.

The role of programme/course managers?
In my recent MA project, I took on the role of Project Manager. I did this partly because I have never experienced useful project managers (they just tick boxes, right?) and I wanted to prove to myself it was possible - that said, I think it should be up to the rest of my team to decide! Nonetheless, I think I made two useful contributions to the process. The first was purely organisational with appropriate chasing when deadlines approached and the second was ensuring consistency of learning resources and checking for accessibility, language use and standardisation of the VLE etc. At the Open University, these functions can come under the remit of the curriculum manager (CM) rather than a project manager. When I went left the OU to join King's, no such role existed. We did have some administrative support but this was not combined with expertise in the discipline and the in depth knowledge of the curriculum, assessment and university processes that curriculum managers have. I tried to explain the role to a colleague at King's only for them to refer to the CM role as an academic's minion - I politely pointed out that the reverse would probably be more appropriate but actually nobody is the minion here - this is a very much about two roles of equal importance. A module cannot run without academic input - we have the expert knowledge of the discipline and the pedagogy to know what and how to teach but, without contextualising this in our institutional policies, programmes, systems and style, the module will fail. So what does this all have to do with herding cats? Well I sometimes think being a CM requires you to herd cats both in the sense of gathering together disparate information to create a whole but also because you have to manage a team of academics that come with the curriculum and I suspect that can be quite a challenge a times. 

So going forward, when I think about effective teaching, I know I am going to thinking about how I can work more in a team to produce quality teaching and learning experiences. I am also going to remember, and keep reminding others, that there are crucial roles beyond that of the academic, that make effective teaching work and that as a sector, we should be investing more in those roles and recognising the value they bring.