I find myself in an interesting transitionary period in learning. I’m in the final stages of my part-time PhD study, just waiting for the copy editor to check the last two chapters and then its submission time. I’m participating – participation that has been negatively impacted recently by the desire to get the thesis finalised – in a MOOC, LAK11 and looking at returning to full-time study as a high school teacher in training. It is from within this context that the following arises.
Yesterday I read a reflection on week 2 of LAK11 Hans de Zwart in which he quotes from a MIT Sloan Management review article on Big Data and analytics. The quote
The adoption barriers that organizations face most are managerial and cultural rather than related to data and technology. The leading obstacle to wide-spread analytics adoption is lack of understanding of how to use analytics to improve the business, according to almost four of 10 respondents.
This doesn’t come as a great surprise. After all, I think the biggest problems for universities when approaching many new technologies is grappling with the fact that most new technologies have biases that challenge the managerial and cultural assumptions upon which the institution operates. Being aware of and responding effectively to those challenges is what most institutions and those in power do really badly.
One contributing factor to this is that organisations and those in power work on assumptions that seek to maintain and reinforce their importance. Let’s use my experience as a starting university student as an example. As a new student at the university I am receiving all sorts of messages designed to help me make the transition back to study. Do you want to know what strikes me most about these messages and the transition assistance being provided?
That the organisation and communication of these help/transition resources correspond more to the structure of the organisation than to what might actually be useful to a new student. Some examples.
The “we’re here to help” message is a list of the different organisational units, which perhaps is not that surprising. But how about the “guide for students”.
Structure of a university guide for students
How would you expect a University guide for new students to be structured?
- By program?
i.e. I’m enrolled in a Graduate Diploma in Learning and Teaching, a guide for those students?
- By discipline?
i.e The GDL&T is within the education discipline, a guide for those students?
- By organisational unit?
This university divides academic staff into schools and then schools into faculties (e.g. the Faculty of Arts, Business, Informatics and Education)
- One for the whole university?
Which would make the most sense? The more specific the guide, probably the more useful. But that might require more work (each program having its own guide) and lead to some fragmentation within the institution.
One of the whole university would reduce the workload and increase the commonality between students, however, it would fail to capture the diversity inherent in disciplines. I’m pretty sure that as a graduate education student, I’ll probably need to know things that are a bit different than an undergraduate engineer.
At this institution it is by organisational unit, by faculty. The institution only has two faculties. So there are two guides.
Content of the university guide
So, if the student guide is divided by faculty, then it must contain faculty specific information. Otherwise, why would there be a division.
The first really specific information mentioned was on page 12 of 19 when it mentioned residential schools for GDL&T students. However, some in the sciences and engineering do residential schools as well. On page 18 of 19 there is mention that Law students need to use a special referencing style. Apart from that there is no information that wasn’t generic to all students. Much check what’s in the other student guide.
Oh, this one starts differently. It has a letter from the Dean of the Faculty. Of course, it was only a couple of months into 2010 (by the way, both guides are still the 2010 guides, 2011 guides haven’t been uploaded yet even though a global “have you read the guides” message has been sent to all students) and the (acting) Dean had moved onto another role.
Another difference, this one mentions clothing and safety within laboratories and on field work. A lot more mention of RPL in this guide. Ahh specific information for engineering students. Must be a great help to all those non-engineering students in the faculty. And this one has screen shots of how students are to get assignment cover sheets, rather than the paragraph of text in the other guide.
So it does contain some different stuff, but still mostly institution level information and information that is already available in other forms elsewhere.
Why have these two guides?
In short, my answer would be, that the management of the two faculties have to do something. There doesn’t appear to be any other explanation why the student guides would be provided at this level. Not to mention that given they simply repeat information that is given elsewhere (and have yet to be updated for 2011) there’s probably no need for them. But it is something that has been done in the past, so it must be done now.
Organisational and cultural influences and problems for learning analytics
For me, this is an example of how organisational and cultural influences impact upon the effective delivery of learning and teaching within universities. Much of what is done, and why it is done, says more about the existing cultures, structures and agendas within the management of the institution than it does about what is best for learning and teaching.
And it won’t be any different for learning analytics. In many universities, the questions that will be asked of analytics will be those deemed important by management. It will be difficult for the questions asked to be designed to cater for the diversity of needs at the levels of discipline, program, teacher or student.
Which is why I’m worried when the Sloan article recommends this solution
Instead, organizations should start in what might seem like the middle of the process, implementing analytics by first defining the insights and questions needed to meet the big business objective and then identifying those pieces of data needed for answers.
The insights and questions that are defined are more likely to say something about the organisational and cultural influences of the host institution, than about what is best for learning and teaching.