Activity Data Synthesis

Thursday, 23 June 2011

JISC online consultation

JISC is currently undertaking a consultation exercise and wrote:

As part of our institutional engagement work, the JISC Organisation and User Technologies Team is carrying out an online consultation (using moodle) to identify emerging issues and concerns in UK Higher Education that we may, in the future, be looking to develop programmes of activity around. There are five top level areas each with a discussion forum attached, please feel free to either post a new concern or issue or respond to someone else’s post.
The site is at it’s a moodle site so there is a quick and simple 2 part registration before you post
Anything you can contribute will be helpful in shaping our future plans

I have added the following post on analytics - you may wish to comment or add others...

One of the key factors for both students and universities will be student success; though at times they may have different definitions of what this means.

There are two key areas here; retention and outcome (loosely result but also that the student has achieved what they set out to do). Retention is already good by international standards, but this does not give grounds for complacency, and there is much that can (and is) being done to improve it.

It is arguable that student success is also one of the factors in the student experience.

In this posting I want to look at one tool that can be used to enhance student success, where JISC is already doing some work, but much more could be done and would have a very positive return on investment for institutions. This is data analytics to support student success.

Universities and colleges are already collecting vast amounts of data about their students, but making very little use of it. Every time a student logs on to the VLE, undertakes a search of the library resources, accesses an e-journal, swipes their card through the library turnstile or lecture theatre the event is recorded in logs on servers at the university. Most of the time this information simply sits there gathering electronic dust until it is archived or deleted. However, there is much valuable information that could be used to help students to help themselves.

For example there are patterns of behaviour which may give early indications that a student is at risk of dropping out (non- attendance, declining use of VLE perhaps) where early intervention to support students may help them to achieve the results that they wanted to.

Similarly there are patterns of behaviour which may indicate that students are studying as effectively as they might, again where early intervention could be of great assistance to the student.

There are a number of areas where intervention at the national level would be of great value to the sector. These include:

  • Understanding the information that universities have available to them
  • Identifying patterns associated with success and failure. Note that these are likely to be discipline dependent. Some disciplines make much more use the library than others. They are also likely to be institution dependent as, for instance some universities make much more use of VLEs than others,
  • Developing algorithms to identify students at risk or with sub-optimal study patterns
  • Researching methods of intervention that actually support students to succeed. There is evidence that some approaches may be counter-productive

These methods can form part of the way in which to enhance student learning and success, and where national support will enable all universities and colleges to achieve more than they could by developing the tools and algorithms for themselves.


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