On Course project final report

You can download the final report (PDF) for the ON Course poject. Here are the conclusions and recommendations.

  • Implementing a programme/course management system is a large, complex project.  Before embarking on it, an institution must ensure it has the time, people and funding available to make it a success.  Stakeholders at senior management team level must actively support and drive the project.
  • The development of curricula within HEIs is a primary responsibility of academic staff. The implementation of a course management system should therefore include academics as key stakeholders.
  • The time needed to populate a new, structured system from existing unstructured information should not be underestimated.  It is likely that it will have to be done manually, and will take considerable time and effort.
  • Extensive and properly structured data about programmes can lead to more innovative uses of the information elsewhere.  Without a common, consistent structure and means of access, re-use (internal, public and third-party) is almost impossible.
  • The provision of an XCRI-CAP feed was, correctly, a minimum requirement for the JISC programme of funding. However, institutions should recognise the value of their full programme data on a much broader level, understanding that it offers insights into one of its core activities (teaching and learning) and can inform other change management programmes across the campus.[1]
  • Application development around the use of course data has so far tended to be marketing-focused. However through the use of visualisations and interactive tools, it could be put to much wider use. The HE community should consider how the use of course data might fundamentally change the design of curricula and provide the basis for discussion between staff and students about the re-production of academic life. Improving the level of oversight and insight into the core activity of teaching and learning can reveal and help question existing constraints in the curriculum design and QA processes, for example.[2]
  • Course data, alongside other datasets (e.g. space utilisation, research activity, energy use, facilities, etc.) provides unprecedented insight into the nature of our organisations. Institutional managers should approach their organisations as objects of research and development. The knowledge and skills exist within HEIs, among students and staff, to better understand, critique and develop the form of the organisation.
  • Data visualisation techniques provide a new and novel oversight of large and rich course datasets. However, due to the complexity of this data, the use of static visualisations quickly reaches their limit. Software applications are needed that help staff and students interact with the data and model new pathways to learning, reveal greater opportunities for collaborative and cross-disciplinary teaching, and critically evaluate the history and future of the institution.

[1] For example, in an earlier project, Lincoln produced tools for enabling closer collaboration between academics and estates staff in the redesign of campuses and the re-use of space. Similarly, visualisations and text mining of course data could be used to inform the collaborative development of curricula.  http://learninglandscapes.lincoln.ac.uk/

[2] At Lincoln, the curriculum design process has recently undergone changes recognized by the QAA (http://www.lincoln.ac.uk/news/2013/02/643.asp). ‘Student as Producer’ is the organizing principle of academic life, encouraging and enabling students “at all levels to view themselves as active producers of knowledge, rather than passive consumers.” http://studentasproducer.lincoln.ac.uk

ON Course – What’s Next?

As I haven’t posted on the blog for some time, I thought it would be useful to provide an update on progress over the past month or so, plus a preview of what I’m hoping to work on over the next few months.

Over the past few weeks I’ve written and submitted a paper to The International Conference on Information Visualization Theory and Applications. The contents of the paper follows the flow of most of my recent blog posts. Firstly, it covers the use of exploratory data visualizations in order to help make sense of large datasets. It then goes on to look at refining the data visualization process and considering the granularity of the data being presented. The final sections of the paper discuss the use of visual analytics – combining data visualization and statistical analysis, within the decision making process.

The next step for me is to look into designing and creating an application that will allow (for example) curriculum designers to view the complexity of the data available to them, as well as showing the potential impact of making alterations to seemingly small and insignificant areas of the curriculum.

As I’ve shown in earlier posts, there’s a lot of data to visualize – if you print some of the network graphs on A0 paper you can only just about make out which node represents which module, for example. As a result of this, I’d imagine that one of the main focuses of the next few weeks is finding visualization techniques and tools that will allow a lot of data to be shown to the user, but in such a way that it’s still a usable application.

As usual, I’ll be attempting to post regularly to document what I’ve been doing.



After being appointed as the web developer for the ON Course project on the 1st of  February, I thought it was about time that I wrote a blog post to introduce myself, so here goes!

For the past 6 months I’ve been working as a Web Developer Intern at the University of Lincoln, working on lots of different things, including open data visualisations and helping to organise the DevXS conference held in November 2011. During this time I’ve also been writing a blog, ‘Ramblings of a Developer’, documenting my work during the internship, discussing events and opportunities in the world of technology, as well as general ramblings or rants.    One of my main interests is open data, which is what makes this project exciting, I’ll be developing useful services and fun visualisations around new collection of open data sets for a full year!

The purpose of this blog is to document the steps that we take and the processes we go through during the course of this project over the next 12 months. The next couple of posts will deal with how I’ve been getting my head around the multitude of data sources that will be being made available over the next few months. Stay tuned!