Improving Learning and Applying GIS in Interdisciplinary Research

I guess I’m not alone in either struggling with GIS (Geographic Information System) technologies, or seeing colleagues struggle to effectively use it. When the GIS does not work, or when learning resources use jargon that the would-be GIS users do not understand, they tend to blame themselves. This should not be the case – though never intentional, badly designed systems, materials or practices should be held accountable and either improved or completely rethought. These problems exist, regardless of discipline, when using GIS.

My professional experience includes working in private, public and academic sectors, across a variety of industries, and I have seen this same issue continually arise – enthusiasm turning to frustration when people cannot do what they want to do with the GIS, so they abandon the technology. As GIS professionals, I believe we have a duty to do better and promote the overall understanding of GIS and associated materials, to improve the likelihood of success and uptake. It is my hope that through my research, we can learn how to better support an increasingly diverse range of GIS users, foster that enthusiasm for GIS and create a better and more inclusive community of practice with and around GIS.

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Patrick Rickles helping an interdisciplinary researcher learning GIS

My recently published article, titled “A suggested framework and guidelines for learning GIS in interdisciplinary research”, is based upon my PhD research and has been written with co-authorship and support from my supervisors, Claire Ellul and Muki Haklay. In the article, I share elements of my PhD work which focused on how people go about learning to use GIS, particularly in the context of interdisciplinary research. From this work, I make recommendations on how these results can be used, going forward, to improve the process of learning GIS for future learners.

To begin, I had to first understand what interdisciplinary researchers were doing with GIS and the issues they faced that might affect uptake. These preliminary findings were discussed in Rickles & Ellul (2015), which identified challenges and suggested solutions in interdisciplinary research, as well as a theoretical understanding of learning approaches. Based on an evaluation of prominent interdisciplinary studies using GIS, and observations of an interdisciplinary team’s use of GIS, the relevance of those challenges and suggested solutions were reviewed to support a learning approach. The knowledge gap and time constraints were the most common challenges, with building relationships and training often suggested as solutions.  Problem Based Learning (PBL) – where learners restructure their knowledge to solve real world problems as part of a collaborative process with other learners and/or educators – was put forward as a viable approach for learning GIS in interdisciplinary research.

 

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Modified Technological Pedagogical and Content Knowledge (TPACK) framework for learning GIS in interdisciplinary research

This article provides updates to and further enriches that initial research. An online survey of interdisciplinary researchers provided verification of the issues uncovered in the first article, with interviews providing a more in-depth exploration of what those issues may mean in a practical sense. An overview of those findings shows that interdisciplinary researchers are using GIS to create, analyse and visualise information; that they are using ArcGIS and QGIS desktop platforms as well as web GIS platforms such as Google Maps/Earth and ArcGIS Online; and that they are using informal learning methods (e.g. internet searches, watching a video, asking a more experienced person). The findings also suggest a more structured learning approach may be supportive of the learner, but PBL can be time consuming for both the learner and educator. Therefore, Context Based Learning (CBL), which recognises the importance of the context of the problem domain for the learning activity, but allows for materials to be created in advance, may be a more appropriate approach. Combining these elements, which modify the Technological, Pedagogical and Content Knowledge (TPACK) framework, guidelines and a specific framework are suggested for educators to use to support interdisciplinary researchers learning GIS. My further research has applied these in a practical setting using a learning resource titled “GIS Lessons for You” (www.patrickrickles.com/tutorial), to test the guidelines and framework. The results will be published as part of my PhD and potentially as a future article.

Patrick Rickles is a PhD student in the Department of Civil, Environmental and Geomatic Engineering at University College London, and is also an Implementation Analyst for the Department of Communities and Local Government.

Rickles, P. & Ellul, C. (2015). A preliminary investigation into the challenges of learning GIS in interdisciplinary research. Journal of Geography in Higher Education, 39(2), 226-236

Rickles P., Ellul C., and Haklay M. A suggested framework and guidelines for learning GIS in interdisciplinary research. Geo: Geography and Environment, 2017; 4 (2), e00046 (open access)

 

Mapping the “Tribes” of London

By Alex Singleton, University of Liverpool, UK

Our paper, The internal structure of Greater London: a comparison of national and regional geodemographic models, recently published in Geo, explores the geography of where we live to identify 19 distinctive “tribes” that characterise London neighbourhoods. This London Output Area Classification (LOAC) was created in collaboration with the Greater London Authority.

We employ an area classification technique referred to as geodemographics, which are a set of methods that were initially developed in the 1970s (with a model of Liverpool) by Richard Webber. Further details are given our paper, however, in brief, geodemographics are created using a computational technique that compares multiple attributes of areas (e.g demographics, employment, built structures etc.) and places them within clusters aiming to maximise similarity. These are then summarised with names and descriptions.

Within the UK, the Output Area Classification (OAC) is an example geodemographic classification, and was created on behalf of the Office for National Statistics from census data. A classification exists for both 2001 and 2011, and both were built with an entirely open methodology. However, one criticism of national classifications such as OAC is that they do not adequately accommodate local or regional structures that diverge from national patterns, which is an acute issue for London. This can be illustrated with maps of the 2011 OAC for London and the much smaller city of Liverpool.

A map of OAC SuperGroups in Liverpool. Source: http://oac.datashine.org.uk/#datalayer=oac11_s&layers=BTFT&zoom=11&lon=-2.8564&lat=53.4308

A map of OAC SuperGroups in Liverpool. Source: http://oac.datashine.org.uk

 

A map of OAC SuperGroups in London. Source: http://oac.datashine.org.uk

A map of OAC SuperGroups in London. Source: http://oac.datashine.org.uk

The problem with the national classification in context of London is evident from these images, with the majority of London classified into 3 clusters. However, the London classification presents a much more variegated picture of London.

 

A map of OAC SuperGroups in London. Source: http://oac.datashine.org.uk

A map of LOAC SuperGroups in London. Source: http://loac.datashine.org.uk

The best way to view the classification is on the website:  or you can search for your postcode – you can even let us know if you think we got your neighbourhood wrong!

About the author:

Alex Singleton is Professor of Geographic Information Science at the University of Liverpool. Alex’s Geo paper was co-authored with Paul Longley. Paul is Professor of Geographic Information Science at UCL)

References:

Singleton, A. D., and Longley, P. (2015) The internal structure of Greater London: a comparison of national and regional geodemographic models. Geo: Geography and Environment, doi: 10.1002/geo2.7.

Further reading:

  • More London-Liverpool Geodemographics Factoids:

In addition to the first UK geodemographics being created for Liverpool by Richard Webber (also a graduate of the University of Liverpool); and this paper a University of Liverpool / UCL collaboration; one of the earliest examples of area classification within the context of London includes the maps of Charles Booth created between 1889-1903 . Charles booth was a Liverpudlian philanthropist. His maps were created through direct observations, and partitioned London into a series of summarising groups which are available to view online.

  • For more on the history of geodmeographics in the US and the UK, see our other open access paper on the subject:

Singleton, A. and Spielman, S. (2013). The Past, Present and Future of Geodemographic Research in the United States and United Kingdom. Professional Geographer, 66(4), 558-567.