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Glasgow Caledonian University is explicitly values-led, with a strong sense of purpose derived from its mission as the University for the Common Good. We understand that the next decade will require us to make a significant contribution to addressing a range of global challenges as identified by the Sustainable Development Goals (SDGs). Whether they are in relation to poverty alleviation, the reduction of inequalities, the use of artificial intelligence to deliver key services, the promotion of social and economic well being or climate change, GCU is focussing on having a local and global impact.
The SDGs provide the overarching framework for the University's Strategy 2030. Our vision for 2030 is to be recognised as world-leading for social innovation: delivering transformative education and impactful research through purposeful partnerships as a globally connected University with an engaged University community committed to the Common Good.
The Principles for Responsible Management Education have informed the Glasgow School for Business and Society's educational approach since joining in 2012. The integration of PRME is led by the School's Senior Management Group, supported by an active PRME Lead who acts as 'knowledge broker' between multiple PRME platforms (PRME Champions, Chapters, and Thematic Working Groups) and academic colleagues. The School provides the PRME Lead with a range of resources to ensure that this work is impactful (time allocation for PRME work, financial support to actively engage with PRME networks, senior management group support).
SDG Integration in all academic activities is an integral part of Strategy 2030, led by a University-wide SDG implementation group that has five workstreams, each led by either a member of the Executive Board or a senior manager. The five workstreams relate to the curriculum, research and knowledge exchange, student engagement, and communications. The integration of the SDGs in to all educational activity, and the implementation of PRME play an essential role in delivery of the University's Strategy 2030.
Mapping of SDGs in the curriculum (the method used for doing it)
The first step towards SDG integration in the curriculum was to create a cross-university working group, headed by a member of the Executive Board, to lead SDG integration in the curriculum, a key objective of Strategy 2030 and the Strategy for Learning. This Group of eight is headed by a member of the Executive Board, and is made up of representatives of three academic Schools in Glasgow and a campus in London, the student association, and members of university policy and planning department, quality office and the university's facilities team.
Once the Group was formed, the second step was to gather, share and discuss knowledge on SDG integration from around the world, so that group members developed a shared understanding of different ways to go about this task. The University's PRME representative took the lead on this, sharing publications such as the Sustainable Development Solutions Network's 'Getting Started with the SDGs in Universities', PRME's 'Blueprint for SDG Integration in the Curriculum, Research and Partnerships, and the United Kingdom's Quality Assurance Agency's (QAA) guidance on Education for Sustainable Development (ESD). The Group decided to use PRME's Blueprint for SDG Integration in to the curriculum, research and partnerships to guide its work.
The third step entailed 'mapping' of the SDGs in current educational programmes, in an attempt to ascertain the extent to which the SDGs feature in current provision. While there are different approaches to mapping the SDGs in the curriculum (see PRME SDG Blueprint), the Group opted to use artificial intelligence (AI) to run a set of SDG 'key words' through the module catalogue. The challenge here was choosing a set of SDG key words to use for the mapping exercise, given that there are different sets to choose from, with 74, 134 and 264 words respectively (see PRME SDG Blueprint for more details).
The Group decided to run all three sets of key words through the module catalogue as a learning exercise, to observe any variations. To do this, it was necessary to collect details of all modules running across the University. To do this we enlisted the help of University registry staff to provide an Excel spreadsheet populated with text from all entries in the university module catalogue. The collated texts included the module title, summary description, module content, learning outcomes, and assessment.
In the first run, University registry identified 4340 module codes, but after cleaning the catalogue by eliminating duplications and modules with less than 20 students, the total number of modules examined was 2300. To expedite this analyse efficiently, the group accessed additional technical expertise to set up an Excel spreadsheet that allowed us to identify how many, and which key words, related to which SDGs, were present in which modules.
The results of this mapping exercise was enlightening, but raised more questions than gave answers. Perhaps its greatest impact was opening the eyes of group members to the intricacies of mapping the SDGs in the curriculum, the resources required (time and expertise) and the challenges of establishing a robust base line that gave us a clear and reliable picture of the extent to which the SDGs were already integrated in to the curriculum.
Data analysis showed that 24% of all modules had six or more key words; 36% of modules had more than five; 51% had more than four; 68% had more than three; 85% had more than two and 95% had more than one SDG key word in the analysed text. Given the total number of SDG key words used (134) these results were surprisingly low, and suggested to us that the language used in descriptions of modules in the catalogue was not congruent with words used by the United Nations in key SDG texts.
Using SDG key words as an indicator, analysis also gave us an indication of which SDGs were more or less prevalent in current educational provision. However the results here differed, depending on which of the three sets of key words were used. Analysis indicated that key words associated with SDGs 1, 2, 5, 6, 7, 10, 14 and 15 appeared most frequently (in at least ten different modules). However, relatively few module descriptors contained language associated with the the majority of SDGs.
The outcome of this mapping exercise was inconclusive. While useful, we feel that quantitative mapping approaches using artificial intelligence needs to be augmented with a more qualitative approach, that entails a closer, human reading of module descriptors. The over-riding conclusion was that the presence in themselves of key words in module descriptors tells us little about SDG integration, as the meaning of words depends very much on the context.
Lesson One: Mapping of the SDGs is a complex task that cannot be undertaken by a single person - it needs a team approach that includes academics and staff with access to university systems.
Lesson Two: Mapping requires different types of knowledge and skills. Firstly knowledge of the SDGs themselves, including knowledge of targets associated with each SDG. Secondly it requires knowledge of existing approaches to 'mapping'. Skills in both qualitative and quantitative data analysis are required.
Lesson Three: Mapping using SDG Key Words is widely accepted as a first step towards SDG integration in the curriculum. However our research revealed different sets of key words. In a 2019 article in the Sustainability Journal Brugmann et al. of the University of Toronto provide a list of 74 key words. A team of PRME Champions have augmented this through close reading of more recent UN texts, and compiled a list of 134 key words. Colleagues at the University of Worcester in the UK developed a 'Big Benchmarking Tool' (BBT) using artificial intelligence, with 264 SDG key words. Institutions using key words need to decide which set of key words they are going to use, and why.
Lesson Four: Words are only words! Reliance on the presence of key words in texts can be hazardous. To illustrate this point, the word 'environment' is a key word in UN SDG texts - and in the context of the SDGs this relates to the natural environment, associated with climate change (SDG 13). However what we found is that most business school programmes use this word in relation to the business, as opposed to the natural environment. If analysis picks up the word 'environment' when used in this context, then it could lead to misinterpretation.
Lesson Five: An optimal approach to mapping requires both quantitative and qualitative analysis (close reading) of texts, because context matters! Qualitative analysis is far more resource intensive than quantitative (using AI), as it takes much longer to physically read texts.
The main resources needed for mapping are the time of several academics, access to university systems to gather data on educational provision, and people with a combination of quantitative (Excel and other) and qualitative research skills. Students should also be engaged in the process, and this may require payment.
In the short term we will enlist as many students as possible to help us to undertake a qualitative analysis of module descriptors on key programmes. We plan to provide training for them to do this, and will probably need to pay them. In this second stage of mapping we will draw on the approach of AASHE STARS approach to mapping sustainability, whereby analysis determines whether the SDGs are explicitly or implicitly integrated in to a module, or not at all.
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