Models make meaning: visualising career readiness

Dr Bob Gilworth and Dave Stanbury explain the impact of reconceptualising an institutional career development model on increasing the understanding and impact of Career Readiness data

The widespread adoption of the Careers Registration approach to gathering and using data on student career readiness in higher education has catalysed the evolution of related institutional models of career development. These models simultaneously serve the purposes of informing the data gathering and analysis and helping to construct meaning across institutional communities. The models have the potential to be key enablers for careers professionals, academic colleagues, students, and institutional managers to use the data in the context of shared understanding of 'stages' on career development journeys. This article looks at the importance of devising, adopting or adapting a conceptual model, using an institutional case study as a concrete example. The purpose of the case study is to illuminate the process in its institutional context, rather than to promote any one model over another.

The Careers Registration context

Gathering and interpreting data has become a key element of higher education careers and employability practice in recent years.1 In some cases, the data is externally gathered and fed back into institutions in a standardised format. Graduate Outcomes would be the most prominent example.2 The Careers Registration approach is not externally prescribed or mandated. It is an institutional choice to generate internal data for the purpose of supporting students on their career development and employability journeys.3 In this case, institutions need to devise meaningful and practical ways of conceptualising student career development starting points and journeys to inform the process of gathering data, the categorisation of responses and crucially, interpreting the data and sharing meaning with those who can benefit.

The Careers Registration approach to gathering and using data provided by students through institutional enrolment processes was instigated at the University of Leeds in 2012 and disseminated at the AGCAS conference in 2013.4,5 Since then, it has been the core of a HEFCE/Office for Students national learning gain project.6,7,8 The approach has been implemented in many universities in the UK and in universities in Ireland, Portugal, Australia, and New Zealand. The UK Careers Registration learning gain project is being replicated in Australia.9

The Careers Registration process is widely understood by higher education careers and employability professionals in the UK and has been documented in The Careers Registration Practical Guide.10 Briefly, it involves students responding to statements/questions regarding career thinking and their acquisition of employability enhancing experience (usually work experience) through the enrolment process when they enrol as new students and every time that they re-enrol as continuing students. These two parts of the process are ubiquitous. A career thinking section (CR1) and a work experience section (CR2) exist in virtually all institutional iterations of Careers Registration. CR1 and CR2 can be thought of as the 'common core' of the Careers Registration approach, wherever it is in place. The data gathered from CR1 is often referred to as 'career readiness' data. In the professional discourse, the terms 'careers registration' and 'career readiness' can sometimes be used interchangeably. It may be helpful to think of Careers Registration as the process for gathering the data and career readiness as referring to the CR1 data and the models related to it. The case study part of this article uses the term 'CRQ' (career readiness questions or questionnaire) to describe the process and 'CRQ data' to describe the resulting data.

In addition to the common core, several institutions have added a third section (CR3) and where this is the case, the most common addition has been to ask students to respond in relation to their occupational sector preferences. A growing number of institutions are adding a fourth element (CR4) concerned with students' aspirations in relation to place, along the lines of 'where do you expect to work when you graduate?' The focus of this article is CR1.

'Journey and Stage' career development models

There was a relationship between data collection and dissemination and a basic model of career development from the beginning. The inception of Careers Registration at the University of Leeds and the headline categories which would be used to categorise student responses to the statements in CR1 were based on a pre-existing internal articulation of careers and employability purpose, which was to support all students to Decide (on options to pursue), Plan (to acquire the right experience, skills, knowledge and networks) and Compete effectively for opportunities in their chosen career areas. A fourth category of 'sorted' was used where students had chosen a response which indicated that they had a graduate role, a post graduate course or a business start already confirmed.

The Decide, Plan, Compete (DPC) model pre-dated the data collection and created the framework for analysis and interpretation.11 It enabled a degree of sense-making of the data through a framework that was already socialised across the institutional community to some extent. The model and the data collection approach were devised by qualified careers professionals. While the connection was not made overtly at the time, it is not difficult to see a link back to the Law and Watts DOTS model, with which those professionals were instinctively familiar.12

The original version of DOTS13 suggested four careers education stages as follows: Decision-making, Opportunity awareness, the capability to make effective Transitions and Self-awareness. Truyens14 suggests that the model was originally conceived as a descriptive tool 'to assess and describe a situation or where the client is'. The strong connection to the Careers Registration approach is the idea of 'where a client is'. A significant motivation for the inception of Careers Registration was to find a way to obtain the answer to the question 'where are you now?' in relation to career thinking, from every student in the institution. If student career development is considered as a journey, the answer to the question where are you now? is key to the ability of the institution to offer directions to the students on that journey.15,16

Although DOTS is a neat acronym, many practitioners felt that the sequence should be adjusted17 if the model was to be used (as it has been) as a tool to help clients to move ahead on their career development journey. Practice adapted the order to SODT, to convey what might be seen as a more logical sequence from Self-awareness, through Opportunity awareness and Decision-making to effective Transition.

Again, there is a direct link to the Careers Registration approach, especially in situations, such as the one in the case study, where there is a clear intention to share the model with students and to link support to it. An unintended consequence of the progression-based logic of the move from DOTS to SODT and the related models in Careers Registration, is that the model can be seen to assume straight linearity of the career thinking journey, though that was not the intention and as the case study shows, careers professionals are very much aware of the potential for career development to be an iterative process.

This quote from Peter Plant18 helps to sum up the importance of models in relation to careers work and in this case, to the Careers Registration approach: 'A model is a simplification. It aims at reducing complexity. In doing so, it provides an overview of a complex area at a glimpse, and, simultaneously, it runs the risk of being simplistic. This is the delicate balance.' Achieving this balance is an important consideration as the case study illustrates. As Plant goes on to say, 'the true sign of a robust model is that it is both concrete and adaptable, and easy and clear to communicate'.

It is important to be clear that the headline categories such as Decide, Plan, Compete rarely if ever appear in the student-facing data collection exercise through enrolment. Students interact with a set of statements describing various stages of career thinking ranging from not started thinking through to having clear ideas, applying for opportunities, and having their next move secured. An example list is available in the Careers Registration Practical Guide. They choose the statement which most closely relates to their own perception of their career thinking at the time. They are not asked questions along the lines of 'are you deciding?  or 'are you planning?' These are broader categories into which the responses are grouped for analysis. Student engagement with the headline categories becomes relevant when there is an intention to use those categories directly with students as part of their engagement with the provision of careers and employability support, as seen in the case study and the examples below plus numerous others from across the Careers Registration community of HE careers services.19

As the Careers Registration approach became more widely adopted, variations on Decide, Plan, Compete started to appear. Examples include Discover, Focus, Action at King's College, London20, No Plan, Some Plan, Clear Plan at University College Dublin21 and Explore, Focus, Apply, Sorted at the University of Melbourne.22 In many cases, including the examples noted here, there is a clear intention to share the model with the student audience as a way of tailoring messages, explaining the careers and employability offer and curating resources. This approach is intended to assure students that their individual starting point is valid, and that careers and employability support will meet them where they are on their career development journey.

In some cases, sharing the idea of career readiness with students and pointing them to relevant support, activities, and actions, operates at the level of the individual statement chosen by the student, rather than the headline category into which that statement fits in the institutional model. This is the case where institutions have adopted automated messages to students following enrolment. This individualised approach may sit alongside a more general offer which is based on the model and its headline categories. The University of Exeter for example, does both and in presenting their model on its Career Zone website it also shows which statements sit in each category.23

In many instances, there is a strategic intent to socialise the model with academic colleagues in the spirit of shared endeavour around careers and employability. Whether the principal target audience is students, academic colleagues or both, the community approach can be supported by practical, and widely shared models of career development.

The original set of CR1 career thinking statements were derived from student focus groups and were re-tested with students during the UK Careers Registration Learning Gain project. It seems sensible to continue to check these with students and to refine where necessary. This is also true of the related categorisation/career development models which have emerged and continue to evolve. The next section of this article provides a detailed description of that evolutionary process in one higher education institution, from the perspective of the project leader.

The case study

The University of Huddersfield has undertaken a project to review and reconceptualise the classic Career Readiness Questions/Questionnaire (CRQ) and to embed a new career planning model into professional practice. The project was a collaborative effort, led by the deputy head of the Careers and Employability Service (CES) with important contributions from Claire Aydogan, head of the CES and Abby Abbott, digital content and engagement coordinator.

The background to the project is that CRQ data has been gathered by Huddersfield since 2018/19. Historically the university has asked about prior work experience, career learning needs and sectoral interest as well as the standard 10 career readiness questions. Students complete the survey as part of registration (and re-registration) in September of each year. Completion rates are typically close to 100% with circa. 19,000 individual respondents. Over time the survey has become a well-established part of the employability infrastructure being reported on annually by the Careers and Employability Services (CES) and valued by internal stakeholders.

The project was initiated in Autumn 2020. At that time, it was clear that a growing number of universities were making greater use of CRQ than Huddersfield. There was at least one example of a university using CRQ to create a real time student dashboard in its Careers Service Management System (CSMS). This pointed to the potential to engage students in using their own data more actively in their career planning. It was also apparent that other universities were using CRQ terms on their websites as part of their broader information strategy and, in some cases, also using student CRQ status to target marketing messages. At the same time, it appeared that use of CRQ data at Huddersfield had plateaued. Analysis of data and dissemination within the university was located with the CES and was not directly connected with the wider set of employability data provided centrally. Systems and capacity factors also meant that there was often a delay between collecting the data and being able to release it to schools.

Taken together this pointed to the need to strategically reposition use of CRQ within the institution. The initial aim was to review the CRQ statements used in enrolment and the headline categories (or terms) used to categorise the responses, to provide a solid platform for future developments. Reviewing the categorisation terms supported an ambition to review the classic Decide, Plan, Compete model which had been imported in the process of setting up the data collection. This became the focus of the project.

The consultation aims were defined as follows:

1. Check if the current four over-arching terms (Decide, Plan, Compete and Sorted) were fit for purpose, including the intention to share the terms with students.
2. Consider if there are more suitable alternatives.

The project identified six key criteria for assessing CRQ terms. Terms adopted should:

• Resonate with and engage students.
• Enable students to effectively undertake career self-management by helping them identify key developmental tasks.
• Be meaningful for a range of school stakeholders.
• Facilitate interpretation and dissemination of career readiness data results.
• Be accepted by the CES and the Global Professional Award team (responsible for delivery of the University's employability award).
• Be congruent with current and emergent career development learning approaches being used with the university.

Process/method

The consultation was composed of four overlapping phases:

1. researching practice elsewhere across the HE sector
2. feedback from stakeholders on the classic CRQ terms and alternatives
3. reflection on findings
4. feedback on options identified. 

The first phase entailed an interview with an academic colleague with an overview of national and international practice in this area (academic adviser to the project) followed by desk-based research on CRQ practice at other universities identified through purposive sampling. This yielded a set of initial examples, with an additional example added in early during phase two. Examples were chosen to illustrate the diversity of good/innovative practice across the sector, provide contrasting approaches, and pragmatically constitute a short list that could be easily shared with stakeholders.

The consultation took the form of small semi-structured focus groups with key stakeholders. At these, the project was explained and set within the institutional context. It was made clear that the purpose was to ensure that terms used were fit for purpose. During the focus groups, each set of terms was presented separately, and attendees were encouraged to identify issues (positive/negative) with each in a non-directive context. Importantly, feedback was only sought in relation to the terms. The way in which each university used their terms and embedded them in local practice was out of scope. The focus groups ran over four months which enabled insights and issues identified from earlier sessions to be fed-forward into later ones. Focus groups were held with the following groups: The CES Careers and Guidance Team (Careers Consultants and Careers and Employability Advisors); The Global Professional Award Team (Trainers responsible for delivering the employability award); the CES Business Partnership Team (staff who work with graduate employers): Students Union Sabbatical Officers. This approach of running focus groups with discrete sub-groups was designed to ensure that each distinctive voice could be heard, in co-developing the approach from the outset.

Discussion

Based on the consultation, the project concluded that Huddersfield should not continue to use the current set of CRQ terms exactly as they were. While 'Decide' and 'Plan' were uncontroversial and widely viewed as acceptable, significant problems were identified with the two other terms. In all groups, most people had strong reactions against the term 'Compete' which was felt by some to be 'intimidating and negative', and potentially demotivating. Defenders of 'Compete, however, referred to the need to signal to students the realities of the competitive jobs market. The term 'Apply' was frequently offered unprompted as a more acceptable alternative.

Instances of the term 'Sorted' being misunderstood were cited. These included in a careers education exercise, where some students regarded being at university or having a part time job as being 'sorted'. There was a perceived risk that students approaching graduation or after might think they were sorted, when their careers were still open to change and development. SU officers noted that the term was not necessarily understood by international students. There was no consensus on what term would be a better replacement, however. Suggestions included, 'transition', 'ambition' 'accelerate' and 'succeed'. The latter provoked some strong and mixed reactions. Concerns included the potential for creating heightened expectations and putting pressure upon students. The impossibility of guaranteeing success for all was noted, as was the desirability of students defining their own career success. The situation of students who were retired or planning on non-paid roles was also noted.

The examples generated by the desk research all had merit. The balance of opinion favoured short, positive, memorable and action orientated approaches, with 'Discover, Develop, Decide and Act' (DDDA) gaining the most support. All the groups which considered this example (GPA, BPT and the SU) preferred its formula.

There was a widespread recognition that all terms potentially need explanation and would benefit from framing for contexts. It was acknowledged that career development is complex and iterative and that the set of terms used should express this. This was a subjective and institutionally specific exercise. Other institutions have embraced terms that Huddersfield has rejected and vice-versa.

Development

The project identified and evaluated three options for change.

Option 1: Minor changes to the Classic CRQ model. With this option 'Decide' and 'Plan', would be retained; 'Compete' replaced with 'Apply' and an alternative to 'Sorted' used. One challenge with this would be what to replace 'Sorted' with. Synonyms such as 'completed', 'finished' or 'concluded' arguably lacked energy and similarly the term 'placed' felt too passive. 'Succeed', on the other hand was likely to prove controversial as outlined earlier. Option 1 would have been relatively easy to implement but would have forfeited the opportunity for strategic change.

Furthermore, the Classic model and set of terms appears to imply a linear movement that begins with making a career decision. Using a modified form of the Classic model was felt to run the risk of obscuring the dynamic and adaptive nature of career development.

Option 2: Adopt the DDDA model from the desk research. All groups that considered the formula of terms used by this University rated it positively. It was seen as using memorable terms which had positive energy and conveyed the dynamic nature of career development. However, the project concluded that there was scope to retain the conceptual clarity of classic CRQ and to convey a stronger idea of process to aid career development, while emulating/retaining the strengths of the DDDA model.

Option 3: The Huddersfield model. The Huddersfield model aims to combine the dynamic and iterative quality of the DDDA example with the process clarity of classic CRQ. Starting with 'Explore,' the model moves clockwise though 'Decide', 'Prepare' and 'Apply', through to 'Develop' which speaks to the need to remain employable even when employed. Reflection and Resilience are central and ever present, relating to each stage but also capable of being treated as distinct activities. The large arrows show the main direction of travel while the smaller ones indicate the possibility of feedback and revision at each stage.

Project outcomes

Feedback was gained on the Huddersfield model from key stakeholders: the academic adviser, SU sabbatical officers; the CES, the GPA team (and subsequently school based academic employability leads). Feedback across the board was positive. The SU, for instance, really liked that the circle showed that students could go through the cycle several times and that it allowed for movement in both directions. They described it as 'mobile' 'flexible,' 'relatable,' and 'intuitive'. Staff valued the way that it included those in work, fitted with employer recruitment and selection practices and the way it supported an iterative approach to career learning based on reflection. The adoption of the new Huddersfield model concluded the developmental phase of the project and signalled the start of the implementation phase.

The original set of CRQ statements has been adapted to fit with the new approach and crossed mapped to the original CRQ system. The Planning department have incorporated CRQ data into the university's main management information system, Apollo, so that for 2023-24, academics will have access to course level data dashboards. The new model has been launched on the CES website and alumni advice is being configured using the CRQ model. Careers education sessions have been created in which undergraduates engage with the model to identify where they are and appropriate next steps to take. A bespoke PGR version of the CRQ questions has been developed for the Graduate School with supporting online-advice tailored to 25 different situations, which will be embedded into Progression Monitoring Meetings. These developments are being underpinned by the creation of over 40 research-informed self-help guides designed to address each of stage of the Huddersfield Career Planning Model suitable for self-directed and mediated learning, careers education and the Global Professional Award.

Conclusion

Feedback over time from the careers registration community24 suggested that in some institutions there had been a significant hiatus between getting the data collection and analysis in place and then starting to realise its potential. The hiatus could be seen as a threat to maintaining the process - 'what's the point of collecting this data if we don't use it?' or an opportunity to strategically reposition as in the case study. In seeing this as an opportunity and a challenge for careers service leaders, it is important to note that in every institutional instance of the implementation of careers registration, the university in question has chosen to incorporate an approach to supporting the careers and employability effort into its most fundamental and closely guarded business process, namely enrolment. This suggests that there is strategic appetite for this to succeed, but that is coupled with an expectation that the careers professionals as the internal experts, will drive this forward. This article seeks to illustrate the ways in which a conceptual model can aid that process.

The case study illustrates ways in which a perceived need to consider ways of categorising career readiness data obtained from students can simultaneously provide the impetus for devising a shared model which enables work with students based on a shared understanding of where they are in their journey and the configuration of resources made available to students on the same basis.

The reflections in the case study on data usage hitting a plateau, the perception of more effective use by other institutions and the need to 'strategically re-position' created a pivotal moment in moving on from simply having and reporting on the data to using it and the related model as strategic and operational assets in the day-to-day business of supporting students on their career journeys. The move to make data visualisation widely available across the institution will make it essential to socialise the new model across the academic community in the spirit of shared endeavour bringing CR1 data to life to enable work with students across the broader careers and employability eco-system.

While this article illustrates a number of variations on the original Decide, Plan, Compete model, it is important to note that some institutions have made a conscious choice to stick with the original model. Others have evolved journey and stage models with different category labels. There is no suggestion that any one version is inherently better than another. Instead, the suggestion is that whatever choice is made, active consideration of the model has played a part in categorising and sharing data and shaping the linked resources and activities.

What next?

One of the authors is coordinating an international project called CR+. The member institutions are users of careers registration, located in the UK, Ireland, Australia and New Zealand. The project is concerned with the ways in which the CR approach and related data can be used to inform, shape and evaluate careers and employability strategy and operations. It seeks to answer the question 'How do institutions develop and deliver their careers and employability strategies and operations now that they have data that they didn't have before?' CR+ will generate further work related to the topic of this article.

Notes

1. Winter, D (2019) 'The Rise of the Practitioner-Researcher' in Burke C and Christie F (eds) Graduate Careers in Context. London: Routledge.
2. Graduate Outcomes, HESA.
3. Starting points and journeys, University of Huddersfield, 2021.
4. Gilworth R and Thambar N (2013) Careers Registration: a data revolution. Conference presentation AGCAS.
5. Daubney, K (2021)  Careers Education to Demystify Employability : A Guide for Professionals in Schools and Colleges, McGraw-Hill Education.
6. Where are you right now? Using careers registration to support employability in higher education - HEA Surveys Conference 2017, AdvanceHE.
7. Cobb, F (2019) 'There's No Going Back': The Transformation of HE Careers Services Using Big Data, Journal of the National Institute for Career Education and Counselling, Volume 42, Number 1, April 2019, pp. 18-25(8).
8. How can career readiness learning gain support student outcomes?, Office for Students, 2019.
9. GCA's Career Registration Research Project, NAGCAS, 2021.
10. The Careers Registration Practical Guide, University of London, 2019.
11. Gilworth R (2022) Careers and Employability in a data-rich environment in Broadley, Y. Cai, M. Firth, E. Hunt, & J. Neugebauer (Eds.), SAGE Handbook of Graduate Employability. Sage.
12. Ibid.
13. Law, B and Watts, AG (2003) The DOTS Analysis Original Version. The Career Learning Network, Cambridge. Available online.
14. Truyens, M (2019), DOTS Model, Career Marcr. Available online.
15. Where are you right now? Using careers registration to support employability in higher education - HEA Surveys Conference 2017, AdvanceHE.
16. Starting points and journeys, University of Huddersfield, 2021.
17. Truyens, M (2019), DOTS Model, Career Marcr. Available online.
18. Plant, P (2014) Beyond DOTS: Theory and Model Development, Journal of the National Institute of Career Education and Counselling, Issue 33, October 2014 pp 44-48
19. Careers Registration: Insights for employability, The Careers Group, University of London
20. Where are you on your career journey?, King's Careers and Employability.
21. University College Dublin Careers Network.
22. How career ready are you?, University of Melbourne Careers Service.
23. Career Planning, University of Exeter Career Zone.
24. Gilworth R (2022) Careers and Employability in a data-rich environment in Broadley, Y. Cai, M. Firth, E. Hunt, & J. Neugebauer (Eds.), SAGE Handbook of Graduate Employability. Sage.