Pivoting university course offerings to upskill the workforce

Teresa Ironside outlines how universities can develop their course portfolio to meet changing workplace skills demands and deliver education to a wider range of learners

Teresa Ironside's avatar
25 Feb 2022
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Advice on developing a course portfolio that meets workplace demand for upskilling

Created in partnership with

Created in partnership with

University of Edinburgh

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There is a growing demand for university courses that help working adults upskill or reskill and aid their professional development. In response, the University of Edinburgh has focused on developing courses in areas such as data skills. The data skills portfolio can benefit anyone from employees looking to gain knowledge in order to advance their careers to those who are at risk of redundancy or are unemployed and need to reskill.

Reflecting on how course content is delivered to make it accessible to diverse learners – and learning from successful courses across the university – we have grown our course offering to deliver high-quality training for working professionals. Here is some advice based on what we have learned so far:

Creating a focal point for your portfolio

Economic drivers should be a key focus, many of which have been heightened over the past two years of the pandemic. Look at where key funding initiatives are being directed. Our initial review of course content potentially available to working professionals was in response to Scottish government and Scottish Funding Council funding schemes such as the Upskilling Fund and National Transition Training Fund, which support eligible learners through higher education short courses.

Review your strengths as a university to identify areas of professional development where you can quickly add the most value. This process led to our focus on data skills training across a range of subject areas, where data can be used at various levels within organisations. Having a clear focus helped us deliver education over a short time period to a wider audience and meet growing government expectations.

Pivoting course delivery and content

Consider how you can expand on and adapt delivery modes and materials used on existing undergraduate and postgraduate courses in order to meet the needs of a broader set of learners.

We reviewed where material could be used in shorter segments within short courses or workshops. We also made existing courses, or modules as they are known elsewhere, available not just to those studying full-time programmes, but also to those who wish to study a single course, or module, from a programme. This helped us grow our portfolio from five courses in the first year in 2020 to nearly 50 in 2022.

Tailoring courses to be more applicable to working professionals where relevant, by welcoming industry input and former students’ feedback, or by providing additional case studies for real-world applicability, benefits both the traditional and working professional cohorts of students.

Developing a range of course styles

Develop different course styles, structures and lengths across your professional skills portfolio to widen participation and access and provide an inclusive environment for those in work, at risk of redundancy or unemployed, all of whom will have different needs.

Using our existing online and hybrid course delivery methods, we developed:

1) Workshops: run over two to three days, with short, sharp skills-based training on specific topics
2) Masterclasses: run over an average of one week and often aimed at senior professionals
3) Short courses: run over two to five weeks and often non-credit-bearing continued professional development with optional assessment
4) Access to credit-bearing single courses from postgraduate programmes: normally run from five to 10 weeks including postgraduate-level assessment.

Workshops, masterclasses and short courses have been developed with working professionals in mind based on academic expertise and industry need. These courses give learners the skills and tools required to enhance their work through improved data skills and provide a potential route into longer-term postgraduate study.

The inclusion of credit-bearing courses from postgraduate programmes builds on longer-term efforts to make master’s-level courses available to wider audiences. We hope to encourage learners who might initially take one or two short courses to continue studying and potentially go on to achieve a master’s degree.

Applying lessons learned from the past two years

The shift to hybrid and online learning has enhanced accessibility of course content for working professionals. The mix of traditional master’s students with those in employment enriches opportunities for all students in the course cohort, through peer learning and the expansion of professional networks, creating plenty of opportunities for students to work together and get to know one another.

Employees who study while working can bring immediate benefits to their workplace, often generating a direct economic boost, so employers should be encouraged to support their staff to enrol on such courses. Those who are not employed can build their confidence and enhance their CVs to be ready for the next opportunity.

A key element to our success has been the external funding made available to support the development of these courses and subsidise fees to make education more accessible to a greater number of employees. Many working professionals would struggle to access these opportunities without this funding, and it gives those who are unemployed access to training, which can help them back on to the career ladder. This is why responding to where the funding is being channelled is so important.

By evaluating our course content to think about what the university offers from a broader standpoint, we have pivoted our delivery to develop shorter courses for working professionals, to widen access to credit-bearing courses and to enable learners to study while they work or reskill while unemployed.

Teresa Ironside is director of data science education at the University of Edinburgh’s Bayes Centre.

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