KEY FINDINGS AND RECOMMENDATIONS

FROM THE DATA:

  • Industry needs digital capabilities relating to data and customer experience/ engagement – graduates need to be able to imagine, find, create and tell the story.
  • Industry roundtable dialogue initially saw ‘digital capabilities’ as functional use of tools, separate from the high-level capabilities needed. Over the five roundtables, dialogue increasingly focused on Perceptual and Adaptive digital capabilities.
  • Roles such as data detectives, narrative strategists and the ‘in-between’ translater/explainer require knowing enough about coding, business and communication; working with other specialists across disciplines; and ‘connecting the dots’ with imagination for developing ideas and solving new problems in new and emerging contexts.
  • No significant difference in job titles, or digital skills required in job advertisements, between Melbourne, Sydney, Brisbane for samples examined (Journalism, Engineering, Communication Design).

Moving forward:

  • Digital Affordance Developmental Learning Model aligns well with industry needs: Functional + Perceptual + Adaptive digital affordance/capability development.
  • The model addresses current gaps in graduate capability and is a good fit with the rapidly evolving world of work and data (artificial intelligence, machine learning, deep learning). Across industries, emphasise data analysis, coding, communicating using digital media, collaboration across disciplines, problem solving and basic mathematics.
  • Foster ‘connecting the dots’
    • Business: know enough about how organisations work, what their business objectives and imperatives are; and/or know enough to interact with business specialists
    • Coding and statistics: know enough to generate and analyse data; and/or know enough to interact with data scientists
    • Communication and design: know enough to visualise data, translate, explain and use storytelling to engage users/customers, or to support strategic decision making and complex problem solving; and/or know enough to interact with communication and design specialists
  • Contract work on the rise; may be more contract and online/collaborative work in Melbourne and possibly Sydney than in Brisbane – requires further research to validate.
  • Professional learning is a significant opportunity emanating from the research – adapting the learning model in industry (and universities) to address staff capability for the unknown future of technology impacts and potential.

FROM THE DATA:

  • Educators and students are more likely to think of ‘digital capabilities’ at the Functional (tools) level and to operate at this level; need to elevate Perceptual and Adaptive.
  • Assumptions may be made about Functional capability of students as ‘digital natives.’
  • Educators are more likely to be teaching digital capabilities than assessing them; or may assume digital capabilities are being covered ‘somewhere else’ in the program.
  • Software/tools are more likely to be addressed than key industry needs around data/AI, etc.

Moving forward:

  • Adaptive capability development as a differentiator for graduates must be supported by Functional and Perceptual knowledge, skills and experience; and is strengthened significantly by real-world complex projects for students (including virtual team projects) with industry partners. Know enough to imagine possibilities and to work with other specialists (technology, business, coding, statistics, communication, design). 
  • Educators like the learning model situating capability development in teaching practice on the ground in the disciplines, rather than being another high-level framework to be mapped.
  • Some early adopters, but most Educators asked for time, professional development and examples in translating the model to existing and new curriculum, especially for assessment.
  • The project website  https://sites.rmit.edu.au/digitalworkpractices/ includes the Learning Model and Student Pilots Report, together with guidelines for the Learning Model and a Resources section.

Key Recommendations

1. Pursue industry professional learning initiatives and produce nuanced jobs data

2. Confirm institutional senior leadership and cascaded support for model at universities

3. Plan professional development for Educators, with scale-up of the learning model and longer-term evaluation (learning outcomes + employment outcomes)

UTS Workshop.
Drawn by Rocco Fazzari and used with permission.