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“Most continuing learning takes place informally in workplaces. Employer-provided training has a greater marginal effect on workers’ continuing skill development” 

Cedefop (2018)

Are we failing to provide continuing development that is engaging? personalised? and actually needed?

Although the concept of learning in the workplace is not new, we need to reflect on how effectively we utilise the affordances offered in workplaces, to promote lifelong learning, and to consider the important role of learning in the workplace, blurring the lines between working and learning. Lave (1993) cited in Jackson (2010) concluded that,

“wherever you encounter practice you also identify learning”.

The phenomenon of “work-based learning” has been gaining support internationally, offering advantages including the connection between school and work (Stasz and Brewer, 1998), the reduction in time and cost of preservice training (Cappeli,; Shapiro and Shumanis, 1998) and support for a productive economy Mumford, J. and Roodhouse, G. (2016).

Should we now be placing a focus on “learning based work” and establishing the success criteria for successful integration? 

Learning Based Work (LBW)

Learning based work would offer numerous advantages to all ages and sectors of workers, from graduates to leadership and executive.

40% of fresh graduates cited learning opportunities as a priority in their employment search, following benefits and work-life balance. If we do not provide, nor demonstrate the value of learning opportunities in our workplaces, we could be missing out on 40% of applicants – from the graduate level alone.

We are missing a valuable opportunity to support lifelong learning, and in fact to attract some of the best and brightest during recruitment.

According to the Foundation for Young Australians (FYA), 

“When a person trains or works in 1 job, they acquire skills for 13 other jobs, on average”.

Foundation for Young Australians (FYA), (2016)

How do we ensure that they bring with them the recognition of the learning and experience they have acquired? But more importantly, how do we prepare them for ‘next’ – which ever of those 13 jobs they wish to pursue, particularly if it includes an extension of, or varying skills to their current role? (FYA, 2017)

Some of the recommendations from FYA (2015) include promoting entrepreneurship as a viable career option, developing enterprise skills, problem solving, creativity and social intelligence, and supporting employment focused and innovation focused entrepreneurship. The development of these skills and attributes is not just relevant for the younger members of our workforce but also for those whose industries are or will become irrelevant in their future work or for their success and happiness as members of society.

Digital literacy is key, the FYA (2015) analysis shows that

“more than 90% of Australia’s current workforce will need to be at least a digital citizen to perform their roles in a digitally enabled economy. More interestingly, approximately 60% of the workforce will ideally be operating at a digital worker level or above.”

FYA, (2015)

These skills and attributes may or may not be considered relevant in current roles, but by providing these learning opportunities, we not only protect current employees but also provide additional opportunities to prepare them for the future of their role and other roles in similar or emerging industries.

Like graduates and experienced workers, digital literacy is a necessary skill for the unemployed and underemployed, whether short or long term. Learning and development needs to address the specific needs of these groups, both as learning opportunities and as work-based learning, opening new avenues and providing opportunities to adapt their existing or newly acquired skills.

What would best practice look like?

Lave (1993) “posits that there is no separation between engaging in work activities and learning as the two are interdependent.“ 

from Billett, Fenwick and Somerville (2006)

Best practice in learning-based work would reflect current and emerging pedagogical practice, whilst adopting the affordances of technology, aligning, and adapting to current and future employers, informed by evidence. This could include PBL (Problem / project-based learning) or IBL (Inquiry based learning).

Best practice would encompass the following:

Every organisation would employ or have access to a Chief Learning Officer (CLO)​

Like other members of the executive or C-suite, learning would be evident as a key goal and strategic direction for the organisation. The learning and development of all staff would be assessed as an outcome for the organisation and decision making and funding allocation would reflect the prioritisation of learning and development. Offerings would be shaped through collaborations of pedagogical expertise, technology, HR and other groups as required e.g. cybersecurity. 

eLearning ecosystems will be defined and evaluated as part of the organisation 

“New technologies and ways of working are providing unprecedented flexibility in how and where people work, which is one of the key drivers of worker happiness.” 

FYA (2017)

Learners would have choice on how they engage in their learning, across the physical, virtual, and social elements making up their learning environment. This will include learning supported by digital affordances that include more than just an LMS (Learning Management System). Learning will be engaging, experiential, reflecting the real-world context, and relevant, accessed ubiquitously, including opportunities to demonstrate or create and share artefacts from their learning. The eLearning ecosystem will include ePortfolios, academic integrity tools, AR / VR or MR, AI, analytics tools, or others, as required throughout the learner journey. These in turn will be linked to other systems including evaluation, peer review, etc.

Importantly, this assumes a level of digital literacy, media literacy, and information literacy, which may need to be developed.

Personalisation, choice, and flexibility would be key in learning provision

 Learning experiences and learning journeys would be personalised, informed by previous learning, current requirements, and future aspirations of the organisation and the individual. Assessment or artefacts would provide evidence of their improvement. Learners would have flexibility in how and when they engage in learning, assessment, and demonstration of the learning outcomes. This approach would eradiate approaches that promote different entitlements to learning opportunities across different stages of careers or in hierarchies.

Assessment and accreditation would be redefined as more than ‘tests’

 To ensure engaging learning experiences across a lifelong learning journey, we need a balance of summative, formative assessment, and diagnostic assessment. The data collated from this assessment, whether it be educator/trainer-led, peer, or self-assessment, would then be utilised iteratively to determine improvement, and inform current and future learning requirements. The recommendations would then be balanced with learner and organisation aspirations.

Through the digital tools available, artefacts and evidence of learning would reduce duplication of learning, except when required (as an update or to reinforce). Current and future in-demand skills will be identified, assessed and developed, informed by the data available, for example, does the number of attempts before giving up or succeeding represent resilience or courage through attempting more difficult or adventurous tasks?

Feedback and evaluation identify weaknesses, as well as strengths and areas for opportunities linked to aspirations, or to share best practice or exemplars. This feedback would include assessments that balance on the job (practical or experiential) assessment, tasks requiring immediate or timely feedback, and tasks that require human interaction for verbal or written feedback.

Micro credentialing would be supported across industries and would embrace both industry-specific learning as well as general skills identified as necessary for the future, with recognition of prior formal and informal learning, in line with compliance and flexible accreditation processes.

An eLearning ecosystem would include software, apps, etc with assessment capabilities and/or dedicated assessment tools, with elements including more than test-based methodologies. The selection of these tools will follow criteria similar to the criteria recommended in the context of educational institutions.

Balancing skills and knowledge, specialist and general, local and global

Learning would encompass a balance of general skills (e.g. digital literacy, entrepreneurial and innovative thinking, problem-solving, collaboration…) as identified by industry, as well as industry-specific for existing and emerging industries. This would ensure the readiness of skills as traditional organisations and industries are replaced by more technological and carer-based industries – future-proofing employees. This would recognise and scale best practice, whilst addressing needs within sector and across sectors, nationally and internationally.

Design and consider workspace as learning space

“the workplace is viewed as a pivotal site for the construction and sharing of knowledge.” Billett, Fenwick, and Somerville (2006).

FYA (2017)

To realise the opportunity of “learning-based work” we need to reimagine workplaces and workspaces as learning space. The affordances of these spaces, along with a rethink on continuous development in the workplace will ensure engaging learning experiences and reflect best practice to ensure effectiveness and efficiency. This should be applied from the design of space, transitioning, occupancy, and post-occupancy evaluation – starting with the activities that will take place and designing the physical, virtual, and social space to support this.

Partner with learners, universities, learning providers and industry regulators

Learning-based workplaces will reflect best practice informed by previous, current, and ongoing research and evaluation. Collaborations across universities, learning providers, and industry will ensure co-creation and co-ownership of the requirements for, and provision of, learning and assessment.

These partnerships will promote innovative thinking, with a focus on the future for employees and leaders, not just from the perspective of the organisation, but all stakeholders – individually and collectively. The co-creation and sharing of learning opportunities will further support differentiated learning opportunities to meet the needs of the collective, and of specific learners, aligned to their interests, experiences, goals, weaknesses, and strengths.

These partnerships necessitate consideration of and inclusion of learners, providing an opportunity for engaging the subject matter expert in all of us, utilising this expertise to co-create learning or crowdsource content or learning experiences, providing real-world demonstration and application of learning.

The expertise of pedagogical experts, from schools, universities, or other educational providers will ensure we embrace pedagogical best practice from the education sector and from research.

Collaborative thinking creates an opportunity to reimagine engagement in learning. Utilising established frameworks from K-12, vocational, tertiary, and adult education will provide valuable frameworks to increase learner engagement, creating an ongoing passion for learning. The Rigor relevance framework and Gilly Salmon’s Five Stage Model, for example, provide an opportunity to verify and improve engagement, rather than considering attendance as an indicator of engagement.

In an online context, there is a vast amount of data that should also be utilised to determine engagement and provide feedback to tutors, assessors, coordinators, and leadership. This can include surveys, length of time engaged in videos and other activities, access (quantity, quality, and choice), attempts at activities (successful and unsuccessful), how learners choose to engage in learning, tools and time for collaboration, and the effect these have on learning improvement.

With consideration of these aspects, how prepared is your organisation to become a learning-based workplace, preparing your teams for success now and into their future as well as the organisations?


Kathleen Donohoe is the Director and Founder of Leading Thinking International. She supports school and industry to reimagine learning experiences across physical, virtual and social learning space, bringing national and international teaching, academic, research and executive experience. She is an Honorary Research Fellow at the University of Melbourne, MGSE, with the ILETC Project. Kathleen has vast experience developing and implementing strategy for transformation, curriculum renewal, and physical virtual and social learning space, including as Director, Futures Learning at NSW Department of Education.


Billett, Fenwick and Somerville (2006) cited Lave (1993). Work, Subjectivity and Learning: Understanding Learning through Working Life edited by Stephen Billett, Tara Fenwick, Margaret Somerville

Cappeli, Shapiro and Shumanis (1998). “Employer Participation in School-to-Work Programs”. Annals of the American Academy of Political and Social Science. 559 (1): 113.

CEDEFOP (2018) Insights into skill shortages and skill mismatch. Learning from Cedefop’s European skills and jobs survey. Cedefop Reference series 106. Luxembourg: Publications Office of the European Union, 2018

FYA (2015) The new work order. Last retrieved June 29, 2020 from

FYA (2017) The new work Mindset, 7 new job clusters to help young people navigate the new work order. Last retrieved June 29, 2020 from

Jackson 2010 cited Lave (1993) from Innovations in Lifelong Learning: Critical Perspectives on Diversity, Participation and Vocational Learning

Mumford, J. and Roodhouse, G. (2016). Understanding work-based learning / edited by John Mumford and Simon Roodhouse

Stasz and Brewer (1998) C”Work-Based Learning: Student Perspectives on Quality and Links to School”. Educational Evaluation and Policy Analysis. 20 (1): 31–46.

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