EAIT–HASS Interdisciplinary Research
Workforce Agility Across High-Risk Industries
Developing a learning framework to support adaptive, boundary-crossing workforce development
The Challenge
Australia's mining and critical minerals industries are facing accelerating change—driven by digital transformation, automation, decarbonisation, and global supply pressures.
Workers increasingly need to apply knowledge across contexts and navigate shifting boundaries between human and machine systems. Yet existing training models often focus on job-specific competencies, overlooking the broader systems, relationships, and artefacts that enable workforce learning and adaptation.
This project addresses a critical gap: how can learning, training, and professional development support workforce agility across organisational and industry boundaries?
Research Team
Objectives
Synthesise Evidence
Review workplace learning, boundary crossing, and Science of Learning literature to identify mechanisms that enable learning and capability transfer.
Develop Framework
Create a systems-based framework integrating individual, social, organisational, and industry dimensions—including human–machine systems.
Validate with Industry
Refine the framework through consultation with experts across mining, defence, and advanced manufacturing sectors.
Deliver Practical Outputs
Produce a visual model and guiding principles to inform workforce learning design, training policy, and professional development.
Building on Existing Collaboration
This project builds on 18 months of collaboration between the UQ Learning Lab (HASS Faculty) and the Faculty of EAIT, drawing on insights from the Science of Learning and from cognitive, social, and workplace learning theories. It extends our previous research on quality training and learning in the mining industry, published in Vocations and Learning (2024).
Methodology
Scoping & Synthesis
Review academic and industry literature to identify mechanisms and conditions that support learning and capability agility across organisational and industry boundaries.
Key Activities
- Systematic review of workplace learning literature
- Analysis of boundary-crossing and transfer research
- Synthesis of Science of Learning principles relevant to workforce contexts
Framework Development
Synthesise insights using conceptual framework analysis to map relationships between learners, technologies, and systems that enable adaptive, boundary-crossing learning and workplace practice.
Key Activities
- Conceptual framework analysis and mapping
- Integration of individual, social, and organisational dimensions
- Consideration of human–machine learning interfaces
Collaborative Refinement
Engage academic and industry partners through targeted workshops to test and refine the framework, producing guiding principles and a visual model for practical application.
Key Activities
- Stakeholder workshops with cross-sector experts
- Framework validation and refinement
- Development of visual model and guiding principles
Expected Outcomes
The project will deliver an evidence-informed conceptual framework that articulates how learning, training, and continuing professional development can support workforce agility across high-risk industries.
Conceptual Framework
Systems-based model integrating individual, social, and organisational learning dimensions
Guiding Principles
Actionable principles for designing adaptive workforce learning programs
Visual Model
Accessible representation for industry and policy stakeholders