A presentation by SMART Infrastructure Facility Research Director Dr Pascal Perez to the 11th International Multidisciplinary Modeling and Simulation Multiconference (I3M), Bordeaux, September 2014.

1. Evaluating the impact of
Virtual Reality-based training
on worker’s competences in the
mining industry
Shiva Pedram
Pascal Perez
Stephen Palmisano
September 2014

2. THE ISSUE
?
Training Safety

3. Actual Training
Needs
Constraints of
Real world
Training
VR
Capabilities
VR Utilisation
FRAMEWORK

4. METHODOLOGY
Factors Interview with Aim
Actual Training Needs
• Subject matter experts (SMEs),
such as team supervisors and
mine managers
• Identifying human mistakes in
mining environments,
• Identifying potential training
needs.
Real-World Constraints
• Subject matter experts (SMEs),
such as team supervisors and
mine managers
• Constraints associated with
real-world training,
• Potential for VR-based training
to overcome these limitations.
VR-based Training Capabilities
• VR designers and trainers • Current VR capabilities and
limitations,
• Potential upgrading for VR to
become more relevant.
VR-based Training Utilisation
• Rescue brigades (trainees) and
trainers
• Expectations and responses to
VR environments,
• Self-assessment of individual
performance

5. METHODOLOGY
Past Current
Training
Sessions
 Analysing previous records and data
 Interviewing past trainees & trainers
 Interviewing VR designers
 Attending training sessions
 Interviewing and observing trainees
 Interviewing and observing trainers
Mining
Management
 Analysing industry assessment reports
 Interviewing technical management
 Interviewing senior management
 Interviewing technical management
 Interviewing senior management
Pre-training Questionnaire
• Professional experience
•Gaming experience
• Individual characteristics (age, motion sickness, anxiety…)
• Expectations from training session
Post-training Questionnaire
• Engagement
• Reality/Presence
• Interest/Enjoyment
• Pressure/stress
• Distraction
• Simulator Sickness
• Perceived Competence
Assessing Training Effectiveness

6. ANALYSIS
Study Period
Competition
Training
Individual Brigade
Characteristics
&
History
Performance
(Competition)
Competence
(Training)
Hidden Markov Model (HMM)

7. METHODOLOGY
Woonona Newcastle Lithgow Singleton
Mines 7 7 6 6
Brigades 156 144 115 139
Sessions
50
(25 with VR)
50 (?) 30 (?) 40(?)
Technical support from Mines Rescue Services to access training sessions
and records, as well as facilitating contacts with mine managers.
Financial support from the Health & Safety Trust to undertake the study
across 4 training facilities.

8. Preliminary Results
Overall, useful and successful training sessions….

9. Preliminary Results
…Regardless of the degree of consistency with reality!

10. Action Research
Addressing the lack of task allocation and coordination

11. RESEARCH OUTCOMES
Outcome 1 – Better Training
This study will estimate expected and actual training transfer capacity associated with
IVR technology and identify the most efficient training sequences. This will help Mines
Rescue to develop better tailored training programs for existing and future rescue
brigades.
Outcome 2 – Better Technology
This study will provide a better understanding of the gaps between training challenges
and simulation capabilities. This study will demonstrate Mines Rescue’s dedication to
upmost quality control of its procedures and outcomes. The findings will also provide
evidence for investment decisions on training and simulation capacity.
Outcome 3 – Better People
This study will provide quantitative evidence of the improved competences of rescue
brigades over time. Finally, the study will provide ample material for Mines Rescue
and the coal mining industry to celebrate all the brave individuals who volunteer to
the Rescue Brigades and give their time to maintain and improve their competences.

12. Shiva Pedram spedram@uow.edu.au
Pascal Perez pascal_perez@uow.edu.au
Stephen Palmisano stephenp@uow.edu.au