evaluating the impact of virtual reality-based training on workers' competences in the mining...

Evaluating the impact of

Virtual Reality-based training

on worker’s competences in the

mining industry

Shiva Pedram

Pascal Perez

Stephen Palmisano

September 2014

THE ISSUE

?

Training Safety

Actual Training Needs

Constraints of Real world

Training

VR Capabilities

VR Utilisation

FRAMEWORK

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

METHODOLOGYPast 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

ANALYSIS

Training

Competition

Study Period

BrigadeIndividual

Characteristics &

History

Performance(Competition)

Competence(Training)

Hidden Markov Model (HMM)

METHODOLOGY

Woonona Newcastle Lithgow Singleton

Mines 7 7 6 6

Brigades 156 144 115 139

Sessions50

(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.

Preliminary Results

Overall, useful and successful training sessions….

Preliminary Results

…Regardless of the degree of consistency with reality!

Action Research

Addressing the lack of task allocation and coordination

RESEARCH OUTCOMES

Outcome 1 – Better TrainingThis 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 TechnologyThis 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 PeopleThis 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.

Shiva Pedram spedram@uow.edu.auPascal Perez pascal_perez@uow.edu.auStephen Palmisano stephenp@uow.edu.au