Driven by mechanisation, traditional career pathways in forestry crews are evolving. As part of the Primary Growth Partnership (PGP) programme, ‘Te Mahi Ngahere i te Ao Hurihuri – Forestry Work in the Modern Age’, the Scion Human Factors research group is exploring ways to reshape these pathways to empower operators in their learning process and bolster well-being.
Video-based feedback can help improve operator performance by offering specific, timely, and content-rich instruction. To demonstrate this, experienced loader operators used video to identify beneficial work practices in various loading processes and these practices were structured into a performance framework. The importance of operator skill in enhancing productivity, safety, and overall efficiency of skid site activities was highlighted by the framework, as was the need for efficient, controlled machine movements.
Now we are looking to test the performance framework in combination with video feedback to improve loader operator skills within the normal operations of a crew. To do that, we would like to work with a loader operator who believes they have room to improve their skills, is willing to give the system a try and give us feedback on how useful it was.
We will use a sports video analysis app to stream footage of them loading trucks to their phone. They will be given feedback on their loading from two sources:
The performance framework for loading operations that can be used to target areas of improvement; and
Footage of a very accomplished loading operator that can be used as a comparison within the app.
They will need:
To be a full-time loader operator (tracked rather than wheeled).
Access to a smartphone.
A crew boss / foreman willing to capture footage of them loading at least one truck per week for four weeks.
To review that video footage and respond to the feedback.
A couple of hours at the start getting set up to review footage and to run through the process.
An hour at the end of the process to review their experience of learning using video as a feedback tool.
If you are interested, text Trevor Best (Researcher) on (+64) 27 432 3155.
