The smooth (tractor) operator: Insights of knowledge engineering

The design of and training for complex systems requires in-depth understanding of task demands imposed on users. In this project, we used the knowledge engineering approach (Bowles et al., 2004) to assess the task of mowing in a citrus grove. Knowledge engineering is divided into four phases: (1) Establish goals. We defined specific goals based on the stakeholders involved. The main goal was to identify operator demands to support improvement of the system. (2) Create a working model of the system. We reviewed product literature, analyzed the system, and conducted expert interviews. (3) Extract knowledge. We interviewed tractor operators to understand their knowledge base. (4) Structure knowledge. We analyzed and organized operator knowledge to inform project goals. We categorized the information and developed diagrams to display the knowledge effectively. This project illustrates the benefits of knowledge engineering as a qualitative research method to inform technology design and training.

► Knowledge engineering provides insights into job demands for tractor operators.
► This study provides an in-depth example to illustrate how to implement knowledge engineering in a job context.
► Skilled operators rely on multi-modal cues to support dynamic decision making.
► The results provide guidance for training, product redesign, and future development.