Human performance in a multiple-task environment: effects of automation reliability on visual attention allocation.

Diagnostic automation has been posited to alleviate the high demands of multiple-task environments; however, mixed effects have been found pertaining to performance aid success. To better understand these effects, attention allocation must be studied directly. We developed a multiple-task environment to study the effects of automation on visual attention. Participants interacted with a system providing varying levels of automation and automation reliability and then were transferred to a system with no support. Attention allocation was measured by tracking the number of times each task was viewed. We found that participants receiving automation allocated their time according to the task frequency and that tasks that benefited most from automation were most harmed when it was removed. The results suggest that the degree to which automation affects multiple-task performance is dependent on the relative attributes of the tasks involved. Moreover, there is an inverse relationship between support and cost when automation fails.

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.

The Persistence of Content Knowledge.

Research has shown that changes in the way a website works or how it is laid out affects how well people are able to use that website. This study examined how changes in the content and procedures of a website-like system affect the way people recover from not being able to find information in that system. Participants were placed in one of four learning conditions, differing by the content and procedures taught for a simple website-like system. They were then tasked with finding certain pages in that system or systems with different procedures, content, or both. The first test (System B Online Test) showed that participants who had to learn new content were less efficient at finding that content, while participants who had to learn new content and procedures were the only ones slowed down. The second test (System C Online Test) showed that participants who had experienced a previous change in content responded to the new change faster, whereas people who started with inconsistent procedures (as compared to consistent) made fewer errors towards the end.