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In many work domains, the push toward higher levels of automation raises the concern of diminishing human expertise. Ecological interfaces could help operators in retaining and potentially even in acquiring expertise as they are hypothesized to lead to a deeper understanding of the work domain. This study explores the short-term impact of ecological interfaces on knowledge development and compares the results with an instruction-based training method. To monitor and compare students' progress, their decision-making strategies, identified from verbal comments recorded in 'think-aloud' simulator sessions, are mapped onto the decision ladder. This method has been applied to an experiment (N=16) aimed at training novices in conflict detection and resolution (CD&R) within a simplified air traffic control context. Results show that the overall CD&R performance in the final measurement sessions, featuring a transfer manipulation, was not significantly different between the 'ecological' and 'instructional' groups. In terms of cognitive behavior, however, students in the ecological group exhibited more laborious rule- and knowledge-based behaviors that sparked goal-oriented thoughts and corresponding control performances beyond the CD&R task. These findings indicate that ecological interfaces can change how people think and approach a control problem, even after removing the support. It is therefore reasonable to believe that ecological interfaces can play an important role in the early stages of deep knowledge development.

Original languageEnglish
Article number8735791
Pages (from-to)623-632
Number of pages10
JournalIEEE Transactions on Human-Machine Systems
Volume49
Issue number6
DOIs
Publication statusPublished - 1 Dec 2019

    Research areas

  • Air traffic control (ATC), ecological interface design (EID), human-machine interface, training

ID: 67890754