MouseTrace: a better mousetrap for catching decision processes.

Area of Science:

• Cognitive Science
• Decision Science
• Human-Computer Interaction

Background:

• Understanding decision-making processes is crucial in various fields.
• Existing tools like MouseLab have limitations in data recording and user-friendliness.
• There is a need for sophisticated software to capture detailed cognitive processes during decision tasks.

Purpose of the Study:

• To introduce MouseTrace, a novel computer program for monitoring decision-making processes.
• To enhance the capabilities of existing decision-monitoring software.
• To provide researchers with a more sophisticated tool for collecting detailed decision-making data.

Main Methods:

• Development of MouseTrace, a Windows-based extension of MouseLab.
• Presentation of complex choice information via an alternative-by-attribute matrix.
• Recording of detailed data including information examined, timing, and sequence of access.

Main Results:

• MouseTrace accommodates significantly more information than previous programs.
• The program allows for multiple responses and decision stages.
• It offers enhanced usability for both subjects and experimenters.
• Detailed cognitive process measures (search depth, sequence, content) can be derived from recorded data.

Conclusions:

• MouseTrace provides unique insights into decision-making theory.
• The software facilitates the study of individual differences in decision-making.
• It enables sophisticated analysis of various decision variables through detailed process tracing.