ERIC Number: EJ1478691
Record Type: Journal
Publication Date: 2025-Dec
Pages: 18
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-2365-7464
Available Date: 2025-07-30
Decision-Making Efficiency with Aided Information: The Impact of Automation Reliability and Task Difficulty
Hanshu Zhang1,2; Ran Zhou3; Cheng-You Cheng4; Sheng-Hsu Huang4; Ming-Hui Cheng4; Cheng-Ta Yang4,5
Cognitive Research: Principles and Implications, v10 Article 44 2025
Although it is commonly believed that automation aids human decision-making, conflicting evidence raises questions about whether individuals would gain greater advantages from automation in difficult tasks. Our study examines the combined influence of task difficulty and automation reliability on aided decision-making. We assessed decision efficiency by employing the single-target self-terminating (STST) capacity coefficient in Systems Factorial Technology, estimating the ratio of performance with aided information to that without it. Participants were instructed to perform a shape categorization task, wherein they assessed whether the presented stimulus belonged to one category or another. In Experiment 1, three automation reliability conditions (high reliability, low reliability, and unaided) were tested in separate blocks. Our results indicated that, in general, participants exhibited unlimited capacity when provided with valid automated cues, implying that the decision efficiency was unaltered by automated assistance. Despite the failure to gain extra efficiency, the benefits of automated aids in decision-making for difficult tasks were evident. In Experiment 2, various types of automation reliability were randomly intermixed. In this scenario, the impact of automation reliability on participants' performance diminished; however, the significance of information accuracy increased. Our study illustrates how the presentation of automation, its reliability, and task difficulty interactively influence participants' processing of automated information for decision-making. Our study may improve processing efficiency in automated systems, hence facilitating superior interface design and automation execution.
Descriptors: Task Analysis, Difficulty Level, Decision Making, Automation, Reliability, Cues, Classification, Validity, Accuracy, Cognitive Processes, Computer Software
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: 1Ministry of Education, Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Wuhan, China; 2Central China Normal University, Key Laboratory of Human Development and Mental Health of Hubei Province, School of Psychology, Wuhan, China; 3South China Normal University, School of Psychology, Guangzhou, China; 4National Cheng Kung University, Department of Psychology, Tainan City, Taiwan; 5Taipei Medical University, Department of Education and Humanities in Medicine, Taipei, Taiwan

Peer reviewed
Direct link
