Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior
By Yu-Yin Wang, Yi-Shun Wang. Interactive Learning Environments, 2019
561 citations recorded by the source corpus.
ABSTRACT While increasing productivity and economic growth, the application of artificial intelligence (AI) may ultimately require millions of people around the world to change careers or improve their skills. These disruptive effects contribute to the general public anxiety toward AI development. Despite the rising levels of AI anxiety (AIA) in recent decades, no AI anxiety scale (AIAS) has been developed. Given the limited utility of existing self-report instruments in measuring AIA, the aim of this paper is to develop a standardized tool to measure this phenomenon. Specifically, this paper introduces and defines the construct of AIA, develops a generic AIAS, and discusses the theoretical and practical applications of the instrument. The procedures used to conceptualize the survey, create the measurement items, collect data, and validate the multi-item scale are described. By analyzing data obtained from a sample of 301 respondents, the reliability, criterion-related validity, content validity, discriminant validity, convergent validity, and nomological validity of the constructs and relationships are fully examined. Overall, this empirically validated instrument advances scholarly knowledge regarding AIA and its associated behaviors.
Subfields: Demography, Gender Studies, Social Psychology
View Paper: https://www.semanticscholar.org/paper/b94149cec27cf046bf7de4353cdbad67168a3d5c
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In Demography
In Gender Studies
In Social Psychology
- Thomas K. F. Chiu
- Cynthia Lynn Breazeal
- Paul Rodway
- Astrid Schepman
- Ching Sing Chai
- Kerstin Dautenhahn
- Brian Scassellati
- Alex S Taylor
Citations in the corpus
- Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study (2022, methodology): “These survey questions are 5-Lik-ert scale questions drawn and modified from validated instruments of the Science Motivation Questionnaire II (Glynn et al., 2011), the Modified Attitudes Towards Science Inventory (Weinburgh & Steele, 2000), and the AI anxiety scale (Wang & Wang, 2019).”
- The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence (2022, methodology): “AI configuration anxiety means fear of humanoid AI (Wang & Wang, 2022).”
- Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-Determination Theory Perspective (2020, background): “As machine learning becomes more powerful and narrow AI are performing more jobs, AI technologies and products are replacing jobs such as cashiers and proofreaders [17].”