Measuring Socio‐Ethical Engagement with Generative AI: Scale Development via Exploratory Factor Analysis
Title
Measuring Socio‐Ethical Engagement with Generative AI: Scale Development via Exploratory Factor Analysis
Creator
Kong, Elaine; Dilinika, JM Shalani; Nie, Xuan; Gautam, Aakash; Huang, Kuo‐Ting
Source
Proceedings of the Association for Information Science and Technology
Date
2025-10-16
Language
eng
Type
Conference Proceeding
Identifier
https://doi.org/10.1002/pra2.1325
Abstract
As the use of generative artificial intelligence (GenAI) systems grows in daily life, there is a need to assess how users interact with these tools in socially and ethically informed ways. This study introduces a multidimensional scale to measure socio-ethical AI engagement competencies, reflecting users' ability to evaluate, interpret, and ethically use AI-generated content, and to critically consider its broader social impacts and power dynamics. Drawing from interdisciplinary frameworks in AI literacy, self-efficacy, and AI ethics, we constructed an initial item pool related to social and ethical engagement.
Responses from 200 participants to an 18-item instrument were analyzed using Exploratory Factor Analysis (EFA) to capture four dimensions: critical appraisal, critical comprehension, ethical behavior, and anthropomorphic interaction. The scale demonstrated strong internal consistency. This work contributes to a theoretically grounded and empirically supported instrument for assessing critical and ethical engagement with GenAI, which has implications for AI literacy, responsible technology use, and curriculum design.
Responses from 200 participants to an 18-item instrument were analyzed using Exploratory Factor Analysis (EFA) to capture four dimensions: critical appraisal, critical comprehension, ethical behavior, and anthropomorphic interaction. The scale demonstrated strong internal consistency. This work contributes to a theoretically grounded and empirically supported instrument for assessing critical and ethical engagement with GenAI, which has implications for AI literacy, responsible technology use, and curriculum design.
Date Issued
2025
Bibliographic Citation
Kong, E., Dilinika, J.M.S., Nie, X., Gautam, A. and Huang, K.-T. (2025), Measuring Socio-Ethical Engagement with Generative AI: Scale Development via Exploratory Factor Analysis. Proceedings of the Association for Information Science and Technology, 62: 978-983. https://doi.org/10.1002/pra2.1325
Position: 1059 (50 views)
Citation
Elaine Kong, “Measuring Socio‐Ethical Engagement with Generative AI: Scale Development via Exploratory Factor Analysis,” CALASYS - CALA Academic Resources & Repository System, accessed April 16, 2026, https://ir.cala-web.org/items/show/1499.