Design and Psychometric Evaluation of the Artificial Intelligence Acceptance and Usage in Research Creativity Scale Among Faculty Members: Insights From the Network Analysis Perspective DOI Open Access
Ayoub Hamdan Al‐Rousan, Mohammad Nayef Ayasrah,

Saadiah Yahya

et al.

European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)

Published: Jan. 27, 2025

ABSTRACT The acceptance of artificial intelligence (AI) in academic settings, particularly the context research creativity, is a growing area interest. This study aimed to design and validate AI Acceptance Research Creativity Scale (AIA&RCS) among faculty members. exploratory mixed‐method was conducted 720 A literature review participant interviews were qualitative phase generate develop items. In quantitative phase, face validity, content construct convergent validity reliability (internal consistency stability) used. Exploratory factor analysis (EFA) indicated 4‐factor model scale with ‘perceived usefulness effectiveness creativity’, ‘ethical issues research’, ‘trusted capabilities’ ‘willingness use AI’ accounting for 51.6% variance. arrangement verified by confirmatory (CFA), fit indices that at suitable levels. Then, network took into account four‐factor structure AIA&RCS further. Similarly, graph (EGA) configuration AIA&RCS. 25‐item well‐suited measuring innovation because its psychometrics.

Language: Английский

Design and Psychometric Evaluation of the Artificial Intelligence Acceptance and Usage in Research Creativity Scale Among Faculty Members: Insights From the Network Analysis Perspective DOI Open Access
Ayoub Hamdan Al‐Rousan, Mohammad Nayef Ayasrah,

Saadiah Yahya

et al.

European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)

Published: Jan. 27, 2025

ABSTRACT The acceptance of artificial intelligence (AI) in academic settings, particularly the context research creativity, is a growing area interest. This study aimed to design and validate AI Acceptance Research Creativity Scale (AIA&RCS) among faculty members. exploratory mixed‐method was conducted 720 A literature review participant interviews were qualitative phase generate develop items. In quantitative phase, face validity, content construct convergent validity reliability (internal consistency stability) used. Exploratory factor analysis (EFA) indicated 4‐factor model scale with ‘perceived usefulness effectiveness creativity’, ‘ethical issues research’, ‘trusted capabilities’ ‘willingness use AI’ accounting for 51.6% variance. arrangement verified by confirmatory (CFA), fit indices that at suitable levels. Then, network took into account four‐factor structure AIA&RCS further. Similarly, graph (EGA) configuration AIA&RCS. 25‐item well‐suited measuring innovation because its psychometrics.

Language: Английский

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