Artificial intelligence literacy, lifelong learning, and fear of innovation: Identification of profiles and relationships

Abstract The study aims to identify the profiles of university students regarding Artificial Intelligence Literacy, Lifelong Learning, and Fear of Innovation using cluster analysis and to examine the relationships among these variables. Cluster analysis and structural equation modeling were conducted with valid responses from 402 university students. The cluster analysis identified three distinct student profiles: the highly adaptive group (Profile 1), the needs improvement group (Profile 2), and the high support required group (Profile 3). Structural equation modeling revealed that artificial intelligence literacy positively affects the tendency for lifelong learning and negatively impacts the fear of innovation. Lifelong Learning Trends also negatively influences the fear of innovation. Furthermore, artificial intelligence literacy was found to indirectly reduce fear of innovation through lifelong learning tendencies. The findings from cluster analysis and structural equation modeling provide significant insights into understanding university students’ artificial intelligence literacy, lifelong learning tendencies, and fear of innovation. Developing customized education and support programs tailored to each profile’s characteristics and the relationships among the study variables can help students enhance their competencies in these areas.

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Publication Details

Journal
Education and Information Technologies
Published
2025-04-22
DOI
https://doi.org/10.1007/s10639-025-13548-y
Citations
17
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
55.18

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article

Artificial intelligence literacy, lifelong learning, and fear of innovation: Identification of profiles and relationships

Ebru Polat
17 citations
Education and Information Technologies
Engineering Education and Technology
55.18
article

Artificial intelligence literacy, lifelong learning, and fear of innovation: Identification of profiles and relationships

Ebru Polat
article en
17 citations

Abstract

Abstract The study aims to identify the profiles of university students regarding Artificial Intelligence Literacy, Lifelong Learning, and Fear of Innovation using cluster analysis and to examine the relationships among these variables. Cluster analysis and structural equation modeling were conducted with valid responses from 402 university students. The cluster analysis identified three distinct student profiles: the highly adaptive group (Profile 1), the needs improvement group (Profile 2), and the high support required group (Profile 3). Structural equation modeling revealed that artificial intelligence literacy positively affects the tendency for lifelong learning and negatively impacts the fear of innovation. Lifelong Learning Trends also negatively influences the fear of innovation. Furthermore, artificial intelligence literacy was found to indirectly reduce fear of innovation through lifelong learning tendencies. The findings from cluster analysis and structural equation modeling provide significant insights into understanding university students’ artificial intelligence literacy, lifelong learning tendencies, and fear of innovation. Developing customized education and support programs tailored to each profile’s characteristics and the relationships among the study variables can help students enhance their competencies in these areas.

Education and Information TechnologiesVol. 30(14)
Mustafa Kemal University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 0%
Engineering Education and Technology
55.18
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