Seeking knowledge or efficiency: Profiling students’ AI-use through survey-based latent class analysis

The spread of easily accessible generative AI in the form of chatbots has impacted secondary education, but the effects of this are largely unknown. Previous studies have shown that using chatbots in a learning context can be both harmful or helpful depending on how they are used. While students are undoubtedly utilising this technology, there is scarce data on the extent, intention, or approach to its use, or what drives it. The present study builds upon the findings of a previous qualitative study, aiming to investigate and quantify students' use of generative AI for schoolwork. Through a survey sent to multiple upper secondary schools, we collected 1266 responses to analyse upper secondary students' attitudes toward, usage of, support for, and knowledge about generative AI. We present an overview of students’ AI usage and knowledge using descriptive statistics. For further analysis, a Latent Class Analysis was conducted and four distinct response patterns among students identified: AI-positive knowledge-seekers, Cautious AI-adopters, AI-sceptics and Efficiency-seekers. These four classes were then used to explore differences relating to gender, grade, choice of study programme, attitude to knowledge, neuropsychiatric diagnoses and non-native Swedish speaking students. We find that students use generative AI for schoolwork primarily as support for the process of doing their schoolwork but also as a shortcut for tasks perceived as meaningless. We find that the identified patterns of attitudes, knowledge and usage exhibit behaviours that are in different ways both promising and worrisome, and that warrant different courses of action in education. This research contributes by identifying differences in student behaviour and attitudes towards AI, and points to needs for further research in the diversity of behaviour and the consequences of different use patterns, as well as the need to tailor educational support for different student groups.

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Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-12-12
DOI
https://doi.org/10.1016/j.caeai.2025.100531
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
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article

Seeking knowledge or efficiency: Profiling students’ AI-use through survey-based latent class analysis

Luisa W. Hugerth, Mattias Wickberg Hugerth
1 citations
Computers and Education Artificial Intelligence
AI in Service Interactions
2.48
article

Seeking knowledge or efficiency: Profiling students’ AI-use through survey-based latent class analysis

Luisa W. Hugerth, Mattias Wickberg Hugerth
article en
1 citations

Abstract

The spread of easily accessible generative AI in the form of chatbots has impacted secondary education, but the effects of this are largely unknown. Previous studies have shown that using chatbots in a learning context can be both harmful or helpful depending on how they are used. While students are undoubtedly utilising this technology, there is scarce data on the extent, intention, or approach to its use, or what drives it. The present study builds upon the findings of a previous qualitative study, aiming to investigate and quantify students' use of generative AI for schoolwork. Through a survey sent to multiple upper secondary schools, we collected 1266 responses to analyse upper secondary students' attitudes toward, usage of, support for, and knowledge about generative AI. We present an overview of students’ AI usage and knowledge using descriptive statistics. For further analysis, a Latent Class Analysis was conducted and four distinct response patterns among students identified: AI-positive knowledge-seekers, Cautious AI-adopters, AI-sceptics and Efficiency-seekers. These four classes were then used to explore differences relating to gender, grade, choice of study programme, attitude to knowledge, neuropsychiatric diagnoses and non-native Swedish speaking students. We find that students use generative AI for schoolwork primarily as support for the process of doing their schoolwork but also as a shortcut for tasks perceived as meaningless. We find that the identified patterns of attitudes, knowledge and usage exhibit behaviours that are in different ways both promising and worrisome, and that warrant different courses of action in education. This research contributes by identifying differences in student behaviour and attitudes towards AI, and points to needs for further research in the diversity of behaviour and the consequences of different use patterns, as well as the need to tailor educational support for different student groups.

Computers and Education Artificial IntelligenceVol. 10
Stockholm University (SE), Science for Life Laboratory (SE)
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
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