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Roles of artificial intelligence experience, information redundancy, and familiarity in shaping active learning: Insights from intelligent personal assistants

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Abstract

Artificial Intelligence (AI) is increasingly being integrated into educational settings, with Intelligent Personal Assistants (IPAs) playing a significant role. However, the psychological impact of these AI assistants on fostering active learning behaviors needs to be better understood. This research study addresses this gap by proposing a theoretical model to outline and predict active learning dynamics. Data was collected from 237 validated questionnaires and analyzed using partial least squares structural equation modeling. Our results confirm most hypotheses advanced in our model, and information redundancy has an unexpected negative and indirect influence on active learning, while perceived familiarity and system quality are positive drivers. Crucial mediators such as perceived usefulness, ease of use, and convenience significantly positively influence active learning outcomes. Interestingly, the relationship between perceived ease of use, perceived convenience, and active learning is positively moderated by AI experience. The most striking and unexpected finding of this study is the preference of university students for familiar systems over high-tech learning methods. This result challenges the common belief that the younger generation is always eager to adopt the latest technology. Instead, our findings suggest that students value convenience and familiarity over novelty in learning systems. This preference is reflected in their systematic evaluation, where convenience and familiarity are considered top priorities. This study provides valuable insights into the potential of AI to enrich the learning experience, thus making it especially relevant to professionals interested in artificial intelligence in international business education.

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Data availability

The datasets used or analysed during the current study are available from the author on reasonable request.

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Acknowledgements

Thanks to Fei Shen for her assistance in collecting the article materials. Thanks to our colleagues and Digital Tools for their help with the article's language.

Funding

This work was supported by the Ministry of Education of People’s Republic of China under Grant [19YJC880104]; National Education Sciences Planning under Grant [ACA220026]; Zhejiang Province Education Science Planning Project under Grant [2019SB122]; Zhejiang Provincial Philosophy and Social Sciences Planning Project (45); 2024 Fuzhou Philosophy and Social Science Key Research Base Project under Grant [2024FZB26]; and 2024 Fujian Provincial Civil Affairs Policy Theory Research Project under Grant [FMYB2024129].

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Authors and Affiliations

  1. International Business School, Fuzhou University of International Studies and Trade, Fuzhou, 350202, China

    Shaofeng Wang

  2. BDA New Town School of The High School Affiliated to Renmin University of China, Beijing, 100176, China

    Zhuo Sun

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  1. Shaofeng Wang
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  2. Zhuo Sun
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Contributions

Conceptualization, S.W.; methodology, S.W.; software, S.W.; validation, S.W. and Z.S.; formal analysis, S.W.; investigation, S.W.; resources, S.W., Z.S.; data curation, S.W.; writing —original draft preparation, S.W.; writing—review and editing, Z.S.; visualization, S.W.; supervision, S.W.; project administration, S.W.; funding acquisition, S.W. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Shaofeng Wang.

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Wang, S., Sun, Z. Roles of artificial intelligence experience, information redundancy, and familiarity in shaping active learning: Insights from intelligent personal assistants. Educ Inf Technol 30, 2525–2546 (2025). https://doi.org/10.1007/s10639-024-12895-6

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