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Effects of higher education institutes’ artificial intelligence capability on students' self-efficacy, creativity and learning performance

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Abstract

Artificial Intelligence (AI) has become an important technology affecting the development of society and education, and it is crucial to explore AI to enhance students' creativity and learning performance. This research proposes the model and hypothesis based on the resource-based theory and related research. AI of higher education institute (HEI) affects students' learning performance and combines the existing literature to develop measurement tools and to obtain a formal questionnaire after pre-research and received 561 valid questionnaires collected from HEIs in China that have applied AI. Then we used SmartPLS 3.0 to construct a partial least squares structural equation model (PLS-SEM) for data analysis on the received data samples. The research results show that: 1) HEIs' artificial intelligence capability is a three-order variable and formed by three formative second-order variables such as resources (data, technical, basic resources), skills (technical skills, teaching applications, collaboration competencies), and consciousness (reform, innovation consciousness); 2) HEIs' artificial intelligence capability significantly affects students' self-efficacy and creativity; 3) HEIs' artificial intelligence capability affects students' learning performance via two mediating variables: student creativity and self-efficacy. This study focuses on AI applications within the HEI, confirms the new explanatory power of resource-based theory in technological practices, and deconstructs the intrinsic mechanics, especially in relationships between students' creativity, self-efficacy, and learning performance. This research also puts forward suggestions to reserve and deploy artificial intelligence resources, improve the digital literacy of teachers and students, use AI to drive teaching and learning, and improve students' creativity and learning performance.

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

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Acknowledgements

Thanks to Mengti Li for her assistance in the language expression of the article.

Funding

This work was supported by the Ningbo Philosophy and Social Science Planning Project [G22-5-JY09]; Ningbo Education Science Planning Project under Grant [2022YZD012]; Ningbo Soft Science Research Program under Grant [2022R040]; Zhejiang Federation of Humanities and Social Sciences Circles under Grant [2023N073]; and Zhejiang Province Association for Higher Education Project under Grant [KT2022412].

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  1. School of Logistics and E-Commerce, Zhejiang Wanli University, Ningbo, 315000, China

    Shaofeng Wang

  2. Smart Learning Institute, Beijing Normal University, Beijing, 100875, China

    Shaofeng Wang, Zhuo Sun & Ying Chen

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Conceptualization, S.W. and Y.C.; methodology, S.W.; software, S.W.; validation, S.W., Z.S. and Y.C.; formal analysis, S.W.; investigation, S.W.; resources, S.W.; data curation, S.W.; writing —original draft preparation, S.W. and Y.C.; 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 Zhuo Sun.

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Wang, S., Sun, Z. & Chen, Y. Effects of higher education institutes’ artificial intelligence capability on students' self-efficacy, creativity and learning performance. Educ Inf Technol 28, 4919–4939 (2023). https://doi.org/10.1007/s10639-022-11338-4

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