IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2180-d1045568.html
   My bibliography  Save this article

The Positive Effects of Growth Mindset on Students’ Intention toward Self-Regulated Learning during the COVID-19 Pandemic: A PLS-SEM Approach

Author

Listed:
  • Yujun Jiang

    (School of Language and Culture, Swan College, Central South University of Forestry and Technology, Changsha 410211, China
    Faculty of Public Administration and Social Studies, Stamford International University, Bangkok 10250, Thailand)

  • Huying Liu

    (School of Language and Culture, Swan College, Central South University of Forestry and Technology, Changsha 410211, China)

  • Yuna Yao

    (College of Preschool Education, Shandong Yingcai University, Jinan 250104, China)

  • Qiang Li

    (School of Economics and Management, Shanghai Technical Institute of Economics and Information, Shanghai 201411, China)

  • Yingji Li

    (School of Humanities and Management, Yunnan University of Chinese Medicine, Kunming 650500, China)

Abstract

The COVID-19 pandemic has brought unprecedented challenges to students’ learning processes in higher education. This study aimed to investigate the effects of a growth mindset on university students’ intention toward self-regulated learning during the COVID-19 pandemic. The theoretical model was proposed based on the Theory of Planned Behavior, along with two additional dimensions: growth mindset and perceived teacher support. The developed model was validated by adopting a partial least squares structural equation modeling (PLS-SEM) approach based on the data collected from 486 students in universities that have been significantly impacted by the COVID-19 pandemic in China. The results show that students’ growth mindset is positively associated with their intention toward self-regulated learning directly, and indirectly through the main constructs of the Theory of Planned Behavior: perceived behavioral control and behavior attitude. Additionally, the mediating and moderating roles of students’ growth mindset are manifest in the relationship between students’ perception of teacher support and their intention toward self-regulated learning. These findings offer implications for teachers, researchers, and higher education administrators in developing students’ growth mindset by considering the relevant factors explored in this research, thereby enhancing students’ self-regulated learning in challenging settings such as the COVID-19 pandemic.

Suggested Citation

  • Yujun Jiang & Huying Liu & Yuna Yao & Qiang Li & Yingji Li, 2023. "The Positive Effects of Growth Mindset on Students’ Intention toward Self-Regulated Learning during the COVID-19 Pandemic: A PLS-SEM Approach," Sustainability, MDPI, vol. 15(3), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2180-:d:1045568
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2180/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2180/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David S. Yeager & Paul Hanselman & Gregory M. Walton & Jared S. Murray & Robert Crosnoe & Chandra Muller & Elizabeth Tipton & Barbara Schneider & Chris S. Hulleman & Cintia P. Hinojosa & David Paunesk, 2019. "A national experiment reveals where a growth mindset improves achievement," Nature, Nature, vol. 573(7774), pages 364-369, September.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    4. Yujun Jiang & Ping Wang & Qiang Li & Yingji Li, 2022. "Students’ Intention toward Self-Regulated Learning under Blended Learning Setting: PLS-SEM Approach," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jooyoung Lee & Ki Han Kwon, 2023. "Promoting Sustainable Learning in the Post-Pandemic Era: Focused on the Role of Motivation, Growth Mindset, Self-Regulated Learning, Well-Being, and Smart Device Utilization," Sustainability, MDPI, vol. 15(17), pages 1-21, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.
    2. Yu Wang & Shanyong Wang & Jing Wang & Jiuchang Wei & Chenglin Wang, 2020. "An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model," Transportation, Springer, vol. 47(1), pages 397-415, February.
    3. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    4. Peter Mantello & Manh-Tung Ho & Minh-Hoang Nguyen & Quan-Hoang Vuong, 2023. "Machines that feel: behavioral determinants of attitude towards affect recognition technology—upgrading technology acceptance theory with the mindsponge model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    5. Fox, Stephen & Groesser, Stefan N., 2016. "Reframing the relevance of research to practice," European Management Journal, Elsevier, vol. 34(5), pages 457-465.
    6. Mäntymäki, Matti & Salo, Jari, 2013. "Purchasing behavior in social virtual worlds: An examination of Habbo Hotel," International Journal of Information Management, Elsevier, vol. 33(2), pages 282-290.
    7. Fatima Zahra Barrane & Gahima Egide Karuranga & Diane Poulin, 2018. "Technology Adoption and Diffusion: A New Application of the UTAUT Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-19, December.
    8. Joan Torrent-Sellens & Cristian Salazar-Concha & Pilar Ficapal-Cusí & Francesc Saigí-Rubió, 2021. "Using Digital Platforms to Promote Blood Donation: Motivational and Preliminary Evidence from Latin America and Spain," IJERPH, MDPI, vol. 18(8), pages 1-17, April.
    9. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    10. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    11. Riffat Ara Zannat Tama & Md Mahmudul Hoque & Ying Liu & Mohammad Jahangir Alam & Mark Yu, 2023. "An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh," Agriculture, MDPI, vol. 13(2), pages 1-22, February.
    12. Scott, Stephanie & Hughes, Paul & Hodgkinson, Ian & Kraus, Sascha, 2019. "Technology adoption factors in the digitization of popular culture: Analyzing the online gambling market," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    13. Pan Gong & Ningshuang Zeng & Kunhui Ye & Markus König, 2019. "An Empirical Study on the Acceptance of 4D BIM in EPC Projects in China," Sustainability, MDPI, vol. 11(5), pages 1-19, March.
    14. Cabrera-Sánchez, Juan-Pedro & Villarejo-Ramos, à ngel F., 2020. "Acceptance and use of big data techniques in services companies," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    15. Alfiero, Simona & Battisti, Enrico & Ηadjielias, Elias, 2022. "Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    16. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    17. Chia-Chien Hsu & Brian Sandford & Chia-Ju Ling & Ching-Torng Lin, 2021. "Can the Unified Theory of Acceptance and Use of Technology (UTAUT) Help Explain Subjective Well-Being in Senior Citizens due to Gateball Participation?," IJERPH, MDPI, vol. 18(17), pages 1-15, August.
    18. Asmussen, Katherine E. & Mondal, Aupal & Bhat, Chandra R., 2022. "Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 156-179.
    19. repec:aud:audfin:v:20:y:2018:i:48:p:373 is not listed on IDEAS
    20. Herman Fassou Haba & Omkar Dastane, 2018. "An Empirical Investigation on Taxi Hailing Mobile App Adoption: A Structural Equation Modelling," Business Management and Strategy, Macrothink Institute, vol. 9(1), pages 48-72, December.
    21. Abu Elnasr E. Sobaih & Ibrahim A. Elshaer, 2023. "Risk-Taking, Financial Knowledge, and Risky Investment Intention: Expanding Theory of Planned Behavior Using a Moderating-Mediating Model," Mathematics, MDPI, vol. 11(2), pages 1-17, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2180-:d:1045568. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.