IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i16p9925-d885673.html
   My bibliography  Save this article

Predicting Factors Influencing Preservice Teachers’ Behavior Intention in the Implementation of STEM Education Using Partial Least Squares Approach

Author

Listed:
  • Tommy Tanu Wijaya

    (School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China)

  • Peijie Jiang

    (School of Mathematics and Statistics, Hunan Normal University, Changsha 410081, China)

  • Mailizar Mailizar

    (Mathematics Education Department, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia)

  • Akhmad Habibi

    (Fakultas Keguruan dan Ilmu Pendidikan, Universitas Jambi, Jambi 36122, Indonesia)

Abstract

The integration of STEM education has been promoted to improve the quality of education in the 21st century, with its usage leading to emphasis on the factors influencing the intentions of preservice teachers. Therefore, this study aims to determine the factors influencing preservice teachers’ intentions, as well as the effects of gender and age on the implementation of STEM education. The Theory of Planned Behavior (TPB) was adopted to predict the relationship between knowledge, social influence, attitude, perceived usefulness, control, and behavioral intention (BI) of using STEM education among preservice secondary school teachers. A total of 30 item questionnaires on behavioral intentions were distributed to 201 respondents, with data being analyzed using the Structural Equation Model (SEM). The results showed that perceived usefulness had a positive significance, and a relationship with the attitudes of preservice teachers toward STEM education. Habit had a positive significance in influencing teachers’ behavioral intentions and implementation. Subjective norms did not have a significant correlation with BI and implementation. These results are recommended for providing solutions to analytical problems, and to successfully improve future learning through an educational approach.

Suggested Citation

  • Tommy Tanu Wijaya & Peijie Jiang & Mailizar Mailizar & Akhmad Habibi, 2022. "Predicting Factors Influencing Preservice Teachers’ Behavior Intention in the Implementation of STEM Education Using Partial Least Squares Approach," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:9925-:d:885673
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/16/9925/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/16/9925/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Julia Stössel & Rebecca Baumann & Elisabeth Wegner, 2021. "Predictors of Student Teachers’ ESD Implementation Intention and Their Implications for Improving Teacher Education," Sustainability, MDPI, vol. 13(16), pages 1-25, August.
    2. Farrah Dina Yusop & Akhmad Habibi & Rafiza Abdul Razak, 2021. "Factors Affecting Indonesian Preservice Teachers’ Use of ICT During Teaching Practices Through Theory of Planned Behavior," SAGE Open, , vol. 11(2), pages 21582440211, June.
    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. Tommy Tanu Wijaya & Yiming Cao & Robert Weinhandl & Eri Yusron & Zsolt Lavicza, 2022. "Applying the UTAUT Model to Understand Factors Affecting Micro-Lecture Usage by Mathematics Teachers in China," Mathematics, MDPI, vol. 10(7), pages 1-20, March.
    5. repec:adr:anecst:y:2014:i:115-116:p:3 is not listed on IDEAS
    6. Abdulwahab Mujalli & Tehmina Khan & Ahmed Almgrashi, 2022. "University Accounting Students and Faculty Members Using the Blackboard Platform during COVID-19; Proposed Modification of the UTAUT Model and an Empirical Study," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
    7. Tommy Tanu Wijaya & Ying Zhou & Tony Houghton & Robert Weinhandl & Zsolt Lavicza & Farrah Dina Yusop, 2022. "Factors Affecting the Use of Digital Mathematics Textbooks in Indonesia," Mathematics, MDPI, vol. 10(11), pages 1-18, May.
    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. Alka Pandita & Ravi Kiran, 2023. "The Technology Interface and Student Engagement Are Significant Stimuli in Sustainable Student Satisfaction," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    2. Tommy Tanu Wijaya & Boran Yu & Fei Xu & Zhiqiang Yuan & Mailizar Mailizar, 2023. "Analysis of Factors Affecting Academic Performance of Mathematics Education Doctoral Students: A Structural Equation Modeling Approach," IJERPH, MDPI, vol. 20(5), pages 1-23, March.
    3. Jeng-Chieh Cheng & Jeen-Fong Li & Chi-Yo Huang, 2023. "Enablers for Adopting Restriction of Hazardous Substances Directives by Electronic Manufacturing Service Providers," Sustainability, MDPI, vol. 15(16), pages 1-45, August.
    4. Tommy Tanu Wijaya & Imam Fitri Rahmadi & Siti Chotimah & Jailani Jailani & Dhoriva Urwatul Wutsqa, 2022. "A Case Study of Factors That Affect Secondary School Mathematics Achievement: Teacher-Parent Support, Stress Levels, and Students’ Well-Being," IJERPH, MDPI, vol. 19(23), pages 1-19, December.

    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. Zhiqiang Yuan & Jing Liu & Xi Deng & Tianzi Ding & Tommy Tanu Wijaya, 2023. "Facilitating Conditions as the Biggest Factor Influencing Elementary School Teachers’ Usage Behavior of Dynamic Mathematics Software in China," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    2. Peijie Jiang & Tommy Tanu Wijaya & Mailizar Mailizar & Zulfah Zulfah & Astuti Astuti, 2022. "How Micro-Lectures Improve Learning Satisfaction and Achievement: A Combination of ECM and Extension of TAM Models," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    3. Hye-Ran Eun & Jong-Tae Park & Jong-Hwa Jang, 2022. "Factors Related to the Intention to Use Dental Care by Industrial Workers Due to COVID-19: Application of Anderson Model and Planned Behavior Theory," IJERPH, MDPI, vol. 19(19), pages 1-14, October.
    4. Qihui Xie, 2022. "The Factors Influencing Chinese University Teachers’ Intentions for Using the Micro-Lecture in the Post COVID-19 Era," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    5. Fang Wang & Tommy Tanu Wijaya & Akhmad Habibi & Yixuan Liu, 2022. "Predictors Influencing Urban and Rural Area students to Use Tablet Computers as Learning Tools: Combination of UTAUT and TTF Models," Sustainability, MDPI, vol. 14(21), pages 1-22, October.
    6. Saeideh Sharifi fard & Ezhar Tamam & Md Salleh Hj Hassan & Moniza Waheed & Zeinab Zaremohzzabieh, 2016. "Factors affecting Malaysian university students’ purchase intention in social networking sites," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1182612-118, December.
    7. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    8. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    9. Melih Engin & Fatih Gürses, 2019. "Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-19, October.
    10. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    11. Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    12. Abdesamad Zouine & Pierre Fenies, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    13. 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.
    14. Kertcher, Zack & Venkatraman, Rohan & Coslor, Erica, 2020. "Pleasingly parallel: Early cross-disciplinary work for innovation diffusion across boundaries in grid computing," Journal of Business Research, Elsevier, vol. 116(C), pages 581-594.
    15. Talukder, Md. Shamim & Sorwar, Golam & Bao, Yukun & Ahmed, Jashim Uddin & Palash, Md. Abu Saeed, 2020. "Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    16. Fang Li & Sheng Zhang & Yuhuan Jin, 2018. "Sustainability of University Technology Transfer: Mediating Effect of Inventor’s Technology Service," Sustainability, MDPI, vol. 10(6), pages 1-17, June.
    17. Waqar Younas & K. Ramanathan Kalimuthu, 2021. "Telecom microfinance banking versus commercial banking: a battle in the financial services sector," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 26(2), pages 67-80, June.
    18. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    19. Claudio Vitari & Elisabetta Raguseo, 2016. "Big data value and financial performance: an empirical investigation [Digital data, dynamic capability and financial performance: an empirical investigation in the era of Big Data]," Post-Print halshs-01923271, HAL.
    20. 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.

    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:14:y:2022:i:16:p:9925-:d:885673. 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.