IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i6p1536-d1103956.html
   My bibliography  Save this article

Facilitating Conditions as the Biggest Factor Influencing Elementary School Teachers’ Usage Behavior of Dynamic Mathematics Software in China

Author

Listed:
  • Zhiqiang Yuan

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

  • Jing Liu

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

  • Xi Deng

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

  • Tianzi Ding

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

  • Tommy Tanu Wijaya

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

Abstract

Dynamic mathematics software, such as GeoGebra, is one of the most important teaching and learning media. This kind of software can help teachers teach mathematics, especially geometry, at the elementary school level. However, the use of dynamic mathematics software of elementary school teachers is still very limited so far. This study analyzed the factors influencing elementary school teachers’ usage behavior of dynamic mathematics software. Four independent variables, namely performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC) from the united theory of acceptance and use of technology (UTAUT), were used to understand elementary school teachers’ usage behavior of dynamic mathematics software. A questionnaire survey was conducted in the Hunan and Guangdong provinces of China. Two hundred and sixty-six elementary school mathematics teachers provided valid questionnaire data. The partial least squares structural equation modeling (PLS-SEM) approach was used to analyze the data. The results showed that facilitating conditions and effort expectancy significantly affect elementary school teachers’ usage behavior of dynamic mathematics software, and facilitating conditions were the biggest factor that affected user behavior. The moderating effects of gender, major, and training on all relationships in the dynamic mathematics software usage conceptual model were not significant. This study contributes by developing a model and providing new knowledge to elementary school principals and the government about factors that can increase the adoption of dynamic mathematics software.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1536-:d:1103956
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/6/1536/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/6/1536/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    2. Elisa Miragliotta & Anna E. Baccaglini-Frank, 2021. "Enhancing the Skill of Geometric Prediction Using Dynamic Geometry," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    3. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    4. Rushan Ziatdinov & James R. Valles, 2022. "Synthesis of Modeling, Visualization, and Programming in GeoGebra as an Effective Approach for Teaching and Learning STEM Topics," Mathematics, MDPI, vol. 10(3), pages 1-16, January.
    5. Mustafa Cevikbas & Gabriele Kaiser, 2021. "A Systematic Review on Task Design in Dynamic and Interactive Mathematics Learning Environments (DIMLEs)," Mathematics, MDPI, vol. 9(4), pages 1-20, February.
    6. 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.
    7. Nisar Ahmed Dahri & Muhammad Saleem Vighio & Jairam Das Bather & Aijaz Ahmed Arain, 2021. "Factors Influencing the Acceptance of Mobile Collaborative Learning for the Continuous Professional Development of Teachers," Sustainability, MDPI, vol. 13(23), pages 1-23, November.
    8. 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.
    9. 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.
    10. 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)

    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. 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.
    2. Niyazi Gümüº & Özgür Çark, 2021. "The effect of customers’ attitudes towards chatbots on their experience and behavioral intention in Turkey," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 19(3), pages 420-436.
    3. Nistor, Cristian, 2013. "A conceptual model for the use of social media in companies," MPRA Paper 44224, University Library of Munich, Germany.
    4. Kawsar Ahmad & Arifuzzaman Arifuzzaman & Abdullah Al Mamun & Junayed Md Khaled Bin Oalid, 2021. "Impact of consumer’s security, benefits and usefulness towards cashless transaction within Malaysian university student," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(2), pages 238-250, March.
    5. Sarv Devaraj & Ming Fan & Rajiv Kohli, 2002. "Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics," Information Systems Research, INFORMS, vol. 13(3), pages 316-333, September.
    6. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    7. Oghuma, Apollos Patricks & Chang, Younghoon & Libaque-Saenz, Christian Fernando & Park, Myeong-Cheol & Rho, Jae Jeung, 2015. "Benefit-confirmation model for post-adoption behavior of mobile instant messaging applications: A comparative analysis of KakaoTalk and Joyn in Korea," Telecommunications Policy, Elsevier, vol. 39(8), pages 658-677.
    8. Shafiqul Islam & Mohammad Fakhrul Islam & Noor-E- Zannat, 2023. "Behavioral Intention to Use Online for Shopping in Bangladesh: A Technology Acceptance Model Analysis," SAGE Open, , vol. 13(3), pages 21582440231, September.
    9. Netsanet Haile & Jörn Altmann, 2016. "Structural analysis of value creation in software service platforms," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 129-142, May.
    10. McLean, Graeme & Osei-Frimpong, Kofi & Al-Nabhani, Khalid & Marriott, Hannah, 2020. "Examining consumer attitudes towards retailers' m-commerce mobile applications – An initial adoption vs. continuous use perspective," Journal of Business Research, Elsevier, vol. 106(C), pages 139-157.
    11. Garaus, Marion & Wolfsteiner, Elisabeth & Wagner, Udo, 2016. "Shoppers' acceptance and perceptions of electronic shelf labels," Journal of Business Research, Elsevier, vol. 69(9), pages 3687-3692.
    12. Ivonne Angelica Castiblanco Jimenez & Laura Cristina Cepeda García & Maria Grazia Violante & Federica Marcolin & Enrico Vezzetti, 2020. "Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications," Future Internet, MDPI, vol. 13(1), pages 1-21, December.
    13. Juan F. Tavera Mesías & Juan C. Sánchez Giraldo & Bernardo Ballesteros Díaz, 2011. "Aceptación del E-Commerce en Colombia: un estudio para la ciudad de Medellín," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, December.
    14. Salvador Angosto & Jerónimo García-Fernández & Moisés Grimaldi-Puyana, 2023. "A systematic review of intention to use fitness apps (2020–2023)," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    15. Yadgar Taha M. Hamakhan, 2020. "The effect of individual factors on user behaviour and the moderating role of trust: an empirical investigation of consumers’ acceptance of electronic banking in the Kurdistan Region of Iraq," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-29, December.
    16. Junic Kim, 2018. "Platform Adoption Factors in the Internet Industry," Sustainability, MDPI, vol. 10(9), pages 1-12, September.
    17. Liébana-Cabanillas, Francisco & Marinkovic, Veljko & Ramos de Luna, Iviane & Kalinic, Zoran, 2018. "Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 117-130.
    18. Deborah Compeau & Barbara Marcolin & Helen Kelley & Chris Higgins, 2012. "Research Commentary ---Generalizability of Information Systems Research Using Student Subjects---A Reflection on Our Practices and Recommendations for Future Research," Information Systems Research, INFORMS, vol. 23(4), pages 1093-1109, December.
    19. Chen Wei, 2021. "The influence of Consumers’ Purchase intention on Smart Wearable Device: A study of Consumers in East China," International Journal of Science and Business, IJSAB International, vol. 5(8), pages 46-72.
    20. Simarpreet Kaur & Sangeeta Arora, 2023. "Understanding customers’ usage behavior towards online banking services: an integrated risk–benefit framework," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 74-98, March.

    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:jmathe:v:11:y:2023:i:6:p:1536-:d:1103956. 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.