IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v12y2025i1d10.1057_s41599-025-05475-7.html
   My bibliography  Save this article

Technology-enhanced mathematics learning: review of the interactions between technological attributes and aspects of mathematics education from 2013 to 2022

Author

Listed:
  • Sherine Menella Omer

    (Sir Arthur Lewis Community College)

  • Katerina Evers

    (National Taiwan University of Science and Technology)

  • Chia-Yu Wang

    (National Taiwan University of Science and Technology
    National Taiwan University of Science and Technology)

  • Sufen Chen

    (National Taiwan University of Science and Technology
    National Taiwan University of Science and Technology
    North-West University)

Abstract

As the body of research surrounding technology-enhanced mathematics learning (TEML) continues to increase, there is a need to investigate the trends in the field. This study reviewed a decade (2013–2022) of research, and synthesized the findings of TEML interventions to inform future practice and research directions. Content of 44 articles on TEML from the Web of Science database for the period 2013–2022 was analyzed. Results indicated that dynamic mathematics software affords visualization and exploration which, when coupled with inquiry-based learning, is best suited for advanced thinking and conceptual development. Significant affective outcomes were attained when online assessment software, dynamic mathematics software, intelligent tutoring systems, and a combination of different software were incorporated into mathematics classrooms. According to the results, recommendations are provided for mathematics teachers regarding approaches to ensure the most effective TEML.

Suggested Citation

  • Sherine Menella Omer & Katerina Evers & Chia-Yu Wang & Sufen Chen, 2025. "Technology-enhanced mathematics learning: review of the interactions between technological attributes and aspects of mathematics education from 2013 to 2022," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-05475-7
    DOI: 10.1057/s41599-025-05475-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-025-05475-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-025-05475-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Lai, Fang & Luo, Renfu & Zhang, Linxiu & Huang, Xinzhe & Rozelle, Scott, 2015. "Does computer-assisted learning improve learning outcomes? Evidence from a randomized experiment in migrant schools in Beijing," Economics of Education Review, Elsevier, vol. 47(C), pages 34-48.
    2. Gwo-Jen Hwang & Yun-Fang Tu, 2021. "Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    3. Helen Crompton & Diane Burke, 2015. "Research Trends in the Use of Mobile Learning in Mathematics," International Journal of Mobile and Blended Learning (IJMBL), IGI Global Scientific Publishing, vol. 7(4), pages 1-15, October.
    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. Ferman, Bruno & Finamor, Lucas & Lima, Lycia, 2019. "Are Public Schools Ready to Integrate Math Classes with Khan Academy?," MPRA Paper 94736, University Library of Munich, Germany.
    2. Cardim, Joana & Molina-Millán, Teresa & Vicente, Pedro C., 2023. "Can technology improve the classroom experience in primary education? An African experiment on a worldwide program," Journal of Development Economics, Elsevier, vol. 164(C).
    3. Gourley, Patrick, 2021. "Back to basics: How reading the text and taking notes improves learning," International Review of Economics Education, Elsevier, vol. 37(C).
    4. Eric Bettinger & Robert Fairlie & Anastasia Kapuza & Elena Kardanova & Prashant Loyalka & Andrey Zakharov, 2023. "Diminishing Marginal Returns to Computer‐Assisted Learning," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(2), pages 552-570, March.
    5. Jamali, Seyedh Mahboobeh & Nader, Ale Ebrahim & Jamali, Fatemeh, 2021. "The Role of STEM Education in Improving the Quality of Education: A Bibliometric Study," MPRA Paper 114214, University Library of Munich, Germany, revised 02 May 2022.
    6. Narain Das & Kenneth Khawandiza Sunguh & Binesh Sarwar & Arslan Ahmed & Shah Hassan, 2019. "Technology-Embedded Educational Policy: Mediation Effects of the Use of Virtual Learning Influence on Learner Satisfaction," Journal of Education and Training, Macrothink Institute, vol. 6(1), pages 41-54, February.
    7. Yahya Fikri & Mohamed Rhalma, 2024. "Artificial Intelligence (AI) in Early Childhood Education (ECE): Do Effects and Interactions Matter?," Post-Print hal-04701470, HAL.
    8. Lafortune, Jeanne & Pugatch, Todd & Tessada, José & Ubfal, Diego, 2024. "Can gamified online training make high school students more entrepreneurial? Experimental evidence from Rwanda," Economics of Education Review, Elsevier, vol. 101(C).
    9. Aymo Brunetti & Konstantin Buechel & Martina Jakob & Ben Jann & Christoph Kuehnhanss & Daniel Steffen, 2020. "Teacher Content Knowledge in Developing Countries: Evidence from a Math Assessment in El Salvador," Diskussionsschriften dp2005, Universitaet Bern, Departement Volkswirtschaft.
    10. Jenny Aker & Joel Cariolle, 2022. "The Use of Digital for Public Service Provision in Sub-Saharan Africa," Post-Print hal-03003899, HAL.
    11. Yu Bai & Linxiu Zhang & Chengfang Liu & Yaojiang Shi & Di Mo & Scott Rozelle, 2018. "Effect of Parental Migration on the Academic Performance of Left Behind Children in North Western China," Journal of Development Studies, Taylor & Francis Journals, vol. 54(7), pages 1154-1170, July.
    12. Hong, Junjie & Liu, Wanlin & Zhang, Qing, 2024. "Closing the digital divide: The impact of teachers’ ICT use on student achievement in China," Journal of Comparative Economics, Elsevier, vol. 52(3), pages 697-713.
    13. Sunghwan Hwang, 2022. "Examining the Effects of Artificial Intelligence on Elementary Students’ Mathematics Achievement: A Meta-Analysis," Sustainability, MDPI, vol. 14(20), pages 1-18, October.
    14. Mini Zhu & Gang Wang & Chaoping Li & Hongjun Wang & Bin Zhang, 2023. "Artificial Intelligence Classification Model for Modern Chinese Poetry in Education," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    15. Karthik Muralidharan & Abhijeet Singh & Alejandro J. Ganimian, 2019. "Disrupting Education? Experimental Evidence on Technology-Aided Instruction in India," American Economic Review, American Economic Association, vol. 109(4), pages 1426-1460, April.
    16. Yue Ma & Robert Fairlie & Prashant Loyalka & Scott Rozelle, 2024. "Isolating the “Tech” from EdTech: Experimental Evidence on Computer-Assisted Learning in China," Economic Development and Cultural Change, University of Chicago Press, vol. 72(4), pages 1923-1962.
    17. Fulya Ersoy, 2021. "Returns to effort: experimental evidence from an online language platform," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 1047-1073, September.
    18. Angel B. Manuel & Julius S. Valderama, 2025. "Unpacking Reductionism in AI-Driven Mathematics Education: A Factor Analysis of Educators’ Insights and Applications," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(3s), pages 4904-4915, June.
    19. Tomoki Fujii & Christine Ho & Rohan Ray & Abu S. Shonchoy, 2025. "Boosting Study Habits with High-Frequency Information: A Field Experiment to Aid Disadvantaged Students," Working Papers 2501, Florida International University, Department of Economics.
    20. Araya, Roberto & Arias Ortiz, Elena & Bottan, Nicolas & Cristia, Julian, 2025. "Integrating learning platforms within regular school time: experimental evidence from Chilean primary schools," Economics of Education Review, Elsevier, vol. 106(C).

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-05475-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/palcomms/ .

    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.