IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p13725-d950909.html
   My bibliography  Save this article

The Potential of Big Data Application in Mathematics Education in Malaysia

Author

Listed:
  • Sim Jia Jin

    (School of Education, Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia)

  • Abdul Halim Abdullah

    (School of Education, Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia)

  • Mahani Mokhtar

    (School of Education, Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia)

  • Umar Haiyat Abdul Kohar

    (Faculty of Management, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia)

Abstract

The world is facing rapid changes after the emergence of innovative technologies. These changes aim to ensure that a country keeps track of current world developments, strengthens its economy, and reduces its dependence on imports. Hence, every country is now amid technological transformation in the industrial sector by replacing manpower with machines to increase production and efficiency, allowing for mass production. Technology advancements in control, information technology, and automation that are applied to business and industry production processes are referred to as ‘Industry 4.0’. The objective is to increase the autonomy, adaptability, and effectiveness of decision-making and production processes utilizing cyber-physical systems (CPS), Big Data (BD), artificial intelligence (AI), and the industrial Internet of Things (IoT). Specifically, this article first introduces Industry Revolution (IR) 4.0, followed by a delineation of the concept of BD. Correspondingly, we discuss BD in education and relate mathematics education with BD. The article concludes with the implications of BD for Malaysian teaching and learning practices.

Suggested Citation

  • Sim Jia Jin & Abdul Halim Abdullah & Mahani Mokhtar & Umar Haiyat Abdul Kohar, 2022. "The Potential of Big Data Application in Mathematics Education in Malaysia," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13725-:d:950909
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/13725/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/13725/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haitham Nobanee & Mehroz Nida Dilshad & Mona Al Dhanhani & Maitha Al Neyadi & Sultan Al Qubaisi & Saeed Al Shamsi, 2021. "Big Data Applications the Banking Sector: A Bibliometric Analysis Approach," SAGE Open, , vol. 11(4), pages 21582440211, December.
    2. Roberto Moro Visconti & Donato Morea, 2019. "Big Data for the Sustainability of Healthcare Project Financing," Sustainability, MDPI, vol. 11(13), pages 1-17, July.
    3. Torrecilla, José L. & Romo, Juan, 2018. "Data learning from big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 15-19.
    4. Lee, In, 2017. "Big data: Dimensions, evolution, impacts, and challenges," Business Horizons, Elsevier, vol. 60(3), pages 293-303.
    5. Prachyanun Nilsook & Pinanta Chatwattana & Thapanee Seechaliao, 2021. "The Project-based Learning Management Process for Vocational and Technical Education," Higher Education Studies, Canadian Center of Science and Education, vol. 11(2), pages 1-20, June.
    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. Haopeng Wang & Zhenzhi Zhao & Yingying Ma & Hao Wu & Fei Bao, 2023. "Sustainable Road Planning for Trucks in Urbanized Areas of Chinese Cities Using Deep Learning Approaches," Sustainability, MDPI, vol. 15(11), pages 1-19, May.

    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. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    2. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    3. Maniyassouwe Amana & Pingfeng Liu & Mona Alariqi, 2022. "Value Creation and Capture with Big Data in Smart Phones Companies," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    4. Pei Zhang & Peiran Chen & Fan Xiao & Yong Sun & Shuyan Ma & Ziwei Zhao, 2022. "The Impact of Information Infrastructure on Air Pollution: Empirical Evidence from China," IJERPH, MDPI, vol. 19(21), pages 1-17, November.
    5. Arnold, René & Hildebrandt, Christian & Taş, Serpil, 2020. "Europäische Datenökonomie: Zwischen Wettbewerb und Regulierung. Endbericht," Study Series, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH, number 251537.
    6. Tiago Carneiro & Winnie Ng Picoto & Inês Pinto, 2023. "Big Data Analytics and Firm Performance in the Hotel Sector," Tourism and Hospitality, MDPI, vol. 4(2), pages 1-13, April.
    7. Al-Omoush, Khaled Saleh & Garcia-Monleon, Fernando & Mas Iglesias, José Manuel, 2024. "Exploring the interaction between big data analytics, frugal innovation, and competitive agility: The mediating role of organizational learning," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    8. Wang, Fengquan & Jiang, Jihai & Cosenz, Federico, 2025. "Understanding data-driven business model innovation in complexity: A system dynamics approach," Journal of Business Research, Elsevier, vol. 186(C).
    9. Bohnsack, René & Liesner, Meike Malena, 2019. "What the hack? A growth hacking taxonomy and practical applications for firms," Business Horizons, Elsevier, vol. 62(6), pages 799-818.
    10. Biman Darshana Hettiarachchi & Stefan Seuring & Marcus Brandenburg, 2022. "Industry 4.0-driven operations and supply chains for the circular economy: a bibliometric analysis," Operations Management Research, Springer, vol. 15(3), pages 858-878, December.
    11. Saarikko, Ted & Westergren, Ulrika H. & Blomquist, Tomas, 2020. "Digital transformation: Five recommendations for the digitally conscious firm," Business Horizons, Elsevier, vol. 63(6), pages 825-839.
    12. Lindsey G Smith & Maggie Yifei Ma & Michael J Widener & Steven Farber, 2023. "Geographies of grocery shopping in major Canadian cities: Evidence from large-scale mobile app data," Environment and Planning B, , vol. 50(3), pages 723-739, March.
    13. Katalina Salas & Deana Pennington, 2024. "Integrating Scenario Analysis and Participatory Modeling to Generate Plausible Future Narratives for Water Resources: A Case Study in the Middle Rio Grande River Basin," Sustainability, MDPI, vol. 16(23), pages 1-19, December.
    14. Roberto Moro-Visconti, 2021. "Networking Digital Platforms and Healthcare Project Finance Bankability," Sustainability, MDPI, vol. 13(9), pages 1-18, April.
    15. Amit Kumar Gupta & Harshit Goyal, 2021. "Framework for implementing big data analytics in Indian manufacturing: ISM-MICMAC and Fuzzy-AHP approach," Information Technology and Management, Springer, vol. 22(3), pages 207-229, September.
    16. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    17. Zhiting Song & Yanming Sun & Jiafu Wan & Lingli Huang & Jianhua Zhu, 2019. "Smart e-commerce systems: current status and research challenges," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 221-238, June.
    18. Dilnaz Muneeb & Haitham Nobanee & Muhammad Mustafa Kamal & Hiba Zaki Shanti, 2025. "A bibliometric review of supply chain finance and digitalisation: mapping, current streams, and future research agenda," Management Review Quarterly, Springer, vol. 75(1), pages 43-81, February.
    19. Issariya Woraphiphat & Pattama Roopsuwankun, 2023. "The impact of online design thinking-based learning on entrepreneurial intention: the case of vocational college," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-18, December.
    20. Donato Morea & Elisa Gebennini, 2021. "New Project Financing and Eco-Efficiency Models for Investment Sustainability," Sustainability, MDPI, vol. 13(2), pages 1-3, January.

    More about this item

    Keywords

    ;
    ;
    ;

    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:gam:jsusta:v:14:y:2022:i:21:p:13725-:d:950909. 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.