IDEAS home Printed from https://ideas.repec.org/a/bcp/journl/v8y2024i11p128-143.html
   My bibliography  Save this article

Tackling Mathematics Underperformance: A Roadmap for SOS Herman Gmeiner School in Asiakwa

Author

Listed:
  • Ransford Ganyo

    (Department of Mathematics, University of Cape Coast, Ghana.)

  • PeterPaul Issah

    (Department of Computer Science, Kwame Nkrumah University of Science and Technology, Ghana)

  • Benedict Nii Ayi Armah

    (Department of Computer Science, Kwame Nkrumah University of Science and Technology, Ghana)

Abstract

This study examines the underlying causes of poor performance in mathematics among pupils at SOS Hermann Gmeiner Basic School in Asiakwa, Eastern Region of Ghana, and proposes effective strategies to address these challenges. Basic education serves as a crucial foundation for lifelong learning, equipping students with essential skills in literacy and numeracy, which are vital for personal and national development. Despite its importance, many students struggle with mathematics, leading to significant educational disparities. Employing a descriptive case study design, the research utilized questionnaires and unstructured interviews to gather data from students, teachers, and the head teacher. The analysis revealed several contributing factors to poor performance, including inadequate teaching methods, lack of qualified mathematics teachers, and negative student attitudes towards the subject. Additionally, environmental factors such as classroom conditions and parental involvement were found to play a significant role in shaping students’ academic experiences. The study highlights the necessity for targeted interventions to improve mathematics education. Recommendations include the recruitment of qualified teachers, provision of adequate teaching resources, and the implementation of in-service training programs focused on innovative teaching methodologies. Furthermore, fostering a positive learning environment through the use of pupil-centred approaches and engaging activities can significantly enhance students’ interest and performance in mathematics. By addressing these issues, the research aims to contribute to the broader discourse on educational reform in Ghana, providing insights that can inform policy decisions and teaching practices. Ultimately, this study seeks to empower students with the mathematical skills necessary for their future academic and career pursuits, thereby promoting overall educational equity and national development.

Suggested Citation

  • Ransford Ganyo & PeterPaul Issah & Benedict Nii Ayi Armah, 2024. "Tackling Mathematics Underperformance: A Roadmap for SOS Herman Gmeiner School in Asiakwa," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(11), pages 128-143, November.
  • Handle: RePEc:bcp:journl:v:8:y:2024:i:11:p:128-143
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijriss/Digital-Library/volume-8-issue-11/128-143.pdf
    Download Restriction: no

    File URL: https://rsisinternational.org/journals/ijriss/articles/tackling-mathematics-underperformance-a-roadmap-for-sos-herman-gmeiner-school-in-asiakwa/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    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. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.
    2. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    3. Aaltonen, Aleksi Ville & Alaimo, Cristina & Kallinikos, Jannis, 2021. "The making of data commodities: data analytics as an embedded process," LSE Research Online Documents on Economics 110296, London School of Economics and Political Science, LSE Library.
    4. Anke Joubert & Matthias Murawski & Markus Bick, 2023. "Measuring the Big Data Readiness of Developing Countries – Index Development and its Application to Africa," Information Systems Frontiers, Springer, vol. 25(1), pages 327-350, February.
    5. Rampersad, Giselle, 2020. "Robot will take your job: Innovation for an era of artificial intelligence," Journal of Business Research, Elsevier, vol. 116(C), pages 68-74.
    6. Sidney Anderson, 2024. "Expanding data literacy to include data preparation: building a sound marketing analytics foundation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(2), pages 227-234, June.
    7. Chiara Mio & Silvia Panfilo & Benedetta Blundo, 2020. "Sustainable development goals and the strategic role of business: A systematic literature review," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3220-3245, December.
    8. Magdalena Rusch & Josef‐Peter Schöggl & Rupert J. Baumgartner, 2023. "Application of digital technologies for sustainable product management in a circular economy: A review," Business Strategy and the Environment, Wiley Blackwell, vol. 32(3), pages 1159-1174, March.
    9. Michela Arnaboldi, 2018. "The Missing Variable in Big Data for Social Sciences: The Decision-Maker," Sustainability, MDPI, vol. 10(10), pages 1-18, September.
    10. Anike Sult & Janice Wobst & Rainer Lueg, 2024. "The role of training in implementing corporate sustainability: A systematic literature review," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(1), pages 1-30, January.
    11. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    12. Mohamed Gaber & Edward J. Lusk, 2019. "A Vetting Protocol for the Analytical Procedures Platform for the AP-Phase of PCAOB Audits," Accounting and Finance Research, Sciedu Press, vol. 8(4), pages 1-43, November.
    13. Leogrande, Angelo, 2021. "The Destruction of Price-Representativeness," MPRA Paper 111239, University Library of Munich, Germany.
    14. Damminda Alahakoon & Rashmika Nawaratne & Yan Xu & Daswin Silva & Uthayasankar Sivarajah & Bhumika Gupta, 2023. "Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities," Information Systems Frontiers, Springer, vol. 25(1), pages 221-240, February.
    15. Taiwen Feng & Hongyan Sheng, 2023. "Identifying the equifinal configurations of prompting green supply chain integration and subsequent performance outcome," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5234-5251, December.
    16. Harkaran Kava & Konstantina Spanaki & Thanos Papadopoulos & Stella Despoudi & Oscar Rodriguez-Espindola & Masoud Fakhimi, 2021. "Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective," Post-Print hal-03781046, HAL.
    17. Correa, Juan C. & Garzón, Wilmer & Brooker, Phillip & Sakarkar, Gopal & Carranza, Steven A. & Yunado, Leidy & Rincón, Alejandro, 2019. "Evaluation of collaborative consumption of food delivery services through web mining techniques," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 45-50.
    18. Sehrish Atif, 2023. "Mapping circular economy principles and servitisation approach in business model canvas: an integrated literature review," Future Business Journal, Springer, vol. 9(1), pages 1-21, December.
    19. Mazanec, Josef A., 2020. "Hidden theorizing in big data analytics: With a reference to tourism design research," Annals of Tourism Research, Elsevier, vol. 83(C).
    20. Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.

    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:bcp:journl:v:8:y:2024:i:11:p:128-143. 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: Dr. Pawan Verma (email available below). General contact details of provider: https://rsisinternational.org/journals/ijriss/ .

    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.