IDEAS home Printed from https://ideas.repec.org/p/ipt/iptwpa/jrc140539.html

Teaching mathematics for success: A data-driven review and analysis of best practices

Author

Listed:

Abstract

Recent PISA 2022 results show that a relatively large proportion of EU students underachieve in mathematics. While this outcome has been partially driven by Covid-19, one should not forget that the decline in student performance was already under way before the pandemic. Evidence indicates that poor mathematics skills can have a detrimental impact on people’s life, leading to financial problems, academic struggles and professional setbacks. This situation underscores the urgent need for Member States to invest in programmes aimed at improving students’ mathematics achievement. In an attempt to assist Member States in identifying effective programmes to enhance students’ mathematics competences, this report synthetises relevant literature and adds some original research work. A rapid umbrella review is carried out to summarise evidence on what policies work best and which do not. Furthermore, PISA 2022 data are used to investigate the impact of digital resources on mathematics test scores. The findings from these two exercises concur in questioning the role of digital technologies in raising students’ performance in mathematics. Existing review studies do not consistently find technology-aided instruction to be among the best policies. Similarly, our analysis of PISA data does not show a positive association between the use of digital resources in mathematics classes and mathematics test scores. However, the empirical estimates suggest that students perform better in mathematics in those schools offering their teachers professional development in the area of integrating digital resources into mathematics instruction.

Suggested Citation

  • DI PIETRO Giorgio & KARPINSKI Zbigniew, 2024. "Teaching mathematics for success: A data-driven review and analysis of best practices," JRC Research Reports JRC140539, Joint Research Centre.
  • Handle: RePEc:ipt:iptwpa:jrc140539
    as

    Download full text from publisher

    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC140539
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Balázs Égert & Christine de la Maisonneuve & David Turner, 2024. "A new macroeconomic measure of human capital exploiting PISA and PIAAC: linking education policies to productivity," Education Economics, Taylor & Francis Journals, vol. 32(6), pages 745-761, November.
    2. repec:plo:pone00:0223049 is not listed on IDEAS
    3. Peter Bergman & Eric W. Chan, 2021. "Leveraging Parents through Low-Cost Technology: The Impact of High-Frequency Information on Student Achievement," Journal of Human Resources, University of Wisconsin Press, vol. 56(1), pages 125-158.
    4. Bonesrønning, Hans & Finseraas, Henning & Hardoy, Ines & Iversen, Jon Marius Vaag & Nyhus, Ole Henning & Opheim, Vibeke & Salvanes, Kari Vea & Sandsør, Astrid Marie Jorde & Schøne, Pål, 2022. "Small-group instruction to improve student performance in mathematics in early grades: Results from a randomized field experiment," Journal of Public Economics, Elsevier, vol. 216(C).
    5. Trine Filges & Christoffer Scavenius Sonne‐Schmidt & Bjørn Christian Viinholt Nielsen, 2018. "Small class sizes for improving student achievement in primary and secondary schools: a systematic review," Campbell Systematic Reviews, John Wiley & Sons, vol. 14(1), pages 1-107.
    6. Daniel Rodriguez-Segura, 2022. "EdTech in Developing Countries: A Review of the Evidence [From Proof of Concept to Scalable Policies: Challenges and Solutions, with an Application]," The World Bank Research Observer, World Bank, vol. 37(2), pages 171-203.
    7. Vicki-Lynn Holmes & Yooyeun Hwang, 2016. "Exploring the effects of project-based learning in secondary mathematics education," The Journal of Educational Research, Taylor & Francis Journals, vol. 109(5), pages 449-463, September.
    8. Apascaritei, Paula & Demel, Simona & Radl, Jonas, 2021. "The Difference Between Saying and Doing: Comparing Subjective and Objective Measures of Effort Among Fifth Graders," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 65(11), pages 1457-1479.
    9. de Ree, Joppe & Maggioni, Mario A. & Paulle, Bowen & Rossignoli, Domenico & Ruijs, Nienke & Walentek, Dawid, 2023. "Closing the income-achievement gap? Experimental evidence from high-dosage tutoring in Dutch primary education," Economics of Education Review, Elsevier, vol. 94(C).
    10. Correa, Hector & Gruver, Gene W., 1987. "Teacher-student interaction: A game theoretic extension of the economic theory of education," Mathematical Social Sciences, Elsevier, vol. 13(1), pages 19-47, February.
    11. Brunello, Giorgio & Kiss, David, 2022. "Math scores in high stakes grades," Economics of Education Review, Elsevier, vol. 87(C).
    12. Bianchi, Nicola & Lu, Yi & Song, Hong, 2022. "The effect of computer-assisted learning on students’ long-term development," Journal of Development Economics, Elsevier, vol. 158(C).
    13. Anna Vignoles & Augustin De Coulon & Oscar Marcenaro-Gutierrez, 2011. "The value of basic skills in the British labour market," Oxford Economic Papers, Oxford University Press, vol. 63(1), pages 27-48, January.
    14. Harry Anthony Patrinos, 2022. "Learning loss and learning recovery," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 49(2), pages 183-188, June.
    15. Lex Borghans & Huub Meijers & Bas Ter Weel, 2008. "The Role Of Noncognitive Skills In Explaining Cognitive Test Scores," Economic Inquiry, Western Economic Association International, vol. 46(1), pages 2-12, January.
    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. Ballestar, María Teresa & Mir, Miguel Cuerdo & Pedrera, Luis Miguel Doncel & Sainz, Jorge, 2024. "Effectiveness of tutoring at school: A machine learning evaluation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    2. Borghans, Lex & Meijers, Huub & ter Weel, Bas, 2013. "The importance of intrinsic and extrinsic motivation for measuring IQ," Economics of Education Review, Elsevier, vol. 34(C), pages 17-28.
    3. Liu, Jing & Lee, Monica & Gershenson, Seth, 2021. "The short- and long-run impacts of secondary school absences," Journal of Public Economics, Elsevier, vol. 199(C).
    4. Silke Anger & Bernhard Christoph & Agata Galkiewicz & Shushanik Margaryan & Malte Sandner & Thomas Siedler, 2025. "Online Tutoring, School Performance, and School-to-Work Transitions: Evidence from a Randomized Controlled Trial," Berlin School of Economics Discussion Papers 0084, Berlin School of Economics.
    5. José Manuel Cordero Ferrera & Manuel Muñiz Pérez & Rosa Simancas Rodríguez, 2015. "The influence of socioeconomic factors on cognitive and non-cognitive educational outcomes," Investigaciones de Economía de la Educación volume 10, in: Marta Rahona López & Jennifer Graves (ed.), Investigaciones de Economía de la Educación 10, edition 1, volume 10, chapter 21, pages 413-438, Asociación de Economía de la Educación.
    6. Non, Arjan & Tempelaar, Dirk, 2016. "Time preferences, study effort, and academic performance," Economics of Education Review, Elsevier, vol. 54(C), pages 36-61.
    7. Carmen Lamagna & Sheikh Selim, 2005. "Heterogeneous Students, Impartial Teaching and Optimal Allocation of Teaching Methods," General Economics and Teaching 0503011, University Library of Munich, Germany.
    8. Heckman, James J., 2011. "Integrating Personality Psychology into Economics," IZA Discussion Papers 5950, IZA Network @ LISER.
    9. Borghans, L. & Golsteyn, B.H.H., 2007. "Are courses chosen to reduce skill-deficiencies? an experimental approach," ROA Research Memorandum 001, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    10. Christine de la Maisonneuve & Balázs Égert & David Turner, 2023. "Quantifying the Macroeconomic Impact of COVID-19-Related School Closures through the Human Capital Channel," Economies, MDPI, vol. 11(12), pages 1-14, November.
    11. Sabates, Ricardo & Gutman, Leslie Morrison & Schoon, Ingrid, 2017. "Is there a wage penalty associated with degree of indecision in career aspirations? Evidence from the BCS70," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 8(3), pages 290-301.
    12. Lex Borghans & Bas ter Weel & Bruce A. Weinberg, 2008. "Interpersonal Styles and Labor Market Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    13. Hui Chen & Guanghui Fu & Huiqin Wu & Yao Xiao & Xuan Nie & Wenjin Zhao, 2024. "Sustainable Collaboration and Incentive Policies for the Integration of Professional Education and Innovation and Entrepreneurship Education (IPEIEE)," Sustainability, MDPI, vol. 16(17), pages 1-24, August.
    14. Eisenkopf, Gerald & Hessami, Zohal & Fischbacher, Urs & Ursprung, Heinrich W., 2015. "Academic performance and single-sex schooling: Evidence from a natural experiment in Switzerland," Journal of Economic Behavior & Organization, Elsevier, vol. 115(C), pages 123-143.
    15. Karsten Ingmar Paul & Alfons Hollederer, 2023. "The Effectiveness of Health-Oriented Interventions and Health Promotion for Unemployed People—A Meta-Analysis," IJERPH, MDPI, vol. 20(11), pages 1-19, June.
    16. Humphries, John Eric & Kosse, Fabian, 2017. "On the interpretation of non-cognitive skills – What is being measured and why it matters," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 174-185.
    17. Schurer, Stefanie & Yong, Jongsay, 2012. "Personality, well-being and the marginal utility of income: What can we learn from random coefficient models?," Working Paper Series 18617, Victoria University of Wellington, School of Economics and Finance.
    18. Benjamin Enke & Uri Gneezy & Brian Hall & David Martin & Vadim Nelidov & Theo Offerman & Jeroen van de Ven, 2020. "Cognitive Biases: Mistakes or Missing Stakes?," CESifo Working Paper Series 8168, CESifo.
    19. John Eric Humphries & Fabian Kosse, 2016. "On the interpretation of non-cognitive skills – what is being measured and why it matters," Working Papers 2016-025, Human Capital and Economic Opportunity Working Group.
    20. Carmit Segal, 2012. "Working When No One Is Watching: Motivation, Test Scores, and Economic Success," Management Science, INFORMS, vol. 58(8), pages 1438-1457, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ipt:iptwpa:jrc140539. 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: Publication Officer (email available below). General contact details of provider: https://edirc.repec.org/data/ipjrces.html .

    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.