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The impact of a mathematics computer-assisted learning platform on students' mathematics test scores


  • Perera, Marcelo

    () (CINVE, and Facultad de Ciencias Económicas y Administración, Universidad de la República de Uruguay)

  • Aboal, Diego

    () (Facultad de Ciencias Económicas y Administración, Universidad de la República de Uruguay, and Universidad ORT Uruguay)


Since 2013, the Uruguayan educational system has been using an online adaptive learning tool for mathematics: The Mathematics Adaptive Platform (PAM for its Spanish acronym). PAM's content has been adapted to the national curriculum and it is a tool that - based on an analysis of students' experiences - offers personalised feedback according to each student's skill level. The use of PAM has been spreading throughout the education system. By 2016, approximately half of all students in 3rd through 6th grades of primary education had used the platform. The purpose of this study is to identify the effect of the use of PAM on the test score gain in mathematics based on longitudinal data from a sample of students in primary education. The results show a positive effect of 0.2 standard deviations on mathematics test scores. Results also show that the impact of PAM increases as the socioeconomic status of students decreases. There is no heterogeneous impact by gender. This is the first evidence at a country-wide level of the impact of a pedagogical tool of this type.

Suggested Citation

  • Perera, Marcelo & Aboal, Diego, 2019. "The impact of a mathematics computer-assisted learning platform on students' mathematics test scores," MERIT Working Papers 007, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:unumer:2019007

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    References listed on IDEAS

    1. Bulman, G. & Fairlie, R.W., 2016. "Technology and Education," Handbook of the Economics of Education, Elsevier.
    2. Esther Duflo & Pascaline Dupas & Michael Kremer, 2011. "Peer Effects, Teacher Incentives, and the Impact of Tracking: Evidence from a Randomized Evaluation in Kenya," American Economic Review, American Economic Association, vol. 101(5), pages 1739-1774, August.
    3. 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.
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    More about this item


    Evaluation of Computer Assisted Learning systems; Mathematics; Uruguay;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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