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  • Computer Assisted Learning  (1)
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  • 1
    Sprache: Englisch
    Seiten: 1 Online-Ressource (30 pages)
    Paralleltitel: Erscheint auch als Angel-Urdinola, Diego Can Digital Personalized Learning for Mathematics Remediation Level the Playing Field in Higher Education? Experimental Evidence from Ecuador
    Schlagwort(e): Computer Assisted Learning ; Digital Personalized Learning ; Education ; Higher Education ; Mathematics Remediation ; Stem Education ; Teaching at the Right Level
    Kurzfassung: Many Ecuadorian students entering higher education have cognitive skills gaps in mathematics that undermine their ability to assimilate academic contents. This paper presents the results of a randomized controlled trial assessing the effects on academic outcomes of a Digital Personalized Learning Software for mathematics remediation (the ALEKS software) offered to first-year students entering technical and technological higher education programs in Ecuador amid the COVID-19 pandemic. The possibility to use the software led to a large and marginally significant decline in the probability of repeating a course, as well as a very large positive impact on standardized test scores in math. The analysis finds no impact on the probability of enrolling in the third semester. When disaggregating the impacts, the findings show that the effects on repetition are particularly large for male students, possibly because of higher male enrollment in science, technology, engineering, and mathematics disciplines. When assessing the potential mechanisms, the findings show evidence that the software led to a net increase in hours dedicated to studying mathematics. The results suggest that Digital Personalized Learning Software can be a cost-effective solution for math remediation with potential for large-scale application
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