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Many students exhibit significant mathematics deficits by the end of elementary school, risking difficulties in secondary education. This study evaluated an adaptive e-learning program, used alone or with small-group tutoring, in a cluster-randomized field experiment using an analytic sample of 1044 fifth graders in 61 classes (from an initial sample of 1393 students), with three measurement occasions over one school year. Regarding procedural arithmetic knowledge, both intervention groups showed delayed effects on division, whereas a small multiplication effect emerged only for the single intervention; addition effects were marginal in both conditions, and subtraction effects were, at most, marginal for the single intervention alone. The combined intervention showed limited evidence of effects on conceptual knowledge, and neither intervention produced effects on motivational outcomes. The findings highlight both the potential and the limitations of these intervention formats for supporting at-risk students. Implications for scaling, given limited financial and human resources, are discussed. Educational relevance statement Many students arrive at secondary school with significant gaps in their mathematical skills, putting them at risk of falling further behind as academic demands increase. To address this challenge, we tested two intervention approaches in a large-scale experiment with over 1000 fifth graders: an adaptive e-learning program for practicing basic arithmetic and, for the lowest-achieving students, additional small-group tutoring delivered by trained student teachers. Both approaches showed small, selective effects on students' basic arithmetic skills—most consistently, a delayed improvement in division—whereas effects on students' conceptual knowledge and motivational outcomes were limited. Taken together, our findings highlight both the potential and the limitations of combining scalable digital tools with targeted, structured tutoring, pointing to the need for further research on how such approaches can be optimized for students at risk of falling behind in mathematics.
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Carstensen et al. (2026) studied this question.
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