Claims

The number of prompts children needed during training predicted mathematics and technical reading achievement, while static pre- and post-test scores did not

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person
Design limits · Kirsten W. J. Touw 2019: no comparison group (read from the study by two models, 2026-10-29)

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q3 i? In ordinal regressions for the training condition, the dynamic prompts measure significantly predicted Cito mathematics (χ²(1) = 5.97, p = 0.015) and technical reading (χ²(1) = 3.91, p = 0.048), with negative coefficients. → Kirsten W. J. Touw 2019 q3 i? Pre-test and post-test scores showed no significant relation with mathematics or technical reading scores. → Kirsten W. J. Touw 2019

Evidence

Kirsten W. J. Touw 2019

Kirsten W. J. Touw, Bart Vogelaar, Merel Bakker, Wilma C. M. Resing. (2019). Using electronic technology in the dynamic testing of young primary school children: predicting school achievement. Education Tech Research Dev. https://doi.org/10.1007/s11423-019-09655-6

q3 · i? · causal · r2

Ordinal regression analyses for the training condition only (mathematics N = 79, technical reading N = 77), with pre-test, post-test and prompts as predictors. Fewer prompts needed related to higher odds of a higher mathematics score; for technical reading the prompts coefficient was −0.077 (p = 0.048).

"The parameter estimates showed a significant relationship between the number of prompts (dynamic measure) and mathematic scores (χ 2 (1) = 5.97, p = 0.015). The coefficient was negative (− 0.093)"

Discussion

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