Claims

Achievement across the four instructional units followed a non-linear, sinusoid-like pattern with a pronounced drop in the final measure, and a non-linear latent growth model fit better than a linear one

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2015 · not yet checked against its sources · not reviewed by a person

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.

q2 i? Mean achievement was rather flat across the first three measures and dropped markedly on the fourth, attributed to the increasing complexity of learning unit 4. → Angel Blanch 2015

Evidence

Angel Blanch 2015

Angel Blanch. (2015). Evaluating fluid and crystallized abilities in the performance of an educational process. Springer Verlag. http://hdl.handle.net/10459.1/48328

q2 · i? · associational · r1

Descriptive analysis of the four achievement means and variances in the BURN11 dataset. The article attributes the drop in the last measure to the increasing difficulty of learning unit 4, where the full Xenograde System was presented.

"Figure 1 shows the means and variances, indicating that the achievement growth process fluctuated across the four observation points as a sinusoid-like pattern, with a rather flat growth in the first three achievement measures, and with a pronounced drop in the last achievement measure."

Discussion

Page metadata
Field Value
type claim
id nonlinear-achievement-growth-pattern
title Achievement across the four instructional units followed a non-linear, sinusoid-like pattern with a pronounced drop in the final measure, and a non-linear latent growth model fit better than a linear one
description Achievement across the four instructional units followed a non-linear, sinusoid-like pattern with a pronounced drop in the final measure, and a non-linear latent growth model fit better than a linear one
status review
evidence_strength moderate
newest_evidence 2015
generated by process:wiki-ingest on 2026-10-18
trust unverified — no one has confirmed this page's content
sources 1 — angel-blanch-2015

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