Claims

Unguided inquiry students overestimate their hypothesis quality in the transfer task more than video modeling students

Claim · All claims
Evidence · 1 study · causal r3 · q3 · i2 medium
Currency · newest study 2022 · 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.

q3 i2 The three groups differed in monitoring accuracy (bias) for hypothesis quality in the transfer task (η2 = 0.09), with control participants overestimating their hypothesis quality relative to VMP and VM participants. → Omarchevska 2022

Evidence

Omarchevska 2022

Omarchevska, Y., Lachner, A., Richter, J., & Scheiter, K. (2022). Do Video Modeling and Metacognitive Prompts Improve Self-Regulated Scientific Inquiry? Educational Psychology Review. https://doi.org/10.1007/s10648-021-09652-3

q3 · i2 · causal · r3

Exploratory one-way ANOVA on monitoring accuracy (bias) for hypothesis quality in the transfer task: "The three groups differed significantly in monitoring accuracy regarding hypothesis quality" (η2 = 0.09). Bias scores were computed from retrospective confidence judgments minus performance scores.

"The three groups differed significantly in monitoring accuracy regarding hypothesis quality, F(2, 122) = 5.68, p = 0.004, η2 = 0.09."

Discussion

Page metadata
Field Value
type claim
id control-overestimates-hypothesis-quality-transfer
title Unguided inquiry students overestimate their hypothesis quality in the transfer task more than video modeling students
description Unguided inquiry students overestimate their hypothesis quality in the transfer task more than video modeling students
status review
evidence_strength moderate
newest_evidence 2022
generated by process:wiki-ingest on 2026-10-21
trust unverified — no one has confirmed this page's content
sources 1 — omarchevska-2022

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