Claims

The Low-Agency condition produced a significantly different mix of preparatory activities than the High-Agency condition

Claim · All claims
Evidence · 1 study · causal r1 · q3
Currency · newest study 2019 · 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 i? The Low-Agency group received significantly fewer problems (p = .001) and WEs (p < .001) but more ErrExs (p < .001) than the High-Agency group. → Xingliang Chen & Antonija Mitrovic & Moffat Mathews 2019

Evidence

Xingliang Chen & Antonija Mitrovic & Moffat Mathews 2019

Xingliang Chen & Antonija Mitrovic & Moffat Mathews. (2019). Investigating the Effect of Agency on Learning from Worked Examples, Erroneous Examples and Problem Solving. International Journal of Artificial Intelligence in Education (2019) 29:396–424. https://doi.org/10.1007/s40593-019-00179-x

q3 · i? · causal · r1

Comparison of completed preparatory task types in the two conditions of the SQL-Tutor study (Table 4); only p-values are printed for these contrasts, no effect sizes.

"The Low-Agency group received significantly fewer problems (p = .001) and WEs (p < .001), but more ErrExs (p < .001) than the High-Agency group."

Discussion

Page metadata
Field Value
type claim
id activity-type-differences-between-conditions
title The Low-Agency condition produced a significantly different mix of preparatory activities than the High-Agency condition
description The Low-Agency condition produced a significantly different mix of preparatory activities than the High-Agency condition
status review
evidence_strength moderate
newest_evidence 2019
generated by process:wiki-ingest on 2026-10-27
trust unverified — no one has confirmed this page's content
sources 1 — xingliang-chen-antonija-mitrovic-moffat-mathews-2019

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