Interventions longer than one month showed the largest effect size for robot-assisted STEM learning, though duration was not a significant moderator overall¶
Claim · All claims
Evidence · 1 study · quant-synthesisr2·q3·i2medium
Currency · newest study 2024 · 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 subgroup with interventions longer than one month had the largest effect size (g = 0.672, p < 0.001), while shorter durations showed non-significant effects. → Fan Ouyang and Weiqi Xu 2024
Evidence¶
Fan Ouyang and Weiqi Xu 2024¶
Fan Ouyang and Weiqi Xu. (2024). The effects of educational robotics in STEM education: a multilevel meta-analysis. International Journal of STEM Education. https://doi.org/10.1186/s40594-024-00469-4
q3 · i2 · quant-synthesis · r2
Ad hoc subgroup analysis within the non-significant intervention-duration moderator (F(2, 26) = 1.2442, p > 0.05). Interventions over one month yielded g = 0.672 (p < 0.001); durations of ≤ 1 day (g = 0.263) and > 1 day ≤ 1 month (g = −0.040) were not significant.
"the duration length of “> 1 month” (g = 0.672, p < 0.001) had the largest effect size on robot-assisted STEM learning."
Discussion¶
Related Claims¶
- Educational level, instructor support, instructional strategy, interactive type, intervention duration, robotic type, and control group condition were not significant moderators of robotics effects — related
- Interventions lasting one to two months show the largest effect, and effects do not increase consistently with longer duration — related
- Intervention duration significantly moderates Gen-AI's effect on HOT, with the strongest effects at 8–16 weeks (ES = 0.759) and weaker effects for shorter (0.494) and longer (0.372) interventions — related
- The effect of ChatGPT on learning performance is moderated by type of course, learning model, and duration, with problem-based learning and 4–8-week interventions showing the largest effects — related
- Educational robotics has a moderate-to-large effect on students' STEM learning performance — related
- Educational robotics has a moderate positive overall effect on K-16 students' STEM learning compared to non-robotics instruction — related
- Educational robotics shows no significant effect on students' computational thinking in STEM education — related
- Scaffold effects peak at 2–4 weeks of treatment and decrease dramatically for treatments lasting 9–24 weeks — related
- Teacher-supported learning scaffolds show the largest effect (ES = 0.92), and longer intervention durations yield larger effects — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
duration-over-one-month-largest-robotics-effect |
title |
Interventions longer than one month showed the largest effect size for robot-assisted STEM learning, though duration was not a significant moderator overall |
description |
Interventions longer than one month showed the largest effect size for robot-assisted STEM learning, though duration was not a significant moderator overall |
status |
review |
evidence_strength |
weak |
newest_evidence |
2024 |
generated |
by process:wiki-ingest on 2026-10-15 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — fan-ouyang-and-weiqi-xu-2024 |
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