Students who compared a climate model with non-climate analog models during productive failure scored significantly higher on far across domain transfer than students who used only the climate model¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r1–r2 · q3 · i2 medium
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i2 The Two Models Group significantly outperformed the One Model Group on the far across domain transfer (robot mining) posttest item, with a medium-to-large effect size. → Jacobson 2020 q3 i2 The far transfer advantage held for both the content-expert teacher's classes and the non-expert teachers' classes. → Jacobson 2020 (2)

Evidence¶

Jacobson 2020¶

Jacobson, Michael, Goldwater, Micah, Markauskaite, Lina, Lai, Polly, Kapur, Manu, Roberts, Gareth, & Hilton, Courtney. (2020). Schema abstraction with productive failure and analogical comparison: Learning designs for far across domain transfer. Learning and Instruction, 65, Article number: 101222. https://doi.org/10.1016/j.learninstruc.2019.101222

q3 · i2 · causal · r2

Linear mixed-model analysis of the posttest robot space mining far transfer item in the quasi-experimental two-condition study (96 analyzed students). The Two Models Group (M = 1.231, SD = 0.777) outperformed the One Model Group (M = 0.719, SD = 0.750); a Bayesian t-test gave "BF10 = 0.052" strong evidence and a frequentist test gave "d = 0.672".

"There was a main effect of Condition, with students in the Two Models Group who were exposed to two models significantly outperforming students in the One Model Group, F(1,92) = 10.403, p < .001, η 2 = .11."

Jacobson 2020 (2)¶

Jacobson, Michael, Goldwater, Micah, Markauskaite, Lina, Lai, Polly, Kapur, Manu, Roberts, Gareth, & Hilton, Courtney. (2020). Schema abstraction with productive failure and analogical comparison: Learning designs for far across domain transfer. Learning and Instruction, 65, Article number: 101222. https://doi.org/10.1016/j.learninstruc.2019.101222

q3 · i2 · causal · r1

Follow-up pairwise analyses of the far transfer item showed the Two Models condition won under every teacher: the content expert's Two Model class beat the One Model class (d = 0.654) and the early career non-expert's Two Model class beat the experienced non-expert's One Model class (d = 0.693), so the advantage did "not" depend on teacher expertise.

"It is important to note that the Two Model condition outperformed the One Model condition for both the Content Expert’s class and the Non-expert classes."

Discussion¶

Related Claims¶

• Both treatment groups improved near within domain transfer, but the One Model Group's benefit depended on having a content-expert teacher while the Two Models Group's did not — related
• PF students scored significantly higher than DI students on far transfer (robot mining problem), with an independent teacher experience effect — related