Expectations about the application context, not only actual experience at learning, shape generalization breadth¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The authors interpret their three experiments as showing that generalization is affected by expectations about application, consistent with prior evidence that generalization is sensitive to verbal instructions. → Hadar Ram 2024

Evidence¶

Hadar Ram 2024¶

Hadar Ram, Guy Grinfeld & Nira Liberman. (2024). Anticipated variability increases generalization of predictive learning. npj Science of Learning. https://doi.org/10.1038/s41539-024-00269-z

q2 · i? · causal · r2

The authors' own interpretation (type e) in the general discussion, synthesizing the three experiments; it is supported by the experiments' pattern of results rather than by a new statistical test, and cites earlier work showing instructions alter generalization.

"Our experiments show that learning, and more specifically, general- ization may be affected by expectations about application, and not only, as has been shown in past research, by actual experience at learning12,30."

Discussion¶

Learner Variables¶

• Domain Context — predictor: learners who differ on it differ in outcomes

Related Claims¶

• Teachers' expectancy beliefs about successfully using AI applications shape their motivation to use them (theoretical argument). — related
• Adult learners expect AI to support transformative and experiential learning through assumption-challenging simulations, role play, and authentic virtual contexts — related
• Explicitly instructing learners to expect high variability in the application context broadens generalization in a predictive learning task — a narrower finding that bears on this claim