The DOI matches its Crossref record.
Cultural Foundations of Learning: East and West
Abstract
Western and East Asian people hold fundamentally different beliefs about learning that influence how they approach child rearing and education. Reviewing decades of research, Dr Jin Li presents an important conceptual distinction between the Western mind model and the East Asian virtue model of learning. The former aims to cultivate the mind to understand the world, whereas the latter prioritizes the self to be perfected morally and socially. Tracing the cultural origins of the two large intellectual traditions, Li details how each model manifests itself in the psychology of the learning process, learning affect, regard of one's learning peers, expression of what one knows and parents' guiding efforts. Despite today's accelerated cultural exchange, these learning models do not diminish but endure.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Reexamining the Verbal Environments of Children From Different Socioeconomic Backgrounds
Sperry, D. E., Sperry, L. L., & Miller, P. J. (2019) · Child Development · doi:10.1111/cdev.13072 · Cited by 384
Liu, Y., Hau, K., Liu, H., Wu, J., Wang, X., & Zheng, X. (2020) · Journal of Personality · doi:10.1111/jopy.12512 · Cited by 139
A fine-grained comparison of pragmatic language understanding in humans and language models
Hu, J., Floyd, S., Jouravlev, O., Fedorenko, E., & Gibson, E. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2023.acl-long.230 · Cited by 78
Social Support in Two Cultures: Everyday Transactions in the U.S. and Empathic Assurance in Japan
Morling, B., Uchida, Y., & Frentrup, S. (2015) · PLOS ONE · doi:10.1371/journal.pone.0127737 · Cited by 40
Metadata
- Authors
- Li, J.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2012-03-26
- OpenAlex
- W4237236107
- Cited by
- 379
- References
- 0
- FWCI
- 19.90
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cultural Foundations of Learning: East and West. https://app.cochat.ai/papers/10.1017/cbo9781139028400
- The paper
- Li, J. (2012). Cultural Foundations of Learning: East and West. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9781139028400
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.