Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,364

The DOI matches its Crossref record.

Theoretical Foundations of Learning Environments

·2014·Routledge eBooks

Abstract

Theoretical Foundations of Learning Environments describes the most contemporary psychological and pedagogical theories that are foundations for the conception and design of open-ended learning environments and new applications of educational technologies.In the past decade, the cognitive revolution of the 60s and 70s has been replaced or restructured by constructivism and its associated theories, including situated, sociocultural, ecological, everyday, and distributed conceptions of cognition. These theories represent a paradigm shift for educators and instructional designers, to a view of learning as necessarily more social, conversational, and constructive than traditional transmissive views of learning. Never in the history of education have so many different theories said the same things about the nature of learning and the means for supporting it. At the same time, although there is a remarkable amount of consonance among these theories, each also provides a distinct perspective on how learning and sense making occur. This book provides students, faculty, and instructional designers with a clear, concise introduction to these theories and their implications for the design of new learning environments for schools, universities, and corporations. It is well-suited as a required or supplementary text for courses in instructional design and theory, educational psychology, learning, theory, curriculum theory and design, and related areas.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.4324/9781410603203

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.

A few free checks a day · papers already verified open instantly · results are public

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

See all 1,364

Metadata

Venue
Routledge eBooks
Publisher
Routledge
Published
2014-04-08
OpenAlex
W318358118
Cited by
1,364
References
0
FWCI
54.71
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: Theoretical Foundations of Learning Environments. https://app.cochat.ai/papers/10.4324/9781410603203
The paper
Theoretical Foundations of Learning Environments. (2014). Routledge eBooks. https://doi.org/10.4324/9781410603203

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.