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Record W4417191732 · doi:10.1108/978-1-68123-842-5

Holistic Education and Embodied Learning

2017· book· en· W4417191732 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsnot available
Fundersnot available
KeywordsEmbodied cognitionVisionContext (archaeology)Variety (cybernetics)ExpansiveHolistic educationMeditationExperiential learning

Abstract

fetched live from OpenAlex

Learning often begins with an experience in the body. Our body can tighten or feel expansive depending on different learning contexts. This experience of learning in the body is crucial to holistic education. This book explores embodied learning from several perspectives.This first section explores how psychology can inform us about embodied learning; for example, the work of Carl Jung and Wilhelm Reich devoted much of their thinking to how energy manifests itself in the body. Meditation and movement are also examined as ways of embodied learning; for example, Dalcroze, a form of movement education, is presented within the context of whole person education. The book also presents schools where embodied learning is nurtured. Waldorf education is discussed as well as a public school in Toronto where the body is central to holistic education. The book also presents visions of embodied learning. John Miller presents a holistic vision of teacher education and Tobin Hart, who has written extensively in this field, writes about the embodied mind.Embodied learning is an emerging area of inquiry in holistic education and this book presents a variety of perspectives and practices that should be helpful to both scholars and practitioners.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.270
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.395
Teacher spread0.353 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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