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Record W2891171762 · doi:10.31581/jbs-4.2.3(1991)

Developing a Participatory Approach to Learning

2018· article· en· W2891171762 on OpenAlexvenueno aff
Maija Pihlainen

Bibliographic record

VenueThe Journal of Bahá’í Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsnot available
Fundersnot available
KeywordsCitizen journalismValue (mathematics)CurriculumProcess (computing)SociologyMoral educationPedagogyPublic relationsEngineering ethicsMathematics educationPolitical sciencePsychologyComputer scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Beginning with a survey of Bahá’í writings and of emerging Bahá’í approaches to education, the article charts the Macau-based School of the Nations’ philosophy of education and considers its implications for the school’s curriculum development process. The article then proposes that the cooperative approach to education offers a potential instructional model within which Bahá’í principles and ideals, with their emphasis on moral education, participation, cooperation, and consultation, could be effectively implemented. Finally, the article discusses the school’s tentative experiments with this model and the steps taken to begin the model’s systematic implementation. The successful continuation of the project, the article suggests, will largely depend on the school’s ability to overcome the constraints imposed by the dominant competitive attitudes and practices and to gain acceptance of the value of a participatory and cooperative approach. An earlier version of this paper was presented at the Eighth Annual Conference of the Hong Kong Educational Research Association. While the author takes full responsibility for the views expressed here, appreciation and thanks are due to the administration and staff of the School of the Nations who provided inspiration and stimulating ideas that made this paper possible.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.095
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.095
Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0950.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0130.028
Scholarly communication0.0130.009
Open science0.0040.019
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.285
GPT teacher head0.470
Teacher spread0.186 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes1
Has abstractyes

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