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Record W2912993379 · doi:10.11575/jet.v45i2.52226

The Application of a Strength-Based Approach of Students' Behaviours to the Development of a Character Education Curriculum for Elementary and Secondary Schools

2018· article· en· W2912993379 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUniversity of Calgary · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicValues and Moral Education
Canadian institutionsMemorial University of NewfoundlandLakehead University
Fundersnot available
KeywordsCharacter (mathematics)OperationalizationCurriculumCharacter educationCharacter developmentPsychologyMathematics educationPedagogyCharacter traitsSocial psychologyEpistemologyMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Character education programs have gained increasing interest in the past decade and are designed to produce students who are thoughtful , ethical, morally responsible, community oriented, and self-disciplined. However, curriculums to develop character education programs have not always been readily embraced by either educators or students. Character is diffuse, abstract, and global and is not easily operationalized into lesson plans. Personal strengths of students, on the other hand, are important aspects of character that have the added advantage of being concrete, specific, and experiential. In this paper, it is argued that by developing a curriculum of character education that is based upon students' strengths in multiple domains of functioning, it is possible to achieve the goals of character education.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.429

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)0.0000.000

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 head0.013
GPT teacher head0.299
Teacher spread0.285 · 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