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Record W4284888156 · doi:10.53967/cje-rce.v45i2.4959

MakerMinds: An Exploratory Study of Making and Mindfulness Pedagogies

2022· article· en· W4284888156 on OpenAlexaffvenue
Joanne Edmundson, Jennifer Jenson

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2022
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of British ColumbiaYork University
Fundersnot available
KeywordsMindfulnessPsychologyIntervention (counseling)Mental healthExperiential learningMetacognitionExploratory researchQualitative researchQualitative propertyPsychotherapistApplied psychologyPedagogyCognitionSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

The purpose of this ethnographically informed research study was to explore the integration of making and mindfulness pedagogies in a single curricular intervention (“MakerMinds”) and, in particular, how making engages students in mindfulness content and encourages their independent use of mindfulness tools. Mindfulness programs have long been used to promote mental health in clinical and non-clinical settings. Related research with school-aged children is limited, however, and the problem of how to fully engage them in mindfulness programming remains unsolved. Here, we report on the experiences of 24 Grade 4 students in MakerMinds over an eight-week period. Qualitative data from multiple sources revealed a program successful in engaging students and encouraging their application of mindfulness tools as needed in their daily lives. It also positively impacted conceptual and experiential knowledge of mindfulness and developed students’ agentic awareness of themselves as problem-solving makers and nascent mindfulness 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 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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.110
GPT teacher head0.365
Teacher spread0.256 · 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 designQualitative
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

Citations1
Published2022
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Education / Revue canadienne de l éducationSame topicMindfulness and Compassion InterventionsFrench-language works237,207