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Record W7132944119

Assessing the Possibility of Anxiety Reduction and Identity Enhancement in Science, Technology, Engineering, and Mathematics Education Through a Mindfulness-Based Intervention

2024· dissertation· W7132944119 on OpenAlexaffabout
Ryan Nelson McCoy

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFeelingFocus groupIntervention (counseling)MindfulnessAnxietyPsychological resilienceIdentity (music)Self-esteemSelf-efficacy
DOInot available

Abstract

fetched live from OpenAlex

This mixed methods study examined the efficacy of the Learning to BREATHE mindfulness-based program to improve STEM learning resilience of a small group of high school students (~ 10) from diverse backgrounds in Nova Scotia, Canada. The 8-week study was situated within critical mindfulness and used both pre-post surveys and a focus group discussion to assess the intervention.The results suggest that this program may not significantly reduce feelings of math and science anxiety in high school (d = 0.10 and d = 0.15, respectively), but that for some students, it may be helpful for reducing stress/anxiety before and during STEM tests. Additionally, this program may significantly improve STEM identity (d = 0.94) by changing study habits, increasing focus on one’s own feelings toward STEM and one’s abilities in those subjects, and by increasing confidence in one’s STEM abilities.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.414
Teacher spread0.392 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes2
Has abstractyes

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