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Record W2923976936

A National Survey on Pre-Service Teachers’ Stress-Management and Well-Being Needs

2019· article· en· W2923976936 on OpenAlexaffabout
Bilun Naz Böke, Stephanie Zito, Isabel Sadowski, Dana Carsley, Nancy L. Heath

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2019
Typearticle
Languageen
FieldPsychology
TopicStress and Burnout Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsStressorStress managementFeelingWorkloadMedical educationPsychologyService (business)CurriculumStress (linguistics)Time managementClassroom managementMedicinePedagogyClinical psychologyBusinessComputer scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Despite substantial evidence of teachers’ challenges with stress and well-being, there is a lack of stress-management or well-being enhancement training at the pre-service level. The present study sought to examine the specific needs of pre-service teachers in the area of stress-management and well-being in an effort to inform the development of programs to address these needs. A total of 307 pre-service teachers in their final year from 12 universities across Canada participated in the online needs assessment survey. Students were asked questions related to their anticipated stressors for the teaching profession, their preferred training in the area of stress-management and well-being, as well as their preferred method of delivery for this training. Commonly anticipated stressors included their own expectations regarding their performance as a teacher, workload, and feeling responsible for students’ success. Overall, 93% of pre-service teachers rated the need for stress-management training as important. Similarly, a majority indicated that training around self-care (86%) and emotion regulation (84%) would be important components of teacher preparation and 50% indicated that this training should be delivered as a mandatory course within any pre-service curriculum. These findings will be used to develop a skills-based stress-management and well-being program for pre-service teachers.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.051
GPT teacher head0.347
Teacher spread0.297 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venue2019 Conference of the Canadian Society for the Study of EducationSame topicStress and Burnout ResearchFrench-language works237,207