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Measuring the Impact of a Weeklong Fall Break on Stress Physiology in First Year Engineering Students

2018· article· en· W2892804860 on OpenAlexaffvenueabout
Ayesha Khan, Heather Poole, Elliott A. Beaton

Bibliographic record

VenueThe Canadian Journal for the Scholarship of Teaching and Learning · 2018
Typearticle
Languageen
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsUniversity of OttawaMcMaster University
Fundersnot available
KeywordsRigourPsychologyHumanitiesPopularitySocial psychologyArtPhilosophy

Abstract

fetched live from OpenAlex

Canadian post-secondary institutions are increasingly introducing a fall break into their term calendars, with the stated goal of reducing student stress and improving academic success. We conducted a pilot study around the time of this fall break during which we collected saliva samples to measure the ratio of two metabolic hormones (cortisol and dehydroepiandrosterone (DHEA)) from first-year male engineering students in order to document possible changes in their stress levels before and after the break. Participants self-identified a particular day in the week prior to the break that they considered to be most stressful, followed by a day in the week after the break that was perceived to be equally stress-inducing. A control sample of student engineers was recruited from another university with equivalent academic rigour but without a fall break. Students who experienced the fall break exhibited a marginally lower ratio of cortisol to DHEA after the break than did those who did not experience the break indicating a difference in psychological stress. Since fall breaks are now increasing in popularity, we make the recommendation that it is imperative to empirically investigate their impact on student mental health. Un nombre de plus en plus grand d’établissements post-secondaires introduisent un congé d’automne dans leur calendrier, avec l’objectif déclaré de réduire le stress des étudiants et d’améliorer la réussite académique. Nous avons mené une étude pilote aux alentours de ce congé d’automne au cours duquel nous avons recueilli des échantillons de salive auprès d’étudiants mâles de première année en génie afin de mesurer le ratio de deux hormones métaboliques (le cortisol et la déhydroépiandrostérone - la DHEA)) et pour documenter les changements possibles dans leurs niveaux de stress avant et après le congé. Les participants ont identifié eux-mêmes un jour spécifique de la semaine avant le congé qu’ils considéraient comme étant le plus stressant, suivi par un jour particulier de la semaine après le congé qu’ils percevaient comme étant aussi stressant. Un échantillon témoin d’étudiants en génie a été recruté dans une autre université où la rigueur académique était équivalente mais où il n’y avait pas de congé d’automne. Les étudiants qui ont bénéficié d’un congé d’automne ont manifesté un ratio plus bas de cortisol par rapport à la DHEA après le congé par rapport aux étudiants qui n’avaient pas bénéficié d’un tel congé, ce qui indique une différence de stress psychologique. Étant donné que la popularité des congés d’automne est en augmentation, nous recommandons qu’il est impératif d’établir empiriquement leur impact sur la santé mentale des étudiants.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.044
GPT teacher head0.330
Teacher spread0.286 · 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 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

Citations11
Published2018
Admission routes3
Has abstractyes

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