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Record W2309612583 · doi:10.22329/celt.v10i0.4754

Student Time Usage During Fall Reading Week

2017· article· en· W2309612583 on OpenAlexaffvenueabout
Ken Cramer, Rebecca Pschibul

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsWorkloadReading (process)RecreationTime managementPsychologyStress (linguistics)Balance (ability)Applied psychologyComputer science

Abstract

fetched live from OpenAlex

The present study investigated the time usage and relative levels of perceived stress, academic workload, and recreation time for 177 students at a mid-sized Canadian university before, during, and after Fall Reading Week. Across three weeks, and at various times of the day, students received a message to their smartphone to complete a 20-second survey that assessed present activity, and levels of stress, academic workload, and recreation. Results showed that student stress following the break was higher with more stress but less workload prior to reading week, more stress experienced during reading week, more workload following reading week; and more time spent recreating during reading week. Implications for student counselling are outlined, which encourage students to seek a balance in time usage and management. Future directions are discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.316
Teacher spread0.301 · 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

Citations8
Published2017
Admission routes3
Has abstractyes

Explore more

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