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Record W4399376280 · doi:10.3998/tia.5214

Supporting student mental health while enhancing self-care: Evaluating the efficacy of a Graduate Teaching Assistant training module

2024· article· en· W4399376280 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTo improve the academy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsComputer science

Abstract

fetched live from OpenAlex

Given the unique proximity and approachability of graduate teaching assistants (GTAs) to students, training GTAs to support student mental health is critical. However, GTAs play dual roles as educators and students, who face their own stress and mental health challenges. This study examined the efficacy of an online module for GTAs focused on how to offer support to students while considering their own self-care. Using an online survey, GTAs’ beliefs (feelings of preparedness, and sense of responsibility) and responses (supportive behaviors) to scenarios of students in distress were examined. Participants also completed a measure of self-care. Compared with a general sample of GTAs who had not participated in the module (n = 111), module participants (n = 42) had higher intentions, felt more responsibility, and felt more prepared to support students in distress. They also reported higher levels of self-care. This study shows training can not only be effective at enhancing GTAs’ ability to support undergraduate student mental health but also positively impact their own self-care.

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.

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)0.013
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.119
GPT teacher head0.448
Teacher spread0.329 · 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