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Record W4412825359 · doi:10.1128/jmbe.00115-25

Perspectives of graduate student teaching assistants on value and meaning in their role

2025· article· en· W4412825359 on OpenAlexaff
N. J. Westwood, Diane S. Srivastava

Bibliographic record

VenueJournal of Microbiology and Biology Education · 2025
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMeaning (existential)PedagogyThematic analysisGraduate studentsValue (mathematics)PsychologyQualitative researchSociologyMathematics educationComputer science

Abstract

fetched live from OpenAlex

There is increasing reliance on graduate student teaching assistants (GTAs) in undergraduate education, yet the impact of this role on graduate students is understudied. Previous research has focused on tangible outcomes such as skill development, rather than how GTAs value or find meaning in this role. Our study used a phenomenological approach rooted in self-determination theory to allow graduate students to describe their own experience of being GTAs and how they found value and created meaning through their role. We conducted interviews with five GTAs and used thematic analysis to describe their experiences. Generally, GTAs found the experience to be an important and positive aspect of their graduate program, intentionally using the experience to explore potential career paths and find belonging in the wider academic community. However, GTAs also identified several challenges, including pressure to exceed their contracted hours, and some GTAs saw these challenges as ethical dilemmas that were difficult to resolve. Overall, our study demonstrates the deep mindfulness that GTAs use when reflecting on their experiences and making choices within their role. Given the reflection that GTAs bring to their role, we recommend that those who train and work with GTAs actively support their professional development through centering GTA needs in order to enhance the experience of GTAs in the classroom.

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 score0.122
Threshold uncertainty score0.261

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 head0.026
GPT teacher head0.359
Teacher spread0.333 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

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