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Record W4311680964 · doi:10.22215/etd/2022-15272

Social Roles in an Experiential Activity in an Undergraduate Neuroscience Course: A Case Study with Emergency Remote Teaching Considerations

2022· dissertation· en· W4311680964 on OpenAlexaffabout
Shana Mantle

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsCarleton University
Fundersnot available
KeywordsExperiential learningConstruct (python library)DisciplinePsychologyClass (philosophy)Thematic analysisExperiential educationPedagogyMathematics educationQualitative researchSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Undergraduate neuroscience students must learn how to effectively produce disciplinespecific genres. Evidence suggests research experience may help students learn to write for discipline-specific purposes; yet a need exists for more widely available methods of research experience than lab experiments. As an investigation into a more available method, this thesis presents a case study of an experiential activity used in a neuroscience writing course at one medium-sized, Canadian university. Using rhetorical genre theory, this study investigated if and how this experiential activity, which took place outside of the lab, helped students discursively construct the social role of researcher and learn how to write for disciplinary purposes. An inductive, thematic analysis of in-class observations, interviews, and open-ended questionnaire responses suggests that the research experience provided by this activity may help neuroscience students bridge the roles of student and professional researcher to effectively write for their discipline, in both physical and virtual environments.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
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 head0.061
GPT teacher head0.398
Teacher spread0.336 · 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 designQualitative
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
Published2022
Admission routes2
Has abstractyes

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