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Record W2092124011 · doi:10.1187/cbe.13-06-0124

Longitudinal Study of Student Attitudes in a Biology Program

2014· article· en· W2092124011 on OpenAlexaff
Malin J. Hansen, Gülnur Bírol

Bibliographic record

VenueCBE—Life Sciences Education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMemorizationMathematics educationCorrelationLongitudinal studyPsychologyPositive correlationMedical educationDemographyMathematicsMedicineStatisticsInternal medicineSociology

Abstract

fetched live from OpenAlex

This is among the first longitudinal studies to report student attitudes across 4 yr of a university program. We found that the attitudes of students in biology become significantly more expert-like from the first year to the fourth year of the program, that is, there was a significant positive shift in students' overall percent favorable scores from 64.5 to 72%, as opposed to the expert response, which averaged 90%. There was a significant positive shift for the real world connection category (78-85%), the enjoyment (personal interest) category (74-82%), and the conceptual connections/memorization category (66-74%). Moreover, there was a significant correlation between students' overall percent favorable scores and performance (cumulative grade point average) at the end, but not at the beginning, of the fourth year, with high-performing students having significantly more expert-like attitudes than low-performing students. The correlation between percent favorable score and performance was the strongest for the problem solving: synthesis and application category, in which the highest-performing students finished their fourth year with 90% favorable compared with 35% favorable for the lowest-performing students. A comparison of these results with previously reported results and their implications for teaching 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)0.004
metaresearch head score (Gemma)0.001
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 score0.073
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
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.179
GPT teacher head0.556
Teacher spread0.377 · 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

Citations21
Published2014
Admission routes1
Has abstractyes

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