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Record W2135962919 · doi:10.3138/jvme.38.3.298

How Do Veterinary Students' Motivation and Study Practices Relate to Academic Success?

2011· article· en· W2135962919 on OpenAlexvenueno aff
Johanna Mikkonen, Mirja Ruohoniemi

Bibliographic record

VenueJournal of Veterinary Medical Education · 2011
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumLongitudinal studyPsychologyMedical educationMathematics educationVeterinary medicinePedagogyMedicine

Abstract

fetched live from OpenAlex

The aim of the present study was to explore the factors associated with veterinary students' study success. All veterinary students who began their studies at the University of Helsinki in 2005 participated in this qualitative longitudinal study (N=52). The data consisted of assignments that the students completed at the beginning of their studies and again after three years of studying. The focus was on differences in motivation and study practices as well as possible changes in these over the three-year period. The students were divided into three groups according to their study success (grade point average and study progress). These groups were compared according to group-level differences in the categorized data. The most successful students already described themselves using more positive words than other students at the beginning of their veterinary studies. In addition, they seemed more adaptive in relation to the study's demands. However, there were drops in both the most and least successful students' motivation during their studies. The findings suggest that it is possible to predict forthcoming study problems by analyzing students' study practices and their own descriptions of themselves as learners. In addition, the results show that veterinary students' high motivation cannot be taken for granted. The comparative and longitudinal perspective of the present study can be useful in the development of curricula and in student support.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.162
GPT teacher head0.456
Teacher spread0.294 · 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

Citations26
Published2011
Admission routes1
Has abstractyes

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