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WHICH MOTIVATIONAL BEHAVIORS IMPACT SUCCESS IN A FOUNDATIONAL ANATOMY COURSE FOR ENTRY DOCTOR OF PHYSICAL THERAPY STUDENTS?

2021· article· en· W3193987093 on OpenAlexaff
Philip A. Fabrizio, Anne Agur, Shannon Groff

Bibliographic record

VenueRevista Argentina de Anatomía Clínica · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyRemedial educationTest anxietyMedical educationSelf-efficacyTest (biology)AnxietyGoal orientationTask (project management)Clinical psychologyMathematics educationSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Objectives: The motivational behavior of self-efficacy for learning and performance was correlated with academic success in Doctor of Physical Therapy (DPT) students taking clinical anatomy, the first foundational course in the program. Students’ motivation strategies have been reported to be important factors in academic success, however, these strategies have not been investigated in DPT students. Therefore, the purpose of this study was to determine if course grade in clinical anatomy was correlated with the motivation subscales of the Motivated Strategies for Learning Questionnaire (MSLQ). Materials and Methods: The MSLQ was administered to thirty-three first-year DPT students who consented to participate in the study. Correlation (Pearson r zero order) between the subscales and final course grade in clinical anatomy were determined. Results: Self-efficacy for learning and performance was correlated with course grade (r(31) = .44, p < .05), while intrinsic and extrinsic goal orientation, task value, control of learning beliefs, and test anxiety, were poorly correlated. Conclusions: The results of the current study, indicating that self-efficacy for learning and performance is correlated with academic success, could be utilized in DPT programs to broaden admission processes, and aid in the development of remedial curricular and teaching strategies to support students identified with poor self-efficacy for learning and performance.

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)0.001
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 score0.015
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.426
Teacher spread0.407 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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Same venueRevista Argentina de Anatomía ClínicaSame topicInnovations in Medical EducationFrench-language works237,207