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Record W2920994034 · doi:10.5430/jnep.v9n6p88

Know thy student: Using a graduate student learning assessment questionnaire

2019· article· en· W2920994034 on OpenAlexvenueno aff
Melinda Hermanns, Danice B. Greer

Bibliographic record

VenueJournal of Nursing Education and Practice · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsDemographicsAutonomyMedical educationPsychologyPerceptionComputer-assisted web interviewingGraduate studentsPedagogyMedicineSociology

Abstract

fetched live from OpenAlex

Background: Creating an online learning environment for today’s adult learner that is engaging and conducive to meeting the various needs can be a challenge for any educator, new or seasoned. Understanding the students’ perspectives of what they need from faculty to be successful is underexplored. Therefore, the purpose of this study was to describe the students’ perspectives of their learning needs and motivation as reported in a faculty developed Graduate Student Learning Assessment Questionnaire (GSLAQ).Methods: A cross-sectional descriptive survey design was employed and consisted of 120 non-traditional adult learners in graduate nursing school. The demographics are as follows: 100 females (83.3%) and 20 males (16.7%) with a mean age of 34.9 years.Results: Five themes emerged: (1) motivation, (2) time orientation, (3) autonomy/role change, (4) caring, and (5) authentic engagement/communication.Conclusions: Understanding students’ concerns as well as their perceptions of what they need from faculty to be successful enables faculty to better communicate with the students as well as provide the needed support as expressed by the students.

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)0.009
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.244
GPT teacher head0.605
Teacher spread0.361 · 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 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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