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Record W2979552746 · doi:10.5539/hes.v9n4p112

Undergraduate Research Supervision: A Case Study of Supervisors' Perceptions at Yanbu University College

2019· article· en· W2979552746 on OpenAlexvenueno aff
Suzan Hasan Al-Doubi, Hala Fawzi, JoDee Walters

Bibliographic record

VenueHigher Education Studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsExploratory researchPerceptionMedical educationPsychologySet (abstract data type)Process (computing)Quality (philosophy)MedicineSociologyComputer science

Abstract

fetched live from OpenAlex

This exploratory case study examined supervisors' perceptions of supervision of undergraduate research projects, and whether the level of experience affects the quality of the supervision process. Data were collected through questionnaires and interviews. Participants were three supervisors with varying levels of experience in the supervision process at Yanbu University College in Saudi Arabia. Obtained themes were used with the whole data-set. The data were rearranged according to the emerged common themes among the three participants. Findings revealed that the level of experience affected the supervision process in relation to the supervisors‘ perceptions. It also suggested that the level of expereince of the supervisors influnced the process of supervision and the feedback given to the undergraduate students. An implication of these findings is that providing novice supervisors with training and guidance should be considered. Departments should create a discussion platform between experienced and novice supervisors to ensure that the supervision expereince is well delivered to undergraduates during their research projects. The study recommends supervisors to revisit all phases of their practice.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.521
GPT teacher head0.601
Teacher spread0.080 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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