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Record W2597576010 · doi:10.5539/ass.v13n4p25

Effect of Prevalent Supervisory Styles on Teaching Performance in Kuwaiti High Schools

2017· article· en· W2597576010 on OpenAlexvenueno aff
Sultan Ghaleb Aldaihani

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsSupervisorViewpointsPsychologySample (material)Ideal (ethics)Medical educationMathematics educationPedagogyMedicineManagementPolitical science

Abstract

fetched live from OpenAlex

Purpose: This study sought to identify the importance of supervision in Kuwaiti high schools from the viewpoints of heads of departments and school teachers, as well as identifying the gap between ideal and prevalent supervisory styles in Kuwaiti high schools and determining the effects of supervision on teachers’ professional performance. Methodology: The researcher took a qualitative approach, using structured interviews with a study sample represented by six heads of departments and six teachers from two high schools in Kuwait. Findings: It was found that supervision as a tool for continuous improvement in the school system positively affected the school climate. There was a gap between actual and ideal supervisory styles in the schools studied. Supervision had a positive effect on the professional performance of teachers; supervisors’ notes and observations helped teachers in identifying their shortcomings and modifying their behavior accordingly. Challenges to the effective implementation of supervision in high schools included unsuitable supervisory practices, loss of connection between the teacher and the supervisor, teacher resistance to support, and lack of meaningful feedback. Recommendations: It is necessary to employ advanced supervisory styles in order to cope with the changes in the surrounding environment. Further study will help to determine the effect of supervision on the relationship between teachers and 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.363
Teacher spread0.333 · 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

Citations27
Published2017
Admission routes1
Has abstractyes

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