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Record W1490720297 · doi:10.5430/wje.v5n3p121

Factor Analytic Study of Lecturer’s Teaching Assessment Scale in Obafemi Awolowo University, Nigeria

2015· article· en· W1490720297 on OpenAlexvenueno aff
Olu Philip Jegede, Bamidele Abiodun Faleye, Emily Oluseyi Adeyemo

Bibliographic record

VenueWorld Journal of Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaPsychologyConstruct validityReliability (semiconductor)Internal consistencyScale (ratio)Spearman's rank correlation coefficientValidityStatisticsPsychometricsMathematicsCartographyClinical psychologyPhysicsGeography

Abstract

fetched live from OpenAlex

This study presents a validation report of the Lecturer’s Teaching Assessment Scale (LTAS) developed for theassessment of lecturer’s teaching effectiveness in Obafemi Awolowo University, Ile-Ife, Nigeria. It also examinedthe factor structure of the LTAS, its construct validity, and internal consistency reliability coefficients. The studyadopted the survey research design. A total of 13,000 students that completed the LTAS online constituted thesample for the study. The 34-item LTAS was used to collect data for the study. Collected data were subjected toreliability and factor analyses. Results showed that the LTAS has two subscales - Attitude to Teaching and LecturePresentation and Organisation. The LTAS was adjudged to possess construct validity, and it was established throughexperts’ judgement. The results also revealed that the LTAS was reliable (Cronbach Alpha reliability coefficient of0.985, Spearman Brown’s Split-half reliability coefficient of 0.998 and Gutman’s Split-half coefficient of 0.997).Thus, the LTAS possessed adequate psychometric qualities that make it suitable for use among Nigerianundergraduate 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.058
GPT teacher head0.396
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2015
Admission routes1
Has abstractyes

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