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Record W2888745542 · doi:10.5430/ijhe.v7n4p187

Prevalence of Educational Malpractice among University Students as Perceived by Lecturers of Delta State University, Abraka

2018· article· en· W2888745542 on OpenAlexvenueno aff
Anna Onoyase

Bibliographic record

VenueInternational Journal of Higher Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in Education
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaMalpracticeRespondentInternal consistencyPsychologyMedical educationMedicinePerceptionJudgementNonprobability samplingSurvey instrumentFamily medicineClinical psychologyPsychometricsApplied psychologyPopulationEnvironmental health

Abstract

fetched live from OpenAlex

The study examined the prevalence of educational malpractice among University students as perceived by lecturers of Delta State University, Abraka. Three research questions were raised to guide the study. The study is a descriptive survey research. The purposive random sampling technique was used to select a sample of 92 lecturers for the study. The instrument for this study is the questionnaire. The instrument has face and content validity through expert judgement and instrumentation. The Cronbach alpha procedure was used to assess the internal consistency of the items. The value obtained was .73. The results revealed that there is a high prevalence of educational malpractice among undergraduates of Delta State University, Abraka. The findings also revealed that there is no significant difference between lecturers in their perception of the prevalence of educational malpractice among students. Lastly, the result showed that the status of lecturers has no impact on their perception of the prevalence of educational malpractice among students. Implications for counselling practice and education were discussed.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.367
Teacher spread0.357 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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