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Record W2900984334 · doi:10.5539/hes.v8n4p162

Teachers’ Attitude towards Teaching of Sexuality Education in Federal Government Colleges in Nigeria - Implications for Counselling

2018· article· en· W2900984334 on OpenAlexvenueno aff
Anna Onoyase

Bibliographic record

VenueHigher Education Studies · 2018
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsHuman sexualityCurriculumSexuality educationGovernment (linguistics)PsychologyPositive attitudeTest (biology)Significant differenceMedical educationMathematics educationPedagogySociologyMedicineSex educationSocial psychologyGender studies

Abstract

fetched live from OpenAlex

The study investigated the attitude of teachers towards the teaching of sexuality education in federal government colleges in Nigeria. In order to carry out the investigation, three hypotheses were formulated. An instrument known as “teachers’ attitude towards teaching of sexuality education” (TATTOSE), was used to obtain information from the respondents. The instrument had a reliability coefficient of 0.79. It also had language appropriateness, content and facial validity. Four research assistants were used to administer 580 copies of the questionnaire to the respondents. Five hundred and twenty eight copies were retrieved showing 91.03 percent return rate. The data collected from the field were analyzed using t-test statistics. The research found out that there was no significant difference in the attitude of male and female teachers towards the teaching of sexuality education, that there was significant difference in the attitude of less experienced and experienced teachers towards the teaching of sexuality education. Finally, the study also revealed that there was no significant difference in the attitude of married and unmarried teachers towards teaching of sexuality education in Nigeria. One of the recommendations is that a curriculum of sexuality education should be drawn up for secondary schools.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.192
GPT teacher head0.539
Teacher spread0.347 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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