Enhancing Interest Among Senior Secondary Students in Expository Essay Writing in South East Nigeria: The Reciprocal Peer Tutoring Approach
Bibliographic record
Abstract
The study focused on investigating the impact reciprocal peer tutoring teaching approach has in promoting interest among senior secondary school students in writing expository essay in Igbo –Etiti Local Government Area, South-East, Nigeria. The effect of gender in promoting interest in expository essay writing among senior secondary school students was also investigated. Two research questions and three null hypotheses guided the study. The study adopted a quasi- experimental design. 75 (32 males and 43 females) in two intact classes consisted of the sample for the study. Expository Essay Writing Interest Inventory (EEWII) which was face validated by four consultants was used as an instrument to data for the study. Mean, standard deviation and analysis of covariance (ANCOVA) were used to analyze the data collected. Results obtained revealed that reciprocal peer tutoring teaching approach was effective in promoting interest in expository essay among the students. The result also indicated that the variation in the mean interest scores of male and female students in expository essay was not significant. The interaction effect of gender and the teaching approach on mean interest scores of senior secondary school students in expository essay writing was also not significant. Hence, the researchers recommended that secondary school teachers should adopt this teaching approach for expository essay writing teaching in secondary schools.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".