Students' Perceptions of the Usefulness of Formative Feedback in Mathematics Lessons
Bibliographic record
Abstract
This study aimed to examine students' perceptions of the usefulness of formative feedback in mathematics lessons at Sagnerigu Municipality in the Northern Region of Ghana. Quantitatively, this study employed a descriptive non-experimental survey design. The population comprises all pupils of public Junior High Schools in the Sagnerigu Municipality. A purposive sampling technique was used to select the Junior High School students for the study. The criterion purposive sampling technique was used to select 518 final-year students for the 2022 Basic education certificate examination from 14 schools in Sagnerigu Municipality. The chosen schools comprised 291 students from high-performing schools and 227 students from low-performing schools. The primary tool for the study was the Student Feedback Perception Questionnaire (SFPQ), administered to the student participants. The Descriptive statistical tool was used to analyse the mean and standard deviation of the data. The study's examination of students' perceptions of feedback revealed a moderate level of perceived usefulness. This emphasises the importance of feedback as a tool for student growth and development. However, the findings also suggest the need for further support and guidance to optimise the impact of feedback on student learning outcomes. The findings also suggest that students value feedback that helps them improve their skills and strategies in Mathematics and keeps them on track to succeed. It also highlights the importance of providing different types of feedback to cater to the diverse learning needs of students. Educators can create a conducive environment that promotes student engagement and achievement by equipping teachers with effective feedback techniques, emphasising constructive comments and avoiding grades.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".