The Effects of Peer Tutoring on the Mathematics Academic Achievement of Grade 10 Students: A Basis for Intervention Program
Notice bibliographique
Résumé
Abstract : Students with difficulties learning mathematics can be found in almost every classroom. Hence, many educators are constantly striving to improve their students’ classroom achievement. One potential solution is using peer tutoring. This research focused on the effects of peer tutoring on students’ academic achievement in learning Mathematics. Five research questions and Four hypotheses were formulated to guide the study. This study utilized the pretest-posttest with control group quasi-experimental research design, involving a sample of 60 Grade 10 students of University of La Salette Inc. High School who were selected based on their 2nd quarter grade. Simple random sampling by fishbowl technique was also employed to assign students to either control or experimental group, and the same method was employed in pairing the students. The experimental group received peer tutoring, while the control group was taught using the conventional lecture method. To gather data for analysis, a researcher made questionnaire Mathematics Students Achievement Test (MAT) was crafted based on the 3rd quarter lessons as stipulated in the curriculum guide set by DEPED and validated by five experts, demonstrating a reliability index of 0.792 as determined by Kuder – Richardson formula (KR-20) which means reliable. After five weeks of intervention, post-test was given to both groups to measure and assess learnings and effectiveness of peer tutoring. The post-test was just similar to the pretest. The result of the post-test was recorded and compared with the results of the pre-test to see if there is an increase in the scores of the students and to determine the effect of the intervention in the achievement of the students in Mathematics. The data were analyzed using mean, standard deviation, paired sample t-test, and t-test for independent which were tested at 0.05 level of significance. Moreover, Cohen’s d was also used to determine the effect size of the peer tutoring. The result of the findings unveiled that the participants to both group, control and experimental group showed that there is a significant difference occurred in students’ academic achievement which means that there is an improvement in the academic achievement of students after the interventions. However, students who were exposed to peer tutoring with Cohens d= 1.07 (large effect) achieved higher scores and exhibited notably superior performance compared to those who exposed to the traditional talk and chalk teaching method with Cohens d= .483 (small effect) which implies that even if there is a significant difference of the scores of the students exposed to traditional teaching, the effect size indicates that there is only a small effect or small improvement. In connection to the findings, the study recommends that teachers should explore more strategies and interventions that will help students in learning mathematics to achieve better academic achievement in the said subject. And since, peer tutoring demonstrated greater effectiveness and contributed to heightened mathematics achievement compared to conventional teaching methods, it is recommended that mathematics educators should embrace and adopt this as an intervention program to help students improve their academic achievements in Mathematics. Future researchers should encompass a larger sample size, different research locations, and additional factors that were not considered in the present study. Moreover, other techniques that help students perform better in mathematics should be explored.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».