EVALUATING THE GENERATIVE LEARNING STRATEGY (GLS) AND ITS IMPACT ON GRADE 10 STUDENTS' MATHEMATICAL PROBLEM-SOLVING SKILLS

Generative learning is a pedagogical model that emphasizes the active integration of new knowledge with students' existing knowledge. This study aims to (1) determine the level of students' mathematical problem-solving abilities when exposed to the Generative Learning Strategy (GLS) compared to the Non-Generative Learning Strategy (Non-GLS), based on their pre-test and post-test scores, and (2) assess whether there is a significant difference in these abilities between the two groups. A quasi-experimental design was employed, selecting research participants based on their mean scores from the second grading periodical exam. The results indicated that both the GLS and Non-GLS groups initially scored at the "poor" level in the pre-test. Following the intervention, the GLS group achieved an "average" level, while the Non-GLS group fell between "below average" and "average." Although analyses revealed a significant difference between the two groups concerning the pre-test scores when used as a covariate, the post-test results showed no significant difference in students' mathematical problem-solving abilities between those exposed to GLS and those exposed to Non-GLS. Both groups demonstrated competent problem-solving skills, yet the GLS group exhibited greater variability in performance. Consequently, the study concludes that the Generative Learning Strategy does not yield a significant improvement in students' mathematical problem-solving abilities. Factors influencing the lack of significant difference include the simplicity of the GLS application, where students generate predictions based on prior knowledge, enhancing learning even when knowledge is limited. Additionally, the role of student confidence is crucial, as retrieval failures with high confidence can lead to improved learning outcomes. The findings underscore the potential of both instructional strategies to yield positive results in mathematical proficiency. Recommendations for practice include broader implementation of GLS across subjects, ongoing professional development for educators, and tailored support for students requiring additional assistance. Overall, this study contributes to the understanding of effective teaching methods in mathematics and emphasizes the importance of engaging students in their learning processes.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-18
DOI
https://doi.org/10.5281/zenodo.15242100
Primary Topic
Mathematics Education and Pedagogy
Type
article
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article

EVALUATING THE GENERATIVE LEARNING STRATEGY (GLS) AND ITS IMPACT ON GRADE 10 STUDENTS' MATHEMATICAL PROBLEM-SOLVING SKILLS

Zenodo (CERN European Organization for Nuclear Research)
Mathematics Education and Pedagogy
article

EVALUATING THE GENERATIVE LEARNING STRATEGY (GLS) AND ITS IMPACT ON GRADE 10 STUDENTS' MATHEMATICAL PROBLEM-SOLVING SKILLS

article en

Abstract

Generative learning is a pedagogical model that emphasizes the active integration of new knowledge with students' existing knowledge. This study aims to (1) determine the level of students' mathematical problem-solving abilities when exposed to the Generative Learning Strategy (GLS) compared to the Non-Generative Learning Strategy (Non-GLS), based on their pre-test and post-test scores, and (2) assess whether there is a significant difference in these abilities between the two groups. A quasi-experimental design was employed, selecting research participants based on their mean scores from the second grading periodical exam. The results indicated that both the GLS and Non-GLS groups initially scored at the "poor" level in the pre-test. Following the intervention, the GLS group achieved an "average" level, while the Non-GLS group fell between "below average" and "average." Although analyses revealed a significant difference between the two groups concerning the pre-test scores when used as a covariate, the post-test results showed no significant difference in students' mathematical problem-solving abilities between those exposed to GLS and those exposed to Non-GLS. Both groups demonstrated competent problem-solving skills, yet the GLS group exhibited greater variability in performance. Consequently, the study concludes that the Generative Learning Strategy does not yield a significant improvement in students' mathematical problem-solving abilities. Factors influencing the lack of significant difference include the simplicity of the GLS application, where students generate predictions based on prior knowledge, enhancing learning even when knowledge is limited. Additionally, the role of student confidence is crucial, as retrieval failures with high confidence can lead to improved learning outcomes. The findings underscore the potential of both instructional strategies to yield positive results in mathematical proficiency. Recommendations for practice include broader implementation of GLS across subjects, ongoing professional development for educators, and tailored support for students requiring additional assistance. Overall, this study contributes to the understanding of effective teaching methods in mathematics and emphasizes the importance of engaging students in their learning processes.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 42%
Mathematics Education and Pedagogy
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EVALUATING THE GENERATIVE LEARNING STRATEGY (GLS) AND ITS IMPACT ON GRADE 10 STUDENTS' MATHEMATICAL PROBLEM-SOLVING SKILLS · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS