Problem-solving competency is one of the core pillars of modern 21st-century education. This skill trains students to think critically, logically, and systematically. However, evidence on the ground indicates that the mathematics performance of Indonesian students generally remains below the international average. Many students experience profound difficulties in comprehending complex problems and formulating effective solution strategies due to the massive volume of information that must be processed by their working memory simultaneously.
Balancing Information Through Cognitive Load Theory
When complex mathematical material is delivered without a well-structured format, students' working memory becomes overloaded. This overload hinders conceptual understanding. Grounded in Cognitive Load Theory, the research team tested two information presentation models designed to minimize students' extraneous cognitive load: the Pre-training strategy and the Segmenting strategy.
- Pre-training Strategy: An instructional model that provides an initial introduction to fundamental concepts or prerequisite material before students engage with the core learning content.
- Segmenting Strategy: An instructional model that divides large learning materials into smaller, structured units presented gradually to facilitate easier information absorption.
Simple and Measurable Experimental Methodology
This quantitative study utilized a $2\times2$ factorial experimental design. The evaluation was carried out on 88 eleventh-grade students at a public senior high school in Banten Province, Indonesia. Using a cluster random sampling technique, the students were divided into two different experimental classes. One class received the pre-training method treatment, while the other class was taught using the segmenting method.
Before the experiment began, the researchers measured each student's level of prior knowledge to classify them into high and low prior knowledge categories. After all learning sessions were completed, the students' mathematical problem-solving abilities were tested through a written essay exam, while their mental effort levels were measured using a cognitive load scale questionnaire.
Key Findings: The Interaction of Prior Knowledge and Material Design
Statistical analysis yielded crucial findings regarding the effectiveness of these two strategies:
- The Dominant Effect of Prior Knowledge: In general, students with a high level of prior knowledge achieved significantly higher mathematical problem-solving scores ($M = 84.71$) compared to students with low prior knowledge ($M = 69.89$). They also experienced much lower levels of cognitive load during the learning process.
- The Effectiveness of the Segmenting Strategy: Presenting material gradually through the segmenting strategy proved highly effective for the high prior knowledge student group. This group achieved the highest average problem-solving score of $87.86$, accompanied by the lowest mental workload level ($M = 4.300$).
- The Value of the Pre-training Strategy: Conversely, for students with low prior knowledge, breaking the material into segments immediately can cause confusion. This group benefited far more from the pre-training strategy (receiving a foundational concept review beforehand), which successfully stabilized their problem-solving performance at an average score of $76.67$.
The analytical results confirm a clear interaction effect between a student's prior knowledge characteristics and the way a teacher structures the instructional design in the classroom.
Broad Implications for Modern Educational Practice
This study carries important practical implications for educators, particularly mathematics teachers. The results highlight that no single instructional strategy fits all types of students perfectly. Teachers are strongly advised against introducing complex topics directly without first mapping out their students' initial baseline capabilities.
For classrooms dominated by students with minimal foundational understanding, prioritizing a review of prerequisite concepts via pre-training is essential. Meanwhile, for highly adaptive classrooms, breaking down textbook content into smaller, structured segments will maximize brain capacity for solving high-level mathematical problems.
Researcher Profiles
- Siti Atfiah, S.Pd.: Lead researcher and academic from Universitas Sultan Ageng Tirtayasa, focusing on instructional media development and secondary mathematics teaching methodologies.
- Dr. Cecep Anwar Hadi Firdos Santosa: Lecturer, mathematics expert, and corresponding author who actively conducts research on Cognitive Load Theory-based instructional design at Universitas Sultan Ageng Tirtayasa.
- Prof. Dr. Hepsi Nindiasari: Professor and senior researcher at Universitas Sultan Ageng Tirtayasa, dedicating her academic career to enhancing students' critical thinking and mathematical problem-solving skills.
Study Reference
- Journal Article Title: The Effect of Prior Knowledge and Instructional Design on Students' Cognitive Load and Mathematical Problem Solving Ability (Found in the file "271-286 Cecep Anwar Hadi Firdos Santosa_Siti Atfiah.pdf")
- Journal Name: International Journal of Advance Social Sciences and Education (IJASSE)
- Publication Year: 2026
- Official DOI / URL Link:
https://doi.org/10.59890/ijasse.v4i3.12 https://journalijasse.my.id/index.php/ijasse
0 Komentar