The Example-Based Cognitive Load Control Learning Model to Improve the Effectiveness of Biotechnology Learning - Mimi Halimah; Adi Rahmat; Sri Redjeki; Riandi Riandi; Supiani Supiani; Nurfitriah Nurfitriah (Jurnal Pendidikan Progresif, 2026)
Biotechnology learning is often perceived as abstract, complex, and cognitively demanding, which may increase students’ cognitive load and hinder meaningful learning. This study aimed to develop, validate, and evaluate the effectiveness of the Example-Based Cognitive Load Control (EBCLC) Learning Model as an instructional model designed to regulate cognitive load and improve biotechnology learning among prospective biology teachers. This study employed a mixed-methods approach within a research and development (R&D) framework. The qualitative phase involved observations, interviews, and document analysis to identify learning difficulties and instructional needs in biotechnology education. The findings informed the development of the EBCLC model. Subsequently, the model was validated by experts and evaluated through a quantitative pre-experimental one-group pretest–posttest design involving 22 prospective biology teachers. Effectiveness was assessed using mental effort ratings and information-processing performance. Data were analyzed using descriptive statistics and paired-sample t-tests. The results showed that the EBCLC model effectively reduced extraneous cognitive load, as indicated by consistently low mental effort scores across 11 biotechnology topics (mean range: 1.33–1.63). Information-processing performance remained high (mean range: 70.30–92.40), indicating effective engagement with complex biotechnology concepts. Furthermore, posttest scores (M = 78.27) were significantly higher than pretest scores (M = 71.27), indicating an average gain of 7.00 points. The paired-samples t-test revealed a statistically significant improvement, t(21) = 9.92, p < .001, with a very large effect size (Cohen's d = 2.12). The EBCLC model offers a novel instructional synthesis that integrates worked-example principles, guided cognitive processing, and multimodal representations into a structured learning sequence explicitly designed to regulate cognitive load. Unlike conventional worked-example approaches that primarily focus on schema acquisition, the EBCLC model incorporates progressive cognitive guidance and staged information processing to support conceptual understanding of complex biotechnology topics. These findings contribute to the refinement of Cognitive Load Theory and provide an innovative framework for biotechnology instruction in higher education. Keywords: biotechnology learning, cognitive load, EBCLC, modeling examples, prospective biology teachers.