Deep learning-based group investigation: Improving creative problem-solving in natural science learning - Yudhistian, Yudhistian; Wulandari, Tabitha Sri Hartati (Biology Education Department, Universitas Insan Budi Utomo, Malang, Indonesia, 2026)
The urgent need for a structured instructional framework that elevates creative problem-solving efficacy necessitates the integration of a pedagogical deep learning approach focused on emotional and cognitive engagement, with the group investigation model. The research aims to examine the effects, effectiveness, and student perceptions regarding the implementation of a group investigation learning model based on a deep learning approach on students' creative problem-solving skills in natural science. Utilizing a quasi-experimental research design with a nonequivalent control group, this research evaluated a sample of 60 students (N = 30 per class). Data collection utilized pretests, posttests, rubrics, and response questionnaires, which were subsequently analyzed using descriptive percentages, hypothesis testing, N-Gain scores, and effect size values. The results showed a notable difference in creative problem-solving skills between the experimental and control groups (p = 0.001 < 0.05), with a high N-Gain score (0.71) and a very high effect size (1.85). Additionally, student responses were in the highly positive category (83.40%). It can be concluded that integrating deep learning into the group investigation model effectively improves creative problem-solving skills in natural science. The study implies that this innovative learning framework can be adopted as an alternative strategy to foster creative problem-solving skills.