The Impact of Adversity Quotient on Students' Problem-Solving Skills Based on Bransford-Stein’s Theory - Istiqomah, Vina; Budi Astuti; Sugianto, Sugianto (Department of Physics Education, Universitas Mataram, 2025)
Problem-solving ability is an important cognitive skill in learning. The aims to analyze students' problem-solving ability based on Bransford-Stein theory by considering the Adversity Quotient (AQ) factor. The research method used is a quantitative method with simple linear regression analysis. Data were collected through problem-solving tests and administering adversity quotient (AQ) questionnaires. The sample was selected using the purposive sampling technique and obtained 100 high school students selected based on different AQ categories (climbers, campers, quitters). The results of the simple linear regression analysis showed that AQ had a significant effect on the level of students' problem-solving ability. Each increase in one unit of AQ will increase the problem solviing by 1,867 units. The R² value is 0.5506, which means that 55.06% of the variability of problem solving ability can be explained by AQ. This shows that students with high AQ tend to be more persistent in solving problems systematically. Reviewed Based on the five Bransford-Stein indicators (IDEAL Problem solving), students with high AQ (climbers) have a better level of problem-solving ability compared to students with medium AQ types (campers) and low AQ types (quitters). Students with the climbers type can solve all five problem-solving indicators in the questions very well. Campers type students have fairly good problem-solving abilities, but can only solve questions up to three Bransford-Stein indicators. Quitter type students can only solve one Bransford-Stein indicator well. The results of this study can provide input for educators in designing appropriate learning strategies, so that they can improve students' problem-solving abilities by considering their psychological factors, especially adversity quotient. This study only examines correlation, without testing causal relationships through experimental interventions.