Hybrid learning style identification and developing adaptive problem-solving learning activities

摘要: Learning style refers to an individual's approach learning based on his or her preferences, strengths, and weaknesses. Problem solving is considered essential cognitive activity wherein people are required understand a problem, apply their knowledge, monitor behavior solve the issue. has recently gained attention in education research, as it ability for effective learning. This study aims investigate relationship between styles performance. To provide adaptive suggestions optimizing problem-solving abilities, developed hybrid identification (HLSI) mechanism k-means clustering algorithm was developed. The participants were 67 undergraduate students. experiment demonstrated that HLSI can successfully cluster into three four combinations performance, which suggests data mining technique explore multiple abilities. Additionally, 13 teachers included discuss effectiveness of mechanism, results indicated 95% probability obtaining above-average acceptance proposed system. We identified affect performance game-based activity.The system had good technology accepted (e.g., "perceived ease use" usefulness").Data techniques employed styles.