<p>Over 10&#xa0;years of the new college entrance examination reform, the flexible subject selection model has posed challenges to Science, Technology, Engineering, and Math (STEM) majors education in Chinese universities. The relaxation of subject requirements has led to diverse knowledge backgrounds among students, resulting in some lacking a solid foundation in these fields, which affects students’ adaptability to university learning, resulting in frequent major changes and high failure rates. In this study, we innovatively combined the dual-channel theory to design a learning adaptability model, which interacts the process of learning adaptability with students’ thinking process, and divides it into emotional adaptation similar to perceptual system and academic achievement adaptation similar to analytical system. Based on the model, a measurement scale and test questions were developed to more accurately assess students’ learning adaptability. Students were then categorized according to their levels of learning adaptability. Findings indicate two main types: low adaptability, characterized by low motivation and difficulty using intelligent tools, and high adaptability, which correlates with better adjustment but moderate interest in the major. Finally, this study offers targeted recommendations for improving the learning adaptability of STEM students.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Study on learning adaptability of STEM students in the new college entrance examination context

  • Xiangyi Shi

摘要

Over 10 years of the new college entrance examination reform, the flexible subject selection model has posed challenges to Science, Technology, Engineering, and Math (STEM) majors education in Chinese universities. The relaxation of subject requirements has led to diverse knowledge backgrounds among students, resulting in some lacking a solid foundation in these fields, which affects students’ adaptability to university learning, resulting in frequent major changes and high failure rates. In this study, we innovatively combined the dual-channel theory to design a learning adaptability model, which interacts the process of learning adaptability with students’ thinking process, and divides it into emotional adaptation similar to perceptual system and academic achievement adaptation similar to analytical system. Based on the model, a measurement scale and test questions were developed to more accurately assess students’ learning adaptability. Students were then categorized according to their levels of learning adaptability. Findings indicate two main types: low adaptability, characterized by low motivation and difficulty using intelligent tools, and high adaptability, which correlates with better adjustment but moderate interest in the major. Finally, this study offers targeted recommendations for improving the learning adaptability of STEM students.