Construction and Empirical Study of Data-Driven Blended Learning Based on Problem-Based Learning:Organic Chemistry
LIU Qiang1**, ZHAO Wan-Xiang1**, ZHENG Cai-Xing2, LIU Sheng-Tao3, WANG Yu-Zhi1**
1. College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China; 2. School of Physics and Electronics, Hunan University, Changsha 410082, China; 3. Educational Science Research Institute, Hunan University, Changsha 410082, China
Abstract Based on the educational concept of “student-centered”, a data-driven blended learning based on problem-based learning (PBL) is designed to solve the problems in the PBL learning of organic chemistry. An empirical study was carried out using the curriculum “Organic Chemistry” as an example. The offline teaching content focuses on finding the student’s zone of proximal development according to the student-learning data, such as the duration of students’ online self-learning and test statistics. According to the student-learning data, decisions on teaching content and activities were flexibly adjusted, focusing on solving difficult problems in online learning, and focusing on students’ deep learning and personalized teaching in the classroom. This teaching mode realizes the deep integration of online learning and offline learning activities. The results of questionnaire survey and behavior analysis show that data-driven blended learning based on PBL is an effective teaching mode to improve students’ learning quality, with advantages of student-centered, individualized instruction, and continuous teaching improvement.
LIU Qiang, ZHAO Wan-Xiang, ZHENG Cai-Xing, LIU Sheng-Tao, WANG Yu-Zhi. Construction and Empirical Study of Data-Driven Blended Learning Based on Problem-Based Learning:Organic Chemistry[J]. Chinese Journal of Chemical Education, 2023, 44(8): 55-60.
