Exploration on Blended Teaching Mode of Data Mining Course with CDIO Concept

• Published in: 2023 IEEE 12th International Conference on Educational and Information Technology (ICEIT) pp. 150 - 155
• Main Authors: Zhu, Yingxue, Liu, Mingyou, Li, Li, Wang, Yue
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.03.2023
• Subjects: active learning; Big Data; blended teaching; Boring; CDIO concept; Data mining; Data science; Education; encouraging learning; Engineering education; Technological innovation
• DOI: 10.1109/ICEIT57125.2023.10107892

With the deep development of big data technology, it has become one of the core educational goals of data science and big data related majors in colleges and universities to cultivate students' ability of data thinking, engineering practice and theoretical innovation. For the traditional data mining course teaching content is boring and difficult to understand, it is difficult to stimulate students' interest in learning the teaching status, this paper analyzes the reasons behind it and integrates the concept of DCIO engineering education to design a student-centered, data thinking as well as practical innovation ability of students as the goal, and a case-driven online and offline blended teaching mode, which explores the teaching objectives, teaching contents and teaching methods. The teaching practice shows that the teaching mode implemented in this paper can give full play to the advantages of online and offline teaching, effectively promote the interaction between teachers and students, and stimulate students' enthusiasm and initiative in learning.