A Teaching Reform and Practice of Small-Class System in Optional Courses of Engineering Postgraduates

Abstract

Abstract-Graduate education is the highest level of higher education. With the rapid development of economy and society in China, the scale of national graduate education is also expanding. The optional courses for engineering postgraduates are highly practical, and also there are usually many curriculums in major cultivation programs for engineering disciplines, resulting in the scattered graduates in various optional courses and the small teaching scale. In view of these characteristics, we take Modern Optimization Technology and Its Application, one optional course of the discipline of Control Science and Engineering at Dalian Maritime University, as an example and put forward three teaching reform ideas in order to improve the overall teaching quality. First, based on the small-class teaching methods, we elaborate the transformation of classroom teaching from traditional single subject of instructors to the double subjects of instructors and students, featuring weak-center distributed control teaching mode; Second, based on the scientific research project undertaken by instructors and combined with the port and shipping characteristics of Dalian Maritime University, we illustrate the research-and-discussion teaching of combining theory with practice, featuring guidance, learning, research and practice. The third is to put forward the diversified course assessments and closed-loop quality control system which are suitable for small-class teaching. After three years of practice, through questionnaires and final assessments, we can know that the overall teaching quality of this course is satisfactory, and the relevant methods and strategies can be widely applied to the teaching practice of other graduate courses.

Mapping the implications and competencies for Industry 4.0 to hard and soft total quality management

“…First, a small sample is prone to Type I (false positive) error or Type II (false negative) error (Banerjee et al , 2009), albeit controlling for the errors (Rothman, 2010). Second, investigating the experience in a large class postgraduate engineering noncapstone course is of interest to establish a negative effect on grades (Kara et al , 2020) or not (Li and Zhao, 2019). Lastly, a future ontology mapping exercise should expand into generating mappings automatically/systematically, modifying mappings, exploring knowledge from mappings and ordering mapping relationships (Narula et al , 2018).…”