On October 29, 2020，the Ministry of Education officially announced the list of the first batch of national-level first-class undergraduate courses, with a total of 3,560 courses recognized. Shanghai University of Finance and Economics has 9 courses selected, and our college has 2 of them. The course "Mathematical Statistics" led by Professor Wu Chunjie has been recognized as a "blended first-class course," while the course "Multivariate Statistical Analysis" led by Associate Professor Wang Xuemin has been recognized as an "online first-class course." This marks the official inclusion of the courses "Mathematical Statistics" and "Multivariate Statistical Analysis" produced by the School of Statistics and Management at Shanghai University of Finance and Economics into the ranks of "national golden courses."
The college takes curriculum development as the main approach to talent cultivation and places great emphasis on the construction of professional courses. By creating a series of curriculum development systems, it continuously optimizes and upgrades the course settings, further enhancing the quality of talent training. Let’s explore the features of the courses selected this time!
1. Hybrid First-Class Course Online and Offline: "Mathematical Statistics"
"Mathematical Statistics," as a foundational professional course in the field of statistics, has undergone more than 20 years of development. Since 2013, with the aim of "building a mathematical foundation course that serves the economic and management disciplines," it started from the university-level economic and management subject platform courses, progressing through the construction of university key courses, university excellent courses, key courses of the Shanghai Municipal Education Commission, Shanghai excellent courses, and university online courses, steadily advancing and maturing.
The success of curriculum construction relies on an excellent teaching team, advanced teaching concepts, and innovative teaching models. The teaching team of "Mathematical Statistics" includes outstanding teaching backbones from different age groups: senior, middle-aged, and young. They consistently uphold a "student-centered" teaching philosophy, aiming to enhance each student's knowledge level and comprehensive quality, integrating various innovative teaching approaches. By making good use of existing resources, the "Mathematical Statistics" course fully leverages the advantages of mathematical courses, strengthens the innovation of online learning, and continually aims to improve the interactivity of blended teaching. In 2018, the course team officially launched a blended teaching model combining online and offline methods, implementing flipped classrooms, and incorporating current topics into case studies of ideological education. Relying on the Wisdom Tree platform, at least 10 online teaching sessions are held each semester. The flexibility of this new teaching format has been widely welcomed by students, and several teachers' teaching effectiveness evaluations rank among the top 5% in the school. The course received the third place in the school's most popular undergraduate courses in 2019 and the Excellent Case Award for Ideological Education in Courses in 2020.
2. Online First-Class Course: "Multivariate Statistical Analysis"
Multivariate statistical analysis is a rich and highly applicable important branch of statistics, widely used in fields such as natural sciences, social sciences, and economics. Associate Professor Wang Xue-min, as the course leader, has taught this course for over twenty sessions to both undergraduate and graduate students, accumulating extensive teaching experience. The textbook used for the course is "Applied Multivariate Statistical Analysis" (5th edition), authored by Associate Professor Wang Xue-min, and is one of the best-selling books in the field of multivariate statistical analysis in China. It has been nearly 20 years since the first edition, during which it has undergone four major revisions. Each revision has marked a breakthrough and improvement, reflecting the author's pursuit of excellence and perseverance, as well as the college's full support and continuous promotion. The original third edition of the textbook received two provincial and ministerial-level outstanding textbook awards, and all editions have collectively won first-class outstanding textbook awards at the university level four times.
After a series of curriculum developments, this course was recognized as a Shanghai Excellent Course in 2011. As the college's curriculum construction system continues to expand and optimize, efforts have been intensified to enhance high-quality courses. At the beginning of 2018, the construction of the MOOC course "Multivariate Statistical Analysis" was initiated, and it officially launched at the end of November 2018. Currently, it has been offered for five semesters on China's University MOOC platform, with more than 42,000 enrollments, receiving high praise.
The School of Statistics and Management has always adhered to talent cultivation as its core mission, using the construction of "first-class undergraduate statistics programs" and "first-class talent bases" as development opportunities, actively promoting teaching reform and innovation, focusing on building a high-level faculty team, and strengthening course and textbook development. The recent recognition of a national-level first-class undergraduate course is the best testament to our school's long-term efforts in exploring an innovative talent cultivation path with financial and economic characteristics.
All that has passed is prologue. The School of Statistics and Management will remember the mission of talent cultivation, not forget the original intention of nurturing virtue, focus on the connotative development of disciplines, and promote deep interdisciplinary collaboration. In the era of big data, we will strengthen the foundation for the school's layout in new engineering disciplines, the development of big data and artificial intelligence disciplines, as well as the integration of information technology, adding bricks to the construction of a first-class discipline in statistics.
