Teaching Reform and Practice of Statistics Courses in Big Data Management and Applications Major in the Context of New Quality Productivity

Abstract

In the new era, the impact of emerging productive forces has permeated every sector of industry. As the core production factor of these forces, data plays a pivotal role in industrial transformation and social development. Consequently, many domestic universities have introduced majors or courses related to big data. Among these, the Big Data Management and Applications major stands out for its interdisciplinary approach and emphasis on practical skills. However, as an emerging field, it has not yet accumulated a robust foundation in teaching theory and practice. Current instructional practices face issues such as unclear training objectives, inconsistent teaching methods and course content, insufficient integration of practical components, and a shortage of qualified faculty—factors that hinder both the development of the major and the overall quality of education. Taking the statistics course within the Big Data Management and Applications major as an example, this paper examines the challenges faced by statistics education in the context of emerging productive forces and proposes corresponding improvement measures. By introducing innovative teaching concepts and strategies, the teaching system for professional courses is optimized, and authentic classroom scenarios are recreated through illustrative examples. Questionnaire surveys and statistical analyses of data collected before and after the teaching reforms indicate that the curriculum changes effectively enhance instructional outcomes, promote the development of the major, and improve the quality of talent cultivation.