为了培养适应新文科背景的创新型人才,以《经济预测与决策》为例,探索研究型课程教学模式:课程内容上,结合科研热点,将章节设置为理论模型 + 案例分析的专题;授课方式上,依托超星学习通平台,开设线上线下混合课程模式;教学评价上,凸显学生的主体地位,学生可自由选择作业和课程分析报告主题,且成绩由学生自评和教师打分构成。进一步,以我国碳排放效应评价为案例,研究灰色关联度分析的应用、弊端以及改进措施,激发学生的学习兴趣和求知欲,从而培养学生的创新和钻研能力。对2019、2020级经济学受众学生课程感受进行文本分析发现,学生普遍认为学习较多预测模型,对于写论文较为实用,然而理论模型有一定难度。In order to cultivate innovative talents who can adapt to the new humanities background, this article takes “Economic Forecasting and Decision Making” as an example to explore the teaching mode of research-oriented courses: in terms of course content, combined with scientific research hot-spots, chapters are set as theoretical models + case analysis topics;in terms of teaching methods, we rely on the Chaoxing Learning Platform to offer a mixed online and offline course model;in terms of teaching evaluation, highlighting the student’s subjectivity, students can freely choose homework and course analysis report topics, and grades are composed of student self-evaluation and teacher scoring. Furthermore, taking the evaluation of carbon emissions in China as a case study, this study explores the application, drawbacks, and improvement measures of grey correlation analysis to stimulate students’ interest and thirst for knowledge, thereby cultivating their innovation and research abilities. Through text analysis of the course experiences of the 2019 and 2020 economics audience, it was found that students generally believe that learning more predictive models is more practical for writing papers, but theore
