研究设计（36学时）课程简介

研究设计（36学时）讲授学术研究的逻辑和方法，开阔学生对社会科学研究的认识, 激发学生的科学兴趣，培养学生独立进行原创性学术研究的能力，指导学生独立完成规范性的学术论文。

研究设计课程的核心内容包括研究问题、文献、数据、计量模型、论文写作五个部分。研究问题部分首先介绍学术研究的组成成分，研究问题的来源和分类，定量与定性研究的区别。其次介绍抽象概念的测量方法（降低抽象水平法、加总法和因果关系法）和评价标准（测量的有效性和可靠性）；文献部分介绍常用中英文文献数据库，文献引用的规则，以及文献的作用和选择标准。数据部分包括数据处理和数据收集。数据处理讲解如何用图表对数据进行描述性分析以及图表的制作方法和要求，数据收集介绍常用中英文数据来源以及区别和比较不同的数据类型（调查数据、直接观察数据和二手数据）；计量模型部分介绍线性回归模型的基本理论，以及因果识别的基本理论和方法，其中包括断点回归、双差分模型和自然实验；论文写作部分讲授中英文学术论文的写作规范以及相关研究辅助工具和网路资源，包括Stata 统计软件、Endnote文献整理软件、和latex写作软件。

参考教材：

Frankfort-Nachmias, Chava and David Nachmias. “Research Methods in the Social Sciences, 8th ed.” New York: Worth Publishers. 2011.

Gerring, John. “Social Science Methodology: A Unified Framework, 2nd ed” Cambridge University Press, 2012.

Research Design (36 class hours)

Research design (36 class hours) introduces the logic and methodology of academic research, broadens college students’ knowledge of social science research, stimulates their interests in science, cultivates the ability to create original academic work, and guides students to write academic papers.

The core contents of research design include five sections: research question, literature, data, econometric model, and writing. Research question section firstly introduces the components of academic research, the sources and classification of research problems, and the difference between quantitative and qualitative studies. This section secondly discusses the measurement of abstract concepts, including the strategies (level of abstraction, aggregation, and causal relationship) and evaluation criteria (measurement validity and reliability); Literature section introduces commonly-used sources of references, citation rules, as well as the roles and selection criteria of references.

Data section discusses data processing and data collection. Data processing explains how to use graphs and tables to provide descriptive data analysis and the criteria of good graphs and tables. Data collection introduces commonly-used data sources and compare different data types (survey data, direct observational data and secondary data); Econometric model section introduces the basic theories of linear regression models, and explains causal identification strategies, including regression discontinuity, difference-in-difference model and natural experiments; Writing section discusses the writing styles and skills of academic papers, and related research auxiliary tools and online resources, including Stata, Endnote, and latex.

《研究设计》课程教学进度计划