Course Information
Course title
 Communication Research Methods 
Semester
 110-2 
Designated for
 GRADUATE INSTITUTE OF JOURNALISM  
Instructor
 Adrian Rauchfleisch 
Curriculum Number
 JOUR7012 
Curriculum Identity Number
 342EM1380 
Class
 02 
Credits
 3.0 
Full/Half
Yr.
 Half 
Required/
Elective
 Required 
Time
 Tuesday 7,8,9(14:20~17:20) 
Remarks
 Restriction: within this department (including students taking minor and dual degree program)
The upper limit of the number of students: 15. 
  
Course introduction video
 
Table of Core Capabilities and Curriculum Planning
 Table of Core Capabilities and Curriculum Planning
Course Syllabus
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Course Description

This course provides an introduction to communication research methods. Students will learn to use different research designs and the most common quantitative methods, such as experiments, surveys, and content analysis. Students will learn to critically assess the research in social science (e.g., replication crisis). Additionally, we will explore how to use the latest computational approaches to answer questions in communication science. We will use the programming language R to analyze and visualize data. We also use R to calculate inferential statistical tests (e.g., regression analysis).  

Course Objective
 - learn the basic methods in social research
- learn how to use R
- be ready to conduct your own research
- be prepared for social research in the big data age
- be prepared to start your thesis 
Course Requirement
  
Student Workload (expected study time outside of class per week)
  
Office Hours
  
Designated reading
 Will be provided in the course 
References
  
Grading
    
Progress
Week
Date
Topic
Week 1
 15-Feb  Introduction course - plan for the semster 
Week 2
 22-Feb  What is social research? 
Week 3
 1-Mar  Research designs and theoretical constructs 
Week 4
 8-Mar  Survey research and Sampling 
Week 5
 15-Mar  Measurements - Reliability and Validity 
Week 6
 22-Mar  Experimental design 
Week 7
 29-Mar  Content analysis and recap 
Week 8
 5-Apr  Holiday 
Week 9
 12-Apr  Midterm exam 
Week 10
 19-Apr  Survey platforms 
Week 11
 26-Apr  Processing data 
Week 12
 3-May  Automatic content analysis and data validation
 
Week 13
 10-May  Analyzing data I 
Week 14
 17-May  Analyzing data II 
Week 15
 24-May  Presenting data 
Week 16
 31-May  Presentations, Review, and discussion