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Course Detail

Degree
Master
Standard Academic Year
1
Course delivery methods
face-to-face
Subject
Computer Science, Mass communications & documentation
Program
School
Master's Program in Informatics
Department
Master's Program in Library, Information and Media Studies
Campus
Tsukuba Campus
Classroom
Union Lecture Hall
Course Offering Year
2023-2024
Course Offering Month
July - August
Weekday and Period
Mon/Thu3,4
Capacity
Credits
2.0
Language
English
Course Number
01MBD51

Practical Seminar A University of Tsukuba

Course Overview

This course covers qualitative research, quantitative survey, and data analysis using a computer. With lectures and group work, students are expected to learn how to plan and implement a survey and conduct data analysis. In addition to traditional data analysis methods, newly developed statistical methods will be presented, which will help understand characteristics of data from different view points.

Learning Achievement

(1) To understand qualitative research and quantitative survey methods
(2) To understand how to collect and analyze various types of data
(3) To understand how to use data analysis tools

Competence

Knowledge application competence, Management competence, Teamwork competence, Qualitative research competence, Quantitative research competence

Course prerequisites

Grading Philosophy

Grading considers reports assigned four times (25% each). The project report is evaluated based on the following evaluation criteria; originality, completeness, relevance, impact, and comprehensibility. Students need to score above 60 on a scale of 0-100 in order to pass the course. Grades from A+ to C will be determined based on the total score.

Course schedule

(1) Guidance: Basics of qualitative research, quantitative survey, and data analytics (Wakabayashi)
(2) Qualitative research 1: Design and implementation (Teruyama)
(3) Qualitative research 2: Analysis of qualitative data (Teruyama)
(4) Quantitative survey 1: Making survey forms and collecting data (Yu)
(5) Quantitative survey 2: Analysis of quantitative data (Yu)
(6) Data analysis 1: Introduction to statistical analysis software (Kim)
(7) Data analysis 2: Analysis using open data (Kim)
(8) Content analysis 1: Planning and implementing content analysis (Wakabayashi)
(9) Content analysis 2: Analyzing content data (Wakabayashi)
(10) Summary (Yu)

Course type

Class Exercises

Online Course Requirement

Instructor

Yu Haitao,Kim SunKyoung,Teruyama Junko,Wakabayashi Kei

Other information

Class format
- Face-to-face
- Students' attendance will be checked by respon.

Site for Inquiry


Link to the syllabus provided by the university