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Teacher name : Isao KAMATA
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Course Title
Research Seminar 1
Course Title in English
Research Seminar 1
Course Type
Major Courses
-
Eligible Students
School of Economics and Management
Target Grade
2Year
Course Numbering Code
KCCBG2MCA3
Credits
2.00Credits
The course numbering code represents the faculty managing the subject, the department of the target students, and the education category (liberal arts / specialized course). For detailed information, please download the separate manual from the upper right 'question mark'.
Type of Class
演習 (Seminar)
Eligible Year/Semester
Fall semester 2026
(Fall semester)
Instructor
Isao KAMATA
Affiliation
School of Economics and Management
Language of Instruction
English
Related SDGs
N/a
Office Hours and Location
By appointment.
Contact
kamata@em.u-hyogo.ac.jp
Corresponding Diploma Policy
A double circle indicates the most relevant DP number and a circle indicates the associated DP.
Corresponding Undergraduate School DP
1◎/3◎/4◎
Corresponding Graduate School DP
ー
Corresponding University-Wide DP
N/a
Academic Goals of Teacher Training Course
ー
Course Objectives and Learning Outcome
【Course Objectives】
A series of my Research Seminar courses focuses on empirical analyses of topics/issues in international trade (including foreign direct investment, multinational enterprises, and so on) through which students develop the analytical foundation for graduation research to be performed through Thesis Seminars I & II. In this particular course of Research Seminar I, students learn how to identify data in need, how to use/utilize the data for an analysis properly, and how to present the result of the analysis effectively. 【Learning Outcome】 By the end of this course, students are expected to be able to: - be able to locate proper data and databases for empirical analyses of topics in international trade; - understand and explain the characteristics (including advantages and disadvantages) of the located data(bases); - perform a basic analysis of an intended topic or selected issue; and - make an effective oral and written presentation of the result of the analysis. Subtitle and Keywords of the Class
【Keywords】 Empirical research on international trade, Data for economic analyses
Course Overview and Schedule
In the first section of the course, students search and identify data on designated subjects, and make presentations to explain to the class the features of the data including their advantages and disadvantages. In the second (and relatively brief) section, the students propose topics of their own data analyses to the class, and refine them through in-class discussions. In the third section, the students perform the analyses using the data identified in the first section and present the results to the class.
Classes should be led primarily by students’ activities (i.e., presentations and discussions), and the instructor will join the classes as the facilitator and coach. 1. Introduction to the seminar: guidance and housekeeping 2. Finding and understanding data (1): International trade 3. Finding and understanding data (2): Trade policy (tariffs, trade agreements, etc.) 4. Finding and understanding data (3): Foreign direct investment (FDI) 5. Finding and understanding data (4): Multinational activities of firms 6. Finding and understanding data (5): Other general & international economic indicators 7. Midterm roundup and reflection 8. Proposing (and reconsidering) the topic of an analysis (1) 9. Proposing (and reconsidering) the topic of an analysis (2) 10. Presenting the result of the analysis (1) 11. Presenting the result of the analysis (2) 12. Presenting the result of the analysis (3) 13. Presenting the result of the analysis (4) 14. Presenting the result of the analysis (5) 15. Course wrapping-up and preliminary guidance to Research Seminar II In-person/Remote Classification
In-person
Implementation Method and Remote Credit Limit Application
・In-person classes only.
・Not subject to the cap on distance-education credits. Uses of Generative AI
Limited permission for use
Precautions for using Generative AI
In this course, the use of generative AI is permitted only as an assistant for searching databases and/or for improving English wording or polishing English sentences in presentation materials. If the submitted contents of any assigned work is found to be generated by AI, the assignment will receive a score of zero.
When using generative AI, students must comply with the “Guidelines on the Use of Generative AI in Education at the University of Hyogo (For Students).” Textbook
Required readings and materials will be provided by the instructor as needed.
References
van Marrewijk, Charles (2017), International Trade, Oxford University Press
(ISBN: 9780198753759). Feenstra, Robert C., and Alan M. Taylor (2021), International Trade (5th edition), Worth Publishers / Macmillan (ISBN: 9781319382865). Other recommended readings and resources will be introduced as needed. Contents and Estimated Time for Pre- and Post- Learning (Preparation and Review)
・Pre-learning/preparation: Class preparation involves preparation for presentations that include the corresponding assignments of data identification, topic proposals, and data analyses (8 hours/week on average).
・Post-learning/review: Class review involves (re-)organizing the information on identified data and datasets, reexamining the topics of analyses, and improving data analyses (4 hours/week on average). Contents of Active Learning
Students are required to search and find data & databases in need, perform basic data analyses, and make in-class presentations on those assignments.
Students are also expected to be actively involved in every class discussion. Grading Criteria and Methods
The course evaluation (grades) will be based on the following criteria (and weights):
- Quality of presentations* (70%) (* Presentations involve corresponding assignments such as data identification and data analyses.) - Engagement in class activities including comments to and discussions on in-class presentations (30%) Grades are assigned as follows: S (90 points or higher), A (80 points or higher), B (70 points or higher), and C (60 points or higher). How to Disclose Assignments and Exam Results
Feedback on students’ presentations and corresponding work will be given in class and/or individually.
Precautions and Requirements for Course Registration
・Basic knowledge of international economics and statistics/econometrics should help you in working on the assignments.
・Students need to come to the classroom on time and participate for the entire class period every time. ・Students are required to search and find data & databases in need, perform basic data analyses, and make in-class presentations on those assignments—“Homework every week” virtually. ・Students are also expected to be actively involved in every class discussion. ・Students are encouraged to come to see the instructor to obtain advice on the assignments. Practical Education
n/a
Remarks
In cases where any differences arise between the English version and the original Japanese version, the Japanese version shall prevail as the official authoritative version.
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