シラバス
授業科目名 | 年度 | 学期 | 開講曜日・時限 | 学部・研究科など | 担当教員 | 教員カナ氏名 | 配当年次 | 単位数 |
---|---|---|---|---|---|---|---|---|
専門演習Ⅲ | 2024 | 秋学期 | - | 国際経営学部 | ヴ マン ティエン |
ヴ マン ティエン |
3年次配当 | 2 |
科目ナンバー
GM-OM3-SI03
履修条件・関連科目等
Students should have passed Seminar II. And students should have their data for analayses before the course begin.
授業で使用する言語
英語
授業で使用する言語(その他の言語)
授業の概要
Based on the research questions and obtained data, students will do their analyses and estimations with the data to test their hypotheses.
科目目的
Students are expected to present their preliminary results and analyses by the end of the semester.
到達目標
Students should be able to fulfill the core parts of data analyses by the end of the course.
授業計画と内容
Course content & schedule (subject to change):
1. Introduction: Planning to achieve your big goals.
2. Working with your data (1): Show me the raw data (Data descriptions, questionnaires)
3. Working with your data (2): data cleaning and creating variables.
4. Working with your data (3): correlation and data descriptions.
5. Working with your data (4): data visualization and testing your hypotheses.
6. Refining your hypotheses and consolidating the results.
7. Individual presentations on research progress: hypothesis, data analyses and findings.
8. Individual presentations on research progress: hypothesis, data analyses and findings.
9. Individual presentations on research progress: hypothesis, data analyses and findings.
10. Individual presentations on research progress: hypothesis, data analyses and findings.
11. Individual presentations on research progress: hypothesis, data analyses and findings.
12. Individual presentations on research progress: hypothesis, data analyses and findings.
13. Individual presentations on research progress: hypothesis, data analyses and findings.
14. Individual presentations on research progress: hypothesis, data analyses and findings.
授業時間外の学修の内容
指定したテキストやレジュメを事前に読み込むこと/その他
授業時間外の学修の内容(その他の内容等)
R studio or any statistics software.
授業時間外の学修に必要な時間数/週
成績評価の方法・基準
種別 | 割合(%) | 評価基準 |
---|---|---|
平常点 | 100 | How students understand and apply the knowledge into the practice via students' presentations. |
成績評価の方法・基準(備考)
課題や試験のフィードバック方法
授業時間内で講評・解説の時間を設ける
課題や試験のフィードバック方法(その他の内容等)
アクティブ・ラーニングの実施内容
ディスカッション、ディベート/グループワーク/プレゼンテーション
アクティブ・ラーニングの実施内容(その他の内容等)
授業におけるICTの活用方法
実施しない
授業におけるICTの活用方法(その他の内容等)
実務経験のある教員による授業
いいえ
【実務経験有の場合】実務経験の内容
【実務経験有の場合】実務経験に関連する授業内容
テキスト・参考文献等
Reference books
1. Glewwe, P. & Todd, P. (2021). Impact Evaluation in International Development : Theory, Methods, and Practice. The World Bank. Free access: https://ebookcentral.proquest.com/lib/chuouniv-ebooks/reader.action?docID=29176653
2. FitzGerald. (2016). “The craft of research. Fourth edition”. The University of Chicago Press: Chicago. (Free access: https://ebookcentral.proquest.com/lib/chuouniv-ebooks/detail.action?docID=4785166&query=The%20craft%20of%20research)
3. Frorian Heiss. (2020). “Using R for Introductory Econometrics”, 2nd Edition. http://www.urfie.net (free access).
4. Hilary Glasman-deal. (2020). “Science research writing: For native and non-native speakers of English. Second edition”. World Scientific: Singapore.
5. Kieran Healy. (2019). “Data visualization. A practical introduction”. Princeton Press: New Jersey.
6. William Strunk Jr. “The Elements of Style”.
その他特記事項
It is preferable to use quantitative methods and microdata to answer the research questions. Language is English for all reports, presentations, and thesis.
Class attendance is mandatory.
参考URL
Seminar's page
https://sites.google.com/g.chuo-u.ac.jp/tienmanhvu/prologue?authuser=0
Instructor's site
https://sites.google.com/view/tienmanhvu/home?authuser=0