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教員名 : 磯貝 茂樹
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授業科目名
Research Seminar I
(英語名)
Research Seminar I
科目区分
専門教育科目
−
対象学生
国際商経学部
学年
2年
ナンバリングコード
KCCBG2MCA3
単位数
2単位
ナンバリングコードは授業科目を管理する部局、学科、教養専門の別を表します。詳細は右上の?から別途マニュアルをダウンロードしてご確認ください。
授業の形態
演習 (Seminar)
開講時期
2026年度後期
(Fall semester)
担当教員
磯貝 茂樹
所属
国際商経学部
授業での使用言語
英語
関連するSDGs目標
目標1/目標2/目標3
オフィスアワー・場所
To be announced in the first class.
連絡先
To be announced in the first class.
対応するディプロマ・ポリシー(DP)・教職課程の学修目標
二重丸は最も関連するDP番号を、丸は関連するDPを示します。
学部DP
1◎/3◎/4◎
研究科DP
ー
全学DP
ー
教職課程の学修目標
ー
講義目的・到達目標
The course aims to provide students with opportunities to learn and discuss basic ideas of game theory.
The students are expected to perform a presentation and lead an academic discussion. They will be able to explain and analyze economic phenomena in their own words (of game theory). 授業のサブタイトル・キーワード
Subtitle: Research Seminar on Game Theory
Keyword: Game Theory 講義内容・授業計画
Game theory studies interaction among multiple decision makers. It is applied to various fields in social sciences such as economics, business, politics, and so on. For example, auction design is one of the most successful applications of game theory. Online search engines such as Google gain their profits primarily from advertising auctions.
The seminar aims to provide students with a deep understanding of the discipline by reading a textbook together and by elaborating game-theoretical arguments in presentations. In the first week, we will discuss the seminar plan and schedule presentations. The rest of the semester will be devoted to reading the textbook(s). Students are required to take turns studying the textbook and presenting the content. 対面・遠隔の別
対面
実施方法及び遠隔上限適用対象の別
①In-person
・In-person classes only ・Not subject to the cap on distance-education credits 生成AIの利用
全面的に許可
生成AI注意点
In this course, the use of generative AI is fully permitted. Appropriate use of gen AI is even encouraged.
Please pay attention to the contents described in "Guidelines on the Use of Generative AI in Education at the University of Hyogo (For Students)". Additional instructions based on the current state of the AI will be provided in the first class. 教科書
The main textbook is (tentatively)
Steven Tadelis, "Game Theory: An Introduction" 参考文献
To be announced during the class.
事前・事後学習(予習・復習)の内容・時間の目安
Preparation for presentations: 30h
Elaboration after feedback: 30h アクティブ・ラーニングの内容
Presentation and discussion
成績評価の基準・方法
The course evaluation is based on quality of presentation and engagement.
For example, students who can exhibit their understanding of the contents by clearly explaining the materials, providing appropriate examples of some concepts, and coming up with an interesting research agenda are likely to obtain high evaluations. Active participation in discussions is also a plus factor. 課題・試験結果の開示方法
The instructor provides suggestions and feedback.
履修上の注意・履修要件
There is no prerequisite for the class. Knowledge of microeconomics may be helpful.
実践的教育
Not applicable.
備考
英語版と日本語版との間に内容の相違が生じた場合は、日本語版を優先するものとします。
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