AY 2024 Undergraduate School Course Catalog AY 2024 Undergraduate School Course Catalog AY 2024 Undergraduate School Course Catalog
| 2024/11/21 |
| Open Competency Codes Table Back |
| 開講学期 ／Semester |
2024年度／Academic Year 4学期 ／Fourth Quarter |
|---|---|
| 対象学年 ／Course for; |
3rd year |
| 単位数 ／Credits |
2.0 |
| 責任者 ／Coordinator |
HEO Younghyon |
| 担当教員名 ／Instructor |
HEO Younghyon |
| 推奨トラック ／Recommended track |
－ |
| 先修科目 ／Essential courses |
－ |
| 更新日／Last updated on | 2024/01/23 |
|---|---|
| 授業の概要 ／Course outline |
This course is designed to provide students with skills and trainings for 1) improving the English speaking fluency and 2) preparing/giving English presentations. By practicing English as an International Language, students will be motivated to speak English more confidently and comfortably. This can further boost their confidence in public speaking (presentation). |
| 授業の目的と到達目標 ／Objectives and attainment goals |
[Corresponding Learning Outcomes] (D)Graduates are able to view human society from a global perspective and think about the coexistence of nature and human beings, as well as the happiness, health, and welfare of humankind. (E)Graduates are able to effectively express their thoughts and judgments in writing, orally, and through information media, both inside and outside the country, and to communicate them to others, as well as to understand the information and opinions expressed by others. (F)Graduates are able to determine and carry out the actions they and others, including those from other disciplines, should take and plan and manage work under given constraints in collaborative projects. [Competency Codes] C-EC-006-2, C-EC-009-4, C-EC-013-2 Upon completion of the course, students should be able to: 1) increase fluency in English speaking, 2) learn how to prepare/design English presentation materials, 3) learn/practice useful techniques for presentations in various situations, and 4) overcome anxiety in speaking English and in giving oral presentations. |
| 授業スケジュール ／Class schedule |
Class 1. Course introduction Class 2. Elements of a good presentation: Slides and verbal language Class 3. Elements of a good presentation: Story-telling Class 4. Elements of a good presentation: Body language and attitude Class 5. Preparing for the mini presentation Class 6. Mini presentation Class 7. Review of mini presentation, Final project planning Class 8. World Englishes Class 9. Fluency session 1 Class 10. Fluency session 2 Class 11. Fluency session 3 Class 12. Fluency session 4 Class 13. Presentation rehearsals Class 14. Final Project Presentation (Session 1) Class 15. Final Project Presentation (Session 2) |
| 教科書 ／Textbook(s) |
There is no textbook for this course. Course materials (e.g. lecture notes) are available on the course Moodle page. |
| 成績評価の方法・基準 ／Grading method/criteria |
Active Participation: 20% Assignments: 30% Mini-presentation: 15% Final project presentation: 35% Notes: If you miss 4 classes or more, you cannot pass this course. |
| Open Competency Codes Table Back |
| 開講学期 ／Semester |
2024年度／Academic Year 1学期 ／First Quarter |
|---|---|
| 対象学年 ／Course for; |
3rd year |
| 単位数 ／Credits |
2.0 |
| 責任者 ／Coordinator |
NICHOLAS Allan |
| 担当教員名 ／Instructor |
NICHOLAS Allan |
| 推奨トラック ／Recommended track |
－ |
| 先修科目 ／Essential courses |
－ |
| 更新日／Last updated on | 2024/01/16 |
|---|---|
| 授業の概要 ／Course outline |
In this course, learners' awareness of cultural differences and the ways in which these differences are realized in communication will be raised. Learners will practice and develop all four language skills (reading, writing, listening & speaking), and will build their vocabulary. Materials for the course will be provided by the instructor. |
| 授業の目的と到達目標 ／Objectives and attainment goals |
[Corresponding Learning Outcomes] (D)Graduates are able to view human society from a global perspective and think about the coexistence of nature and human beings, as well as the happiness, health, and welfare of humankind. (E)Graduates are able to effectively express their thoughts and judgments in writing, orally, and through information media, both inside and outside the country, and to communicate them to others, as well as to understand the information and opinions expressed by others. (F)Graduates are able to determine and carry out the actions they and others, including those from other disciplines, should take and plan and manage work under given constraints in collaborative projects. [Competency codes] C-EC-002-5 C-EC-009-5 C-EC-012-5 By the end of the course, learners will: a) have a basic understanding of the concepts of collectivism and individualism in relation to culture b) have some understanding of other prominent cross-cultural research and theories, including high/low context communication and orientation to time; c) have an understanding of research-based insights into Japanese culture and communication styles d) be able to compare and contrast their own communication styles with those of other cultures |
| 授業スケジュール ／Class schedule |
Class 1: Introduction to the course Class 2: Defining “culture” and “cross-cultural communication” Class 3: Individualism versus collectivism: the work of Hofstede Class 4: Individualism & collectivism: continued Class 5: Hierarchical & democratic cultures Class 6: Power-distance Class 7: High versus low-context communication styles: the work of Hall Class 8: Non-verbal behavior communication & culture Class 9: Non-verbal communication and culture Class 10: Conversation & Social context Class 11: Conversation & Social context Class 12: End-term Project Class 13: End-term project Class 14: Review activity/test |
| 教科書 ／Textbook(s) |
All materials are provided by the instructor. |
| 成績評価の方法・基準 ／Grading method/criteria |
Active participation: 5% End-term exam: 40% Project: 20% In-class activities/assignments: 35% |
| 履修上の留意点 ／Note for course registration |
This course is designed for intermediate-level Japanese learners of English. All materials are provided by the instructor. Every student must enroll in the course through Moodle. Weekly announcements will be uploaded on the course page on Moodle. Please check Moodle for detailed information on assignments or other course information. Please contact your professor if you have any problems accessing the website. If you have problems with your login, please contact or visit SSB (RQ 207-E). It is required that students take quizzes and exams individually; cheating/plagiarizing other’s work will not be tolerated. There are no set requirements. However, learners are expected to have completed 1st and 2nd year English core courses. |
| 参考(授業ホームページ、図書など) ／Reference (course website, literature, etc.) |
The instructor has work experience in private industry. |
| Open Competency Codes Table Back |
| 開講学期 ／Semester |
2024年度／Academic Year 1学期 ／First Quarter |
|---|---|
| 対象学年 ／Course for; |
3rd year |
| 単位数 ／Credits |
2.0 |
| 責任者 ／Coordinator |
ROY Debopriyo |
| 担当教員名 ／Instructor |
ROY Debopriyo |
| 推奨トラック ／Recommended track |
－ |
| 先修科目 ／Essential courses |
Competency Requirements: C-EC-010 & C-EC-015 |
| 更新日／Last updated on | 2024/02/13 |
|---|---|
| 授業の概要 ／Course outline |
Visualization and data storytelling is absolutely essential in today’s business. If raw data can’t be turned into compelling information, companies will be unable to devise a strategy for better corporate performance. The MIT Sloan School of Management described data storytelling as "the ability to convey data not just in numbers or charts but as a narrative that humans can comprehend." Sloan also said, "As with any good story, a data tale needs a beginning, a middle, an end, and some actionable insights. Data scientists aren't always up to the job". Reference: https://www.techrepublic.com/article/why-data-storytelling-in-business-matters-more-than-ever/ In this course, we will discuss how data storytelling is a methodology for communicating information, tailored to a specific audience, with a compelling narrative. Data storytelling ideally merges three key fields of expertise: Data science: This field of expertise is the interdisciplinary field of sciences, which extracts knowledge and insight from data, making it readily available. Visualizations: Transforming data into graphs, pie, and line charts meant we could see our data like never before, however, data visualizations alone have limitations. They provided at-a-glance snapshots of data, lacking the context needed to explain why something has happened. Storytelling: Data scientists are often skilled at collecting and delivering data, but lack the skills to relay a true understanding of the opportunities hidden in the data delivered. As part of this course, we will focus on understanding how data science is now one of the most demanding areas of study in computer science, what it takes to become a good data scientist, the power of data visualization, and how to deliver compelling data storytelling for efficient project management, and how it could be converted into actionable strategies for companies. |
| 授業の目的と到達目標 ／Objectives and attainment goals |
[Corresponding Learning Outcomes] (A)Graduates are able to view human society from a global perspective and think about the coexistence of nature and human beings, as well as the happiness, health, and welfare of humankind. (B)Graduates are able to effectively express their thoughts and judgments in writing, orally, and through information media, both inside and outside the country, and to communicate them to others, as well as to understand the information and opinions expressed by others. (C)Graduates are able to determine and carry out the actions they and others, including those from other disciplines, should take and plan and manage work under given constraints in collaborative projects. We will look forward to achieving multiple goals during the semester. Develop a comprehensive understanding of the field of data science Develop different visualization techniques depending on the scope of the data Understanding machine and deep learning and the contribution to data science Understanding design thinking and the contribution to data science The difference between data visualization and data storytelling Develop speaking ability to explain specific graph types, decoding, and preparing a compelling story from the visual presentation. Develop technical writing skills when explaining data for business purposes |
| 授業スケジュール ／Class schedule |
Week # 1 Introduction to Data Science / Bonus Forum Assignment Week # 2 Data Science Research Process / Quiz 1 & Google Scholar Research Article Video Analysis Week # 3 Introduction to Design Thinking & Design Thinking vs. Machine Learning / Quiz 2 Week # 4 Design Thinking in Data Science / Quiz 3 & Infographics Design & Visualisation Type Explanation Week # 5 Data Visualization Techniques and Processes of Infographic Design / Quiz 4 & Working with Excel Datasheet Week # 6 Working with Kaggle & Tableau Public / Quiz 5 & Bonus Forum Assignment Week # 7 Final Project / Turning Visualization into Data Storytelling Students will be participating in the ETLTC summer conference and the other events during the week of May 15-19, and networking with the international attendees. The final project on information management will require students to attend the conference and represent the conference-related information/talks as a data storytelling assignment. Class 14-15: Participation in https://etltc-acmchap.org/ ● Minor alterations in the schedule might be necessary. |
| 教科書 ／Textbook(s) |
No textbooks are needed. All required materials will be posted in Moodle. |
| 成績評価の方法・基準 ／Grading method/criteria |
Assessment (Overall Criteria): Each group and/or individual assignment will be graded against a specific set of criteria. A student will either get 0 or 1 for each category as is seen below. 1. Organization of Ideas ( 0/1) 2. Clarity of Ideas (0/1) 3. Grammatical and Sentence Construction Issues (0/1) 4. Use and Explanation of Graphics (0/1) 5. User-Friendly Nature of the Information (0/1) 6. Text-Graphics Coordination (0/1) 7. Information Accessibility (0/1) Grading: ❖ Quiz: 20% ● Quiz 1: Introduction to Data Science ● Quiz 2: Design Thinking ● Quiz 3: Machine Learning vs. Data Science ● Quiz 4: Data Scientist vs. Data Analyst ● Quiz 5: Data Visualization & Storytelling ❖ Google Scholar Research Article Video Analysis - 20% ❖ Infographics Design & Visualisation Type Explanation - 20% ❖ Working with Excel Datasheet - Preparing Data for Project Management - 20% ❖ Turning Visualization into Data Storytelling - 20% (related to conference participation) Bonus Points: Two bonus point assignments in the Moodle forum will be built into the course. |
| 履修上の留意点 ／Note for course registration |
Reasonable English language proficiency and a basic understanding of statistics will help. Interest in project management and business studies is welcome. Feel free to consult with your friends about your assignment. Group discussions are entertained. Warning: Class Attendance and participation and communication with the course instructor are factored into the final grade. |
| 参考(授業ホームページ、図書など) ／Reference (course website, literature, etc.) |
References: Data Visualization: A Practical Introduction by Kieran Healy https://www.amazon.co.jp/gp/product/0691181624/ref=ppx_yo_dt_b_asin_title_o05_s00?ie=UTF8&psc=1 Storytelling with Data: A Data Visualization Guide for Business Professionals by Nussbaumer Knaflic, Cole https://www.amazon.co.jp/gp/product/1119002257/ref=ppx_yo_dt_b_asin_title_o07_s00?ie=UTF8&psc=1 |