2023/01/30 |
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開講学期 /Semester |
2022年度/Academic Year 2学期 /Second Quarter |
---|---|
対象学年 /Course for; |
3rd year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
PERKINS Jeremy |
担当教員名 /Instructor |
PERKINS Jeremy |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/01/11 |
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授業の概要 /Course outline |
Students will learn to use R in order to apply basic statistical techniques on linguistic data. The course will focus on analysis of acoustic data using the Praat software package. Students will learn how to run an acoustic study using Praat scripts, with techniques for organizing, processing and analyzing the results via R. |
授業の目的と到達目標 /Objectives and attainment goals |
The following objectives will be of particular interest: 1. A basic understanding of acoustic phonetics. 2. How to use Microsoft Excel to work with data. 3. How to use Praat software to analyze acoustic data. 4. How to write scripts that allow processing large amounts of data. 5. Statistical techniques and hypothesis testing using R software. |
授業スケジュール /Class schedule |
** Classes will be held at scheduled times via online Zoom lectures: Class 1: Introduction Classes 2-3: An Introduction to Acoustic Phonetics Classes 4-5: Using Praat to analyze Acoustic Phonetics Classes 6-7: Writing Praat Scripts Classes 8-9: Review & Midterm Exam Classes 10-11: Statistical Techniques Classes 12-14: Using R for statistical analysis |
教科書 /Textbook(s) |
No textbook will be used. Course material will be made available online to students via Moodle. |
成績評価の方法・基準 /Grading method/criteria |
Students are required to take the TOEIC test in class during the final exam week to pass this course. Homework Assignments (6 assignments worth 5% each) 30% Midterm Exam (in class – class 8 or 9) 25% Take-home Final Project (assigned class 10; due end of quarter) 25% Active Participation 20% |
履修上の留意点 /Note for course registration |
The class does not have a final exam. Instead, a final project is assigned. |
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開講学期 /Semester |
2022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 |
- |
Back |
開講学期 /Semester |
2022年度/Academic Year 2学期 /Second Quarter |
---|---|
対象学年 /Course for; |
3rd year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
BLAKE John |
担当教員名 /Instructor |
BLAKE John |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/01/11 |
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授業の概要 /Course outline |
Language is permeated with patterns. In English, the letter q tends to be followed by the letter u. The word moon is almost always preceded by the word the. Passive voice is usually formed with the verb be and a past participle (e.g. was done). Students study the patterns in the words, grammar, meaning and functions in texts. Less obvious patterns can be discerned using specialist pattern-matching tools. This course enables students to investigate the relationship between patterns and language by exploring the vocabulary, grammar and structure of texts. Statistical tools and visualization tools are used to discover the less obvious patterns. |
授業の目的と到達目標 /Objectives and attainment goals |
By the end of the course students will be able to: (a) describe patterns and pattern-seeking behaviour (b) identify patterns at lexical, grammatical and discourse levels (c) use statistical and visualization tools to identify language patterns (d) adapt or create a language visualization tool to discover language patterns |
授業スケジュール /Class schedule |
Patterns and pattern seeking Session 01 Patterns and pattern seeking Session 02 Language system and its patterns Session 03 Patterns in written English Session 04 Patterns in spoken English Session 05 Review and consolidation Specific language patterns Session 06 Functional patterns Session 07 Clausal and phrasal patterns Session 08 Lexical and grammatical patterns Session 09 Lexical and grammatical patterns II Session 10 Review and consolidation Pattern detection and visualization Session 11 Word patterns I Session 12 Word patterns II Session 13 Review Session 14 Consolidation Session 15 Final exam |
教科書 /Textbook(s) |
No textbook. Materials will be provided. |
成績評価の方法・基準 /Grading method/criteria |
Active participation: 30% Quizzes: 30% Final exam: 40% Students are required to take the TOEIC test in class during the final exam week to pass this course. |
参考(授業ホームページ、図書など) /Reference (course website, literature, etc.) |
None |
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開講学期 /Semester |
2022年度/Academic Year 3学期 /Third Quarter |
---|---|
対象学年 /Course for; |
3rd year , 4th year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
ILIC Peter |
担当教員名 /Instructor |
ILIC Peter |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/01/28 |
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授業の概要 /Course outline |
This course will cover Information and Communications Technology (ICT) in Education particularly focusing on affordances offered by the technology. It will address the “what” and “how” of ICT in education, by providing students with theoretical and practical knowledge invaluable in the planning, implementation, and evaluation of ICT supported education. Students will learn about various affordances of educational technology, from current trends to future possibilities. Also, the course will help students develop awareness of the current advantages and limitations of ICT in the educational context. It will be of particular interest to students who are interested in becoming educators. *Students are required to take the TOEIC test in class during the final exam week to pass this course. |
授業の目的と到達目標 /Objectives and attainment goals |
1. Develop theoretical and practical knowledge of ICT in education. 2. Develop critical understanding of the limits of ICT in education. 3. Acquire skills in the planning and implementation of ICT in education. |
授業スケジュール /Class schedule |
1. Introduction to ICT in Education a. Homework: i. Online Reading ii. Quiz 1 (8%) 2. History of ICT in Education a. Homework: i. Online Reading ii. Quiz 2 (8%) 3. Synchronous/Asynchronous a. Homework: i. Online Reading ii. Quiz 3 (8%) 4. Ubiquitous Learning a. Homework: i. Online Reading ii. Quiz 4 (8%) 5. Active Knowledge Making a. Homework: i. Online Reading ii. Quiz 5 (8%) 6. Multimodal Meaning a. Homework: i. Online Reading ii. Quiz 6 (8%) 7. Recursive Feedback a. Homework: i. Online Reading ii. Quiz 7 (8%) 8. Collaborative Intelligence a. Homework: i. Online Reading ii. Quiz 8 (8%) iii. Project Outline (5%) 9. Metacognition a. Homework: i. Online Reading ii. Quiz 9 (8%) 10. Differentiated Learning a. Homework: i. Online Reading ii. Quiz 10 (8%) 11. The Future a. Homework: i. Presentation PowerPoint upload 12. Project Presentations (15%) 13. Project Presentations 14. Project Presentations 15. Final exam week: TOEIC online |
教科書 /Textbook(s) |
No textbook will be used. Course material will be made available online to students via Moodle. |
成績評価の方法・基準 /Grading method/criteria |
Online Reading Quizzes: 80% Project: Total 20% • Project Outline: 5% • Project Presentation (PowerPoint): 15% Notes: Late assignments will lose 10% per day. After 5 days, a late assignment will receive a mark of 0%. Not participating in class activities will result in -2%. Being late 3 times will be equivalent to 1 absence. Being more than 30 minutes late will equal 1 absence. |
履修上の留意点 /Note for course registration |
Students are required to take the TOEIC test in class during the final exam week to pass this course. |
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開講学期 /Semester |
2022年度/Academic Year 3学期 /Third Quarter |
---|---|
対象学年 /Course for; |
3rd year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
WILSON Ian |
担当教員名 /Instructor |
WILSON Ian |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/01/28 |
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授業の概要 /Course outline |
In this course, open-source acoustic analysis software ("Praat") will be mastered so that students have skills to analyze speech/pronunciation beyond the classroom. Students will be taught about properties of the acoustic signal and they will be taught how to write Praat scripts to automate acoustic analysis. Students will sometimes be required to submit voice recordings demonstrating their pronunciation. This course provides basic phonetic knowledge that is necessary for work in fields such as speech recognition and speech synthesis. |
授業の目的と到達目標 /Objectives and attainment goals |
By the end of the course, students will: (a) have learned the English vocabulary for acoustics concepts (b) have acquired detailed knowledge of how to use Praat software, including writing scripts to automate acoustic measurements and to manipulate sounds (c) know how to use waveforms and spectrograms to analyze properties of speech such as formant patterns, duration, intensity, pitch (including sentence intonation), voice onset time (VOT), etc. (d) know the acoustic properties of English vowels, including schwa (e) have had much practice pronouncing English words and sentences |
授業スケジュール /Class schedule |
Class 1: Introduction to the course and to Praat software; initial recording Class 2: Acoustics glossary; English vowel acoustics Class 3: Using TextGrid files to label sounds in Praat Class 4: Praat script writing 1 Class 5: Praat script writing 2; homework assignment Class 6: Manipulation of Pitch and Duration Class 7: Intonation and rhythm in English Class 8: Midterm exam Class 9: English schwa - acoustic properties Class 10: Praat environments; acoustics of /r/ and /l/ Class 11: Praat script writing 3; Form...Endform Class 12: Reading speed; Pausing during speech; voice onset time (VOT) Class 13: World Englishes; Final recording Class 14: Review activity/test Final exam week: TOEIC online |
教科書 /Textbook(s) |
Materials will be distributed in class or on the class website. This course will be organized in Moodle. Students will use Praat open-source software in class on iMac computers, make recordings, and analyze their pronunciation. Note that Praat is free to download from the Praat website, if you want to download it to your own computer. |
成績評価の方法・基準 /Grading method/criteria |
Active participation and quizzes: 20% Homework assignments: 20% Midterm exam: 30% Review activity/test: 30% Students are required to take the TOEIC test in class during the final exam week to pass this course. |
参考(授業ホームページ、図書など) /Reference (course website, literature, etc.) |
The course instructor Ian Wilson has practical working experience. He worked for GEOS Corporation for 8 years, where he was involved in teaching English-as-a-Foreign-Language (EFL) and training EFL teachers. Based on his experience, he can teach all 4 skills (speaking, listening, reading, writing) of EFL. Praat website here: Praat website Prof. Ian Wilson's YouTube channel: Ian Wilson - YouTube CLR Phonetics Lab website: CLR Phonetics Lab Class:Lecture |
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開講学期 /Semester |
2022年度/Academic Year 2学期 /Second Quarter |
---|---|
対象学年 /Course for; |
3rd year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
LINGLE William |
担当教員名 /Instructor |
LINGLE William |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/02/03 |
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授業の概要 /Course outline |
This course aims to provide students with the cognitive tools to distinguish between statements of fact and opinion, between strong and weak logical arguments, and to identify how emotions and cultural values can influence the ways in which arguments are constructed, expressed, and understood. |
授業の目的と到達目標 /Objectives and attainment goals |
By the end of the course students will be able to: 1) distinguish statements of fact from statements of opinion 2) identify sources of information by which statements of fact may be evaluated as correct or incorrect 3) identify logical arguments 4) identify appeals to cultural values and emotions within arguments 5) identify logical fallacies within arguments 6) evaluate arguments as strong or weak 7) recognize strengths and weaknesses of their own arguments and of those they disagree with |
授業スケジュール /Class schedule |
Facts vs. Opinions Session 1: Facts vs. Opinions 1 Session 2: Facts vs. Opinions 2 Session 3: Facts vs. Opinions 3 Session 4: Review and Quiz Arguments Session 5: Structure of Arguments Session 6: Logical Reasoning / Venn Diagrams Session 7: Fallacies 1 Session 8: Fallacies 2 Session 9: Evaluating Strength of Arguments Session 10: Review and Quiz Emotions and Values Session 11: Logic and Morals Session 12: Cultural Values Session 13: Critical Media Literacy Session 14: Final Review Activity/Test Final Exam Week: TOEIC online |
教科書 /Textbook(s) |
No textbook. Materials will be provided by instructor. |
成績評価の方法・基準 /Grading method/criteria |
Participation activities: 25% Exercises: 20% Quizzes: 30% Final Review Activity/Test: 25% Students are required to take the TOEIC test in class during the final exam week to pass this course. |
履修上の留意点 /Note for course registration |
None |
参考(授業ホームページ、図書など) /Reference (course website, literature, etc.) |
All materials will be available on the course Moodle page. |
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開講学期 /Semester |
2022年度/Academic Year 4学期 /Fourth Quarter |
---|---|
対象学年 /Course for; |
3rd year , 4th year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
BENSON Stuart |
担当教員名 /Instructor |
BENSON Stuart |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/01/25 |
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授業の概要 /Course outline |
In addition to knowing general vocabulary, knowledge of specific vocabulary related to the field of Computer Science is critical. Comprehension of texts, articles, presentations, lectures, and classes is critical to your success in the field. In this Computer Science vocabulary course, we will learn the most important words in the field through numerous activities of reading, writing, listening, and speaking. In addition, a computer science word list will be the focus of the course, with the goal of learning and actively using these words on context. |
授業の目的と到達目標 /Objectives and attainment goals |
The goal of this course is to learn the most frequent Computer Science vocabulary and use these words, receptively and productively. By the end of the course, learners will: a) have knowledge of several vocabulary learning strategies b) have an understanding of the most frequent vocabulary in Computer Science c) be able to comprehend these words in reading and listening activities d) be able to use these words in speaking and writing activities |
授業スケジュール /Class schedule |
Class 1: Introduction to the course Class 2-4: vocabulary strategies to learn CS vocabulary Class 5-9: Learning CS vocabulary through speaking/listening activities Class 7: Mid-term vocabulary test Class 10-13: Learning CS vocabulary through reading/writing Class 14: Review activity / test Final exam week: TOEIC online |
教科書 /Textbook(s) |
All materials will be provided by the professor via Moodle and in-class |
成績評価の方法・基準 /Grading method/criteria |
Active participation: 15% Weekly vocabulary quizzes: 30% Mid-term vocabulary test: 25% End-term vocabulary test: 30% Students are required to take the TOEIC test in class during the final exam week to pass this course. Student obligations It is the responsibility of students to read the syllabus and complete all assignments, quizzes, and tests on time. If you do not bring the materials you need to class, you will be considered ‘absent.’ If you are exceed the maximum number of absences allowed, the final grade will be an F regardless of your final score for the course. Academic integrity Cheating/plagiarizing other’s work is not allowed. Sometimes the instructor will ask you to complete work in pairs or small groups, and sometimes individually. When working by yourself, you are not allowed to copy other students’ work. |
履修上の留意点 /Note for course registration |
You will need to spend time learning the vocabulary outside of class time. |
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開講学期 /Semester |
2022年度/Academic Year 1学期 /First Quarter |
---|---|
対象学年 /Course for; |
3rd year , 4th year |
単位数 /Credits |
2.0 |
責任者 /Coordinator |
BLAKE John |
担当教員名 /Instructor |
BLAKE John |
推奨トラック /Recommended track |
- |
先修科目 /Essential courses |
- |
更新日/Last updated on | 2022/01/11 |
---|---|
授業の概要 /Course outline |
The primary aim of this content-based course is to enable participants to create a prototype authorship analysis tool using Python. Participants are first introduced to similarity detection and authorship attribution. Texts are then analyzed linguistically by both genre type and author. Case studies involving solving crimes using forensic evidence are used. Participants then develop a natural language processing (NLP) pipeline to detect similarities and differences of language features among a dataset of texts. Detection will involve both rule-based parsing and machine learning. Participants will practice the four language skills required to function in an English language environment. The course culminates in a software demonstration. |
授業の目的と到達目標 /Objectives and attainment goals |
By the end of the course participants will: (a) understand how language analysis can be used to solve crimes (b) explain how authorship can be detected (c) create a natural language processing pipeline in Python to analyze authorship |
授業スケジュール /Class schedule |
This content of the course will be tailored to the requirements of the participants by the class teacher. Block 1 Authorship and language Session 1 Solving crimes using authorship analysis Session 2 Types of authorship analysis Session 3 Language as a fingerprint Session 4 Similarity detection Session 5 Case study I Session 6 Case study II Session 7 Review Block 2 Prototype development Session 8 Introduction to NLP using Python Session 9 Introduction to the Natural Language Toolkit (NLTK) Session 10 Scenario: Problem breakdown Session 11 Prototype development I Session 12 Prototype development II Session 13 Prototype development III Session 14 Demonstrations Session 15 Final Exam |
教科書 /Textbook(s) |
No textbook. Materials will be provided. |
成績評価の方法・基準 /Grading method/criteria |
Active participation: 30% Coursework: 30% Final exam: 40% Students are required to take the TOEIC test in class during the final exam week to pass this course. |