KA130001 Practical English II

Hiroshima University Syllabus

Japanese

Academic Year 2024Year School/Graduate School School of Informatics and Data Science

Lecture Code KA130001 Subject Classification Specialized Education

Subject Name 実用英語II

Subject Name
（Katakana）ジツヨウエイゴ２

Subject Name in
English Practical English II

Instructor TING HIAN ANN,GU YANLEI,DOHI TADASHI

Instructor
(Katakana) ティン　ヒェン　アン,コ　エンライ,ドヒ　タダシ

Campus Higashi-Hiroshima Semester/Term 3rd-Year,  Second Semester,  3Term

Days, Periods, and Classrooms (3T) Mon1-4

Lesson Style Seminar Lesson Style
(More Details) 　

Each lecture is followed by a tutorial as a set of two lessons. Lectures are exclusively in English. There will be simple quizzes and exercises to keep students alert. Each week, before 1 PM, the in-class exercises must be submitted.  Solutions for each homework assignment are to be typeset in English with latex and submit as a pair of latex source file and the resulting pdf file.

Credits 1.0 Class Hours/Week 　 Language of Instruction E : English

Course Level 4 : Undergraduate Advanced

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 01 : Mathematics/Statistics

Eligible Students 3rd year students in School of Informatics and Data Science

Keywords

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) ・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data.
・A. Skills related to the development of an information infrastructure, information processing techniques, and technology for producing new added value through data analysis.
・ B. Ability to identify and solve new problems on their own by quantitative and logical thinking based on data, diverse perspectives, and advanced skills for information processing and analysis.
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) Computer Science Program
（Comprehensive Abilities）
・C2. English conversation, reading, and writing skills are necessary for conducting research, good oral presentation skills, documentation skills for open discussion, and communication skills.

Data Science Program
（Comprehensive Abilities）
・C2. English conversation, reading, and writing skills are necessary for conducting research, good oral presentation skills, documentation skills for open discussion, and communication skills.

Intelligence Science Program
（Comprehensive Abilities）
・C2. English conversation, reading, and writing skills are necessary for conducting research, good oral presentation skills, documentation skills for open discussion, and communication skills.

Class Objectives
/Class Outline Rapid globalization brings about a need to develop a practical proficiency in English that is applicable internationally. As a foundation to attain the required English proficiency, this course is about learning a wide range of vocabulary so as to be able to read and comprehend, in English, textbooks, articles, and manuals related to informatics and data science. The ability to express such academic contents in English will be developed. Moreover, the basic communication capability for various areas related to informatics and data science will be cultivated. This course will also be beneficial to students in helping them to acquire the ability to learn English on their own.

Class Schedule Lesson 1 Relations and Orders
lesson2 Tutorial (Exercise with LaTeX)
lesson3 Limits and Continuity of Functions
lesson4 Tutorial (Exercise with LaTeX)
lesson5 Differentiation of Functions
lesson6 Tutorial (Exercise with LaTeX)
lesson7 Applications of the Derivative
lesson8 Tutorial (Exercise with LaTeX)
lesson9 Indefinite and Definite Integrals
lesson10 Tutorial (Exercise with LaTeX)
lesson11 Applications of Integrals
lesson12 Tutorial (Exercise with LaTeX)
lesson13 Double Integrals
lesson14 Tutorial (Exercise with LaTeX)
lesson15 Summary

Each student's performance is evaluated based on the in-class exercises and homework assignment reports. No examination will be conducted.

Critical thinking skills will be introduced through a wide range of applications from radiometric dating to cosmology.

Text/Reference
Books,etc. 微分積分学 by 阿部, 岩本, 島, and 向谷 published by 培風館 (2018)
Everything you need to master Calculus and Differential Equations, online resource https://www.math24.net/

PC or AV used in
Class,etc. 　

(More Details) Slides in the pdf format, which are written with latex's beamer, will be projected with Microsoft Teams

Learning techniques to be incorporated 　

Suggestions on
Preparation and
Review Recommended to revise the contents after each class because they are linearly connected.   Each week, approximately 3 to 5 hours outside of the class are needed for revision and preparation for a report.

Requirements Students need to bring their own laptops for online lectures and tutorials.

Grading Method The credit will be evaluated based on individual reports and in-class exercises. 60/100 point is the minimum requirement. The evaluation is based on (i) fundamental understanding of linear algebra in English, (ii) problem solving skill, (iii) English proficiency demonstrated in the report, (iv) communication skill, (v) Class participation

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

Other

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2024Year	School/Graduate School	School of Informatics and Data Science
Lecture Code	KA130001	Subject Classification	Specialized Education
Subject Name	実用英語II
Subject Name （Katakana）	ジツヨウエイゴ２
Subject Name in English	Practical English II
Instructor	TING HIAN ANN,GU YANLEI,DOHI TADASHI
Instructor (Katakana)	ティン　ヒェン　アン,コ　エンライ,ドヒ　タダシ
Campus	Higashi-Hiroshima	Semester/Term	3rd-Year, Second Semester, 3Term
Days, Periods, and Classrooms	(3T) Mon1-4
Lesson Style	Seminar	Lesson Style (More Details)
Each lecture is followed by a tutorial as a set of two lessons. Lectures are exclusively in English. There will be simple quizzes and exercises to keep students alert. Each week, before 1 PM, the in-class exercises must be submitted. Solutions for each homework assignment are to be typeset in English with latex and submit as a pair of latex source file and the resulting pdf file.
Credits	1.0	Class Hours/Week		Language of Instruction	E : English
Course Level	4 : Undergraduate Advanced
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	01 : Mathematics/Statistics
Eligible Students	3rd year students in School of Informatics and Data Science
Keywords
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)	・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data. ・A. Skills related to the development of an information infrastructure, information processing techniques, and technology for producing new added value through data analysis. ・ B. Ability to identify and solve new problems on their own by quantitative and logical thinking based on data, diverse perspectives, and advanced skills for information processing and analysis.
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)	Computer Science Program （Comprehensive Abilities）・C2. English conversation, reading, and writing skills are necessary for conducting research, good oral presentation skills, documentation skills for open discussion, and communication skills. Data Science Program （Comprehensive Abilities）・C2. English conversation, reading, and writing skills are necessary for conducting research, good oral presentation skills, documentation skills for open discussion, and communication skills. Intelligence Science Program （Comprehensive Abilities）・C2. English conversation, reading, and writing skills are necessary for conducting research, good oral presentation skills, documentation skills for open discussion, and communication skills.
Class Objectives /Class Outline	Rapid globalization brings about a need to develop a practical proficiency in English that is applicable internationally. As a foundation to attain the required English proficiency, this course is about learning a wide range of vocabulary so as to be able to read and comprehend, in English, textbooks, articles, and manuals related to informatics and data science. The ability to express such academic contents in English will be developed. Moreover, the basic communication capability for various areas related to informatics and data science will be cultivated. This course will also be beneficial to students in helping them to acquire the ability to learn English on their own.
Class Schedule	Lesson 1 Relations and Orders lesson2 Tutorial (Exercise with LaTeX) lesson3 Limits and Continuity of Functions lesson4 Tutorial (Exercise with LaTeX) lesson5 Differentiation of Functions lesson6 Tutorial (Exercise with LaTeX) lesson7 Applications of the Derivative lesson8 Tutorial (Exercise with LaTeX) lesson9 Indefinite and Definite Integrals lesson10 Tutorial (Exercise with LaTeX) lesson11 Applications of Integrals lesson12 Tutorial (Exercise with LaTeX) lesson13 Double Integrals lesson14 Tutorial (Exercise with LaTeX) lesson15 Summary Each student's performance is evaluated based on the in-class exercises and homework assignment reports. No examination will be conducted. Critical thinking skills will be introduced through a wide range of applications from radiometric dating to cosmology.
Text/Reference Books,etc.	微分積分学 by 阿部, 岩本, 島, and 向谷 published by 培風館 (2018) Everything you need to master Calculus and Differential Equations, online resource https://www.math24.net/
PC or AV used in Class,etc.
(More Details)	Slides in the pdf format, which are written with latex's beamer, will be projected with Microsoft Teams
Learning techniques to be incorporated
Suggestions on Preparation and Review	Recommended to revise the contents after each class because they are linearly connected. Each week, approximately 3 to 5 hours outside of the class are needed for revision and preparation for a report.
Requirements	Students need to bring their own laptops for online lectures and tutorials.
Grading Method	The credit will be evaluated based on individual reports and in-class exercises. 60/100 point is the minimum requirement. The evaluation is based on (i) fundamental understanding of linear algebra in English, (ii) problem solving skill, (iii) English proficiency demonstrated in the report, (iv) communication skill, (v) Class participation
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
Other
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

Back to syllabus main page