30040002 Introduction to Information and Data Sciences

Hiroshima University Syllabus

Japanese

Academic Year 2024Year School/Graduate School Liberal Arts Education Program

Lecture Code 30040002 Subject Classification Information and Data Science Courses

Subject Name 情報・データ科学入門[1文,1理数,1理生,1工一,1情]

Subject Name
（Katakana）ジョウホウ・データカガクニュウモン

Subject Name in
English Introduction to Information and Data Sciences

Instructor INAGAKI TOMOHIRO,IWASAWA KAZUO,OKAMOTO KAZUKO,NAKASHIMA KENICHIRO,MURAKAMI YUKO,HIKITA ATSUSHI,MIYAO JUNICHI,KAJIMOTO TSUYOSHI,SUMIYA TAKAHIRO,NAGATO YASUSHI,YAMAMOTO MIKIO

Instructor
(Katakana) イナガキ　トモヒロ,イワサワ　カズオ,オカモト　カズコ,ナカシマ　ケンイチロウ,ムラカミ　ユウコ,ヒキタ　アツシ,ミヤオ　ジュンイチ,カジモト　ツヨシ,スミヤ　タカヒロ,ナガト　ヤスシ,ヤマモト　ミキオ

Campus Higashi-Hiroshima Semester/Term 1st-Year,  First Semester,  2Term

Days, Periods, and Classrooms (2T) Weds1-4：Online,IAS K110

Lesson Style Seminar Lesson Style
(More Details) 　

Lecture and exercise, PC will be used

Credits 2.0 Class Hours/Week 　 Language of Instruction J : Japanese

Course Level 1 : Undergraduate Introductory

Course Area（Area） 21 : Fundamental Competencies for Working Persons

Course Area（Discipline） 08 : Information Education

Eligible Students

Keywords Information science, data science, information ethics, survey, programming, AI

Special Subject for Teacher Education 　 Special Subject 　

Class Status within
Liberal Arts Education Students learn information and data sciences as fundamental knowledge and skills of all the class.
Expected Outcome 1. Students will be able to properly communicate based on the knowledge and skills of information and data sciences.
2. Students will be able to explain required information ethics and social problems to use the data.

Class Objectives
/Class Outline The purpose of this class is to introduce students to fundamental knowledge and skills to use data and computer in an appropriate manner. Students will be able to solve problems in an information-oriented society in consideration for an information ethic.

Class Schedule lesson1 Guidance, artificial intelligence and society
lesson2 Data science and society (lecture)
lesson3 Information, data, AI and computer (lecture)
lesson4 Information, data, AI and computer (exercise)
lesson5 Computer network (lecture)
lesson6 Computer network (exercise)
lesson7 Programing (lecture)
lesson8 Programing (exercise)
lesson9 Artificial intelligence (lecture)
lesson10 Questionnaire survey (lecture)
lesson11 Questionnaire survey (exercise)
lesson12 Accessibility (lecture)
lesson13 Media literacy (lecture)
lesson14 Media literacy (exercise)
lesson15 Media literacy (exercise)
Information ethics (online)

Basically, online tests are assigned for (lectures), reports are assigned for (exercises), and online courses are assigned online exams.

Text/Reference
Books,etc. Basically, teaching materials will be provided online. Related books are instructed during class.

PC or AV used in
Class,etc. 　

(More Details) Text, handout, Web, PC

Learning techniques to be incorporated 　

Suggestions on
Preparation and
Review Follow instructions at the guidance and each class. Finish the online course within the specified period.

Requirements The class room is specified for each fresh student. You will be able to find it on the bulletin bord.

Grading Method Lecture: Assignments (about 45%)
Exercise: Active participation in classes, assignments  (about 45%)
Online: Online examination (about 10%)

Practical Experience Experienced

Summary of Practical Experience and Class Contents based on it Teachers who have work experience in information system are doing exercises based on their experience.

Message In this class PC will be used. It is not a class to learn PC and application software.

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	Liberal Arts Education Program
Lecture Code	30040002	Subject Classification	Information and Data Science Courses
Subject Name	情報・データ科学入門[1文,1理数,1理生,1工一,1情]
Subject Name （Katakana）	ジョウホウ・データカガクニュウモン
Subject Name in English	Introduction to Information and Data Sciences
Instructor	INAGAKI TOMOHIRO,IWASAWA KAZUO,OKAMOTO KAZUKO,NAKASHIMA KENICHIRO,MURAKAMI YUKO,HIKITA ATSUSHI,MIYAO JUNICHI,KAJIMOTO TSUYOSHI,SUMIYA TAKAHIRO,NAGATO YASUSHI,YAMAMOTO MIKIO
Instructor (Katakana)	イナガキ　トモヒロ,イワサワ　カズオ,オカモト　カズコ,ナカシマ　ケンイチロウ,ムラカミ　ユウコ,ヒキタ　アツシ,ミヤオ　ジュンイチ,カジモト　ツヨシ,スミヤ　タカヒロ,ナガト　ヤスシ,ヤマモト　ミキオ
Campus	Higashi-Hiroshima	Semester/Term	1st-Year, First Semester, 2Term
Days, Periods, and Classrooms	(2T) Weds1-4：Online,IAS K110
Lesson Style	Seminar	Lesson Style (More Details)
Lecture and exercise, PC will be used
Credits	2.0	Class Hours/Week		Language of Instruction	J : Japanese
Course Level	1 : Undergraduate Introductory
Course Area（Area）	21 : Fundamental Competencies for Working Persons
Course Area（Discipline）	08 : Information Education
Eligible Students
Keywords	Information science, data science, information ethics, survey, programming, AI
Special Subject for Teacher Education		Special Subject
Class Status within Liberal Arts Education	Students learn information and data sciences as fundamental knowledge and skills of all the class.
Expected Outcome	1. Students will be able to properly communicate based on the knowledge and skills of information and data sciences. 2. Students will be able to explain required information ethics and social problems to use the data.
Class Objectives /Class Outline	The purpose of this class is to introduce students to fundamental knowledge and skills to use data and computer in an appropriate manner. Students will be able to solve problems in an information-oriented society in consideration for an information ethic.
Class Schedule	lesson1 Guidance, artificial intelligence and society lesson2 Data science and society (lecture) lesson3 Information, data, AI and computer (lecture) lesson4 Information, data, AI and computer (exercise) lesson5 Computer network (lecture) lesson6 Computer network (exercise) lesson7 Programing (lecture) lesson8 Programing (exercise) lesson9 Artificial intelligence (lecture) lesson10 Questionnaire survey (lecture) lesson11 Questionnaire survey (exercise) lesson12 Accessibility (lecture) lesson13 Media literacy (lecture) lesson14 Media literacy (exercise) lesson15 Media literacy (exercise) Information ethics (online) Basically, online tests are assigned for (lectures), reports are assigned for (exercises), and online courses are assigned online exams.
Text/Reference Books,etc.	Basically, teaching materials will be provided online. Related books are instructed during class.
PC or AV used in Class,etc.
(More Details)	Text, handout, Web, PC
Learning techniques to be incorporated
Suggestions on Preparation and Review	Follow instructions at the guidance and each class. Finish the online course within the specified period.
Requirements	The class room is specified for each fresh student. You will be able to find it on the bulletin bord.
Grading Method	Lecture: Assignments (about 45%) Exercise: Active participation in classes, assignments (about 45%) Online: Online examination (about 10%)
Practical Experience	Experienced
Summary of Practical Experience and Class Contents based on it	Teachers who have work experience in information system are doing exercises based on their experience.
Message	In this class PC will be used. It is not a class to learn PC and application software.
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.

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