Hiroshima University Syllabus

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Japanese
Academic Year 2024Year School/Graduate School Liberal Arts Education Program
Lecture Code 30040004 Subject Classification Information and Data Science Courses
Subject Name 情報・データ科学入門[1総総,1教,1経]
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,NAKASHIMA KENICHIRO,MURAKAMI YUKO,SENDA TAKASHI,HIKITA ATSUSHI,DING YEPENG,KISHIBA SEIGO,SUMIYA TAKAHIRO,NAGATO YASUSHI,YAMAMOTO MIKIO,WATANABE HIDENOBU,KIMURA AKITAKA
Instructor
(Katakana)
イナガキ トモヒロ,ナカシマ ケンイチロウ,ムラカミ ユウコ,センダ タカシ,ヒキタ アツシ,テイ ヨウホウ,キシバ セイゴ,スミヤ タカヒロ,ナガト ヤスシ,ヤマモト ミキオ,ワタナベ ヒデノブ,キムラ アキタカ
Campus Higashi-Hiroshima Semester/Term 1st-Year,  First Semester,  2Term
Days, Periods, and Classrooms (2T) Fri5-8:Online,IAS K313,IAS L101
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 Outcome1. 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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