Advanced Study in Information Science 1

Course Title

Course Title in English

Advanced Study in Information Science 1

Course Type

-

Research Guidance Course

Eligible Students

Graduate School of Information Science

Target Grade

2Year

Course Numbering Code

KIIMD6MCA3

Credits

2.00Credits

The course numbering code represents the faculty managing the subject, the department of the target students, and the education category (liberal arts / specialized course). For detailed information, please download the separate manual from the upper right 'question mark'.

Type of Class

演習 (Seminar)

Eligible Year/Semester

Spring semester 2026

(Spring semester)

Instructor

Rashed Essam

Affiliation

Graduate School of Information Science

Language of Instruction

English

Related SDGs

3／4

Office Hours and Location

（Tue）10:00 〜 12:00 【Faculty office】

Contact

rashed@gsis.u-hyogo.ac.jp

Corresponding Diploma Policy

A double circle indicates the most relevant DP number and a circle indicates the associated DP.

Corresponding Undergraduate School DP

ー

Corresponding Graduate School DP

3◎／2〇

Corresponding University-Wide DP

N/a

Academic Goals of Teacher Training Course

ー

Course Objectives and Learning Outcome

Based on the results of "Basic Study in Information Science 1" and 2, the ultimate goal is to be able to publish an academic paper and write a master's thesis, and acquire the ability to actually carry out research and development through dissertation research, various surveys, software development, experiments, analysis, etc.

Subtitle and Keywords of the Class

Course Overview and Schedule

Consult with the instructor in charge and create a research guidance plan. This plan will include the research title (tentative) and research outline (background, content, methods, etc.). Research will be conducted according to this plan, and a research progress report will be provided at the end of the first term. After receiving feedback, submit a research progress report that reflects that feedback to the graduate school.

[About the use of generation AI]
Reports, essays, dissertations, etc. are assumed to be created by students themselves, so they cannot be created using generative AI alone.

In-person/Remote Classification

In-person

Implementation Method and Remote Credit Limit Application

Uses of Generative AI

Limited permission for use

Precautions for using Generative AI

レポート，小論文，学位論文等については、学生本人が作成することを前提としているため、生成系AIのみを用いて作成することはできません。

Textbook

The instructor in charge will notify you separately.

References

The instructor in charge will notify you separately.

Contents and Estimated Time for Pre- and Post- Learning (Preparation and Review)

Contents of Active Learning

Through reporting and discussion, students will develop the skills and attitudes necessary to formulate and verify their own hypotheses.

Grading Criteria and Methods

Comprehensively evaluation of the degree of understanding of potential issues, presentation style, persuasiveness, insight into the process and results, self-critical ability, ability to make calm judgment in presentation, etc.

How to Disclose Assignments and Exam Results

Provide individual research guidance.

Precautions and Requirements for Course Registration

Practical Education

Not applicable.

Remarks

In cases where any differences arise between the English version and the original Japanese version, the Japanese version shall prevail as the official authoritative version.

Syllabus data