Mathematics / Data Science / AI Education Program
Kansai University of International Studies will offer a minor in data science from the 2022 academic year, and has developed a curriculum that complies with the Ministry of Education, Culture, Sports, Science and Technology's "Mathematics, Data Science and AI Education Program" certification system, implementing a university-wide data science education program. This education program was certified as a "Mathematics, Data Science and AI Education Program (Literacy Level)" by the Ministry of Education, Culture, Sports, Science and Technology in August 2023. Furthermore, the curriculum will be revised in the 2025 academic year to allow more students to take this program.
Additionally, the Faculty of Sociology will begin a data science major in the 2021 academic year, and through the subjects of the newly established "Advanced Data Science Human Resources Development Program," aim to cultivate human resources who can acquire practical skills to address challenges in society and business, and who can systematically acquire the necessary applied knowledge of data science and related technologies. This educational program was also certified as a "Mathematics, Data Science, and AI Education Program (Applied Basic Level)" by the Ministry of Education, Culture, Sports, Science and Technology in August 2023. (See related article）
About “Mathematics/Data Science/AI Education Program (Literacy Level)”
Educational Program Name
"Data Science and AI Exploration Program"
Abilities that can be acquired
In recent years, with the development of new information technologies such as artificial intelligence (AI) and big data, we have become a data-driven society where data is omnipresent.In this educational program, we will help you understand the changes occurring in society and how AI and data science are useful in the real world, and then teach you the basics of reading data, explaining data, and handling data. You can acquire knowledge, increase your literacy towards AI and data, and acquire the knowledge required to utilize them.
Courses and completion requirements for the departmental "Data Science and AI Research Program"
This educational program is open to students from all faculties and departments, and students must earn at least five credits from designated courses in their department.
- Each subject is worth two credits, except for Introduction to Research, which is worth one credit. The courses offered by each department are as follows:
By acquiring these credits, you will be certified as having completed this educational program.
| Faculty | Subject | Course subjects (number of credits) |
|---|---|---|
| Faculty of Sociology | Department of Sociology | Basic Statistics (2 credits), Information Literacy (2 credits), Introduction to Data Science (2 credits) |
| Faculty of Health Care | Department of Nursing | Introduction to Research (1 credit), ICT Literacy (2 credits), Data Science (2 credits) |
| Faculty of Education | Department of Education and Welfare | Introduction to Research (1 credit), ICT Literacy (2 credits), Data Science (2 credits) |
| Faculty of Psychology | Department of Psychology | Introduction to Research (1 credit), ICT Literacy (2 credits), Data Science (2 credits) |
| Global Faculty■ | Global Studies | Introduction to Research (1 credit), ICT Literacy (2 credits), Data Science (2 credits) |
| Faculty of Business | Department of Business Administration | Introduction to Research (1 credit), ICT Literacy (2 credits), Data Science (2 credits) |
- New faculties established from 2025
Class methods and content
For the "Data Science" and "Introduction to Data Science" classes, we have developed teaching materials for first-year university students that combine the humanities and sciences and are not dependent on specialization, based on the model curriculum of the "Mathematics, Data Science, and AI Education Program (Literacy Level)."These contents can be used in conjunction with face-to-face classes and on-demand, and each department is working on them.
In each subject, you will study the following items.
Please refer to the file below for detailed study content and correspondence between course subjects.
Reference document
About “Mathematics/Data Science/AI Education Program (Applied Basic Level)”
Educational Program Name
“Advanced Data Science Human Resource Development Program”
Abilities that can be acquired
In this educational program, you will be able to appropriately collect and analyze various data and build systems to utilize AI, so that you can use data to solve problems in society and companies when researching your specialized field or finding employment after graduation. You can learn knowledge and techniques related to the flow up to operation, and acquire practical applied basic skills related to mathematics, data science, and AI.
| Subjects that make up the program | Contents included in the course subjects | Class subject name | Advanced Data Science Human Resources Development Program Credits |
|---|---|---|---|
| Area I: Basic statistics and its application subjects (Basic) |
Statistics and mathematical foundations | Basic statistics (required) Social statistics |
Acquired 4 or more credits |
| Data utilization practice | social research theory | ||
| Area II: ICT Utilization/Data Science Practical Subjects (Introduction/Knowledge) |
Points to keep in mind when utilizing data and AI | Information literacy | Acquired 4 or more credits |
| data literacy | ICT Utilization A (required) (Basic Data Science Exercises) |
||
| Utilization of data and AI in society | Introduction to data science (required) | ||
| Area III: programming Big data/IoT/AI (Application basics) |
AI/Data Science Basics | Software engineering basics Fundamentals of artificial intelligence (required) |
Acquired 4 or more credits |
| AI/data science practice | data science theory Data science practical training (required) |
||
| Area IV: Existing specialized subjects (Specialized basics) |
Data representation and algorithms | Data structures and algorithms (required) Python programming exercise (required) Database basics (required) |
Acquired 6 or more credits |
Courses offered and completion requirements
This educational program constitutes Kansai International University's unique advanced data science human resource development program, and consists of four subject groups from the Faculty of Sociology. (Table below)
In order to complete this educational program, you must earn at least 4 credits from "Area I Basic Statistics and Its Utilization Subjects," at least 4 credits from "Area II ICT Utilization/Data Science Subjects," and "Area III Programming Technology/Area III." Students must acquire at least 6 credits from the "Big Data/IoT/AI basic subject group" and 4 or more credits from the "existing specialized basic subject group" for a total of 16 credits or more.
| Faculty | Major | Course subjects (number of credits) |
|---|---|---|
| Faculty of Sociology | Data science major |
■Area I subject group: |
| Department of Symbiotic Society | ||
| Culture/Media Major |
Class methods and content
In the class, students will acquire practical skills to solve problems in society and businesses by utilizing mathematics, data science, and AI.
You will systematically acquire the necessary knowledge and skills using the structure shown in the table below.
Please refer to the file below for detailed study content and correspondence between course subjects.
Reference document
Implementation system
| committee etc. | role |
|---|---|
| President | Program operator |
| Academic Affairs Committee | Program improvement / evolution |
| Evaluation center | Program self-inspection / evaluation |
Attendance status and self-inspection/evaluation results in 2022
In order to improve and evolve this educational program, starting in 2023, the "Data Science Education Department" set up at Kansai International University will conduct self-inspections and evaluations, and the results will be made public.
We will strive to improve the quality of this educational program while receiving opinions not only from within the university but also from outside the university, such as companies.
Program completion and completion status
The Academic Affairs Committee for 4 announced that the data science minor had a record of 4 students taking the course in 39, with a enrollment rate of 1%, and the advanced data science human resource development program had a record of 4 students taking the course in 54. The results, with 27 students and a 4% enrollment rate, were judged to be good results for the program's first year.Furthermore, regarding the credit acquisition status as of the end of XNUMX, both the data science minor and the advanced data science human resource development program are in good condition, and we are continuing to use the academic affairs web system to monitor the credit acquisition status.
Learning outcomes
The establishment and operation of inspection and evaluation methods for learning outcomes based on the three policies, the inspection of the achievement status of educational objectives, and the devising and development of evaluation methods are mainly conducted by the Evaluation Center and the Higher Education Research and Development Center, and the whole university is involved in We are working on this.The Evaluation Center aggregates and analyzes benchmark achievement levels, achievement confirmation test results, graduation thesis rubrics, student surveys, etc. related to the abilities and qualities listed in the Diploma Policy, and provides information on university councils, faculty meetings, and PD training in order to contribute to educational improvement. Reports are made to the faculty at meetings and other occasions.The First-Year Education Division of the Higher Education Research and Development Center conducts a ``survey on the process of adjustment to university (learning bias)'' regarding student life in November for first- and third-year students and before graduation for fourth-year students. There is.The Evaluation Center also conducts a University IR Consortium student survey (sample survey).In both cases, we survey students about their learning experiences and learning outcomes, analyze trends and problems in student life, and use the results to improve students' learning and lives at PD (Professional Development) training sessions. It is reported at the meeting).Regarding our university's data science education, we used the evaluation tool "IR Conso Student Survey" to compare learning outcomes with other universities, and found that our students have issues in improving their mathematical abilities. .For this reason, it was considered important to strengthen efforts in data science education.
Students' understanding of the content through student surveys, etc.
The Educational Development Division of the Higher Education Research and Development Center conducts mid-term and final class surveys every semester with the aim of reforming classes to an active learning style.Mid-term surveys are conducted by each faculty member in the middle of the semester for two or more courses, and the results are quickly reflected in improvements to the classes in question.In addition, the results of the term-end questionnaire and comments from course instructors are published online within the university, making it possible for students to view them.
According to the results of this student survey, the percentage of students who responded that they ``used information on the Web for class assignments'' was on the rise as a survey item related to data science education, and the percentage of students who responded that ``I used information on the Web for class assignments'' was on the rise. It was also found that the percentage of students who responded that their computer operating skills had improved was also increasing.
Recommendation to other students, such as juniors, based on student surveys, etc.
Until now, our university had not set up a survey item regarding the degree of recommendation of data science education to other students, such as juniors, so we plan to investigate this survey item from 5 onwards.
Progress and achievement of plans to increase the number of students enrolled and the enrollment rate across the university
Starting in 5, a data science education department will be established at the Higher Education Research and Development Center, with plans to improve and evolve data science education in order to increase the number of students and enrollment rates.
