1. Tetsuro Kakeshita Saga University, Japan kake@is.saga-u.ac.jp
National Survey of Japanese Universities on Computing Education Analysis of Non-IT Departments and Courses
Tetsuro Kakeshita
Saga University, Japan
My name is Tetsuro Kakeshita from Saga University, Japan. Today I would like to talk about national survey of Japanese universities on IT education. We present a series of four papers in this session. In my talk, I would like to explain the overview of the survey project first. The survey project contains four different types of surveys. The result and analysis of each survey type will be presented after that.

2. Background and Survey Purpose
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Background and Survey Purpose
First National Survey on IT Education in Japanese Universities
No definition did exist for IT education
Science Council of Japan
Reference Standard of Informatics for University Education (March 2016)
Provide Common BOK for IT Education
Survey Purpose
Understand and analyze current status of IT education
IPSJ utilize the survey result to develop J17 curriculum standard for IT education
Japanese government (Ministry of Education) utilize the survey result to improve national policy for IT education
This is the first national survey on IT education supported by the Japanese government.
Such survey was impossible because no formal definition did exist for IT education. This situation was changed last year. The science council of Japan published the reference standard of Informatics for university education last March. The reference standard provides common body of knowledge for IT education and was supported by the Japanese government so that we now have a formal definition of IT education.
As the first national survey on IT education in Japanese universities, we tried to understand and analyze current status of IT education from various aspects. The information processing society of Japan is planning to develop a new computing curriculum standard called J17. The survey result will be utilized to develop J17. Japanese government, the ministry of education, will utilize the survey result to improve national policy for IT education.

3. Typical Organization of IT Education at Japanese Universities
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Typical Organization of IT Education at Japanese Universities
Academic
Year
IT Department
Non-IT Department D:
IT Education for
High School Teacher License on IT
4-th Year
A: IT Education as a Major Field of Study
B: IT Education as non-Major Subject
3-rd Year
2-nd Year
This is a typical organization of IT education at Japanese universities. ★クリック★ Many of the college students take courses of general IT education in order to learn computer and network literacy and fundamentals of computer software and hardware typically at their first academic year. The students belonging to IT department take IT courses as a major field of study. Also some of the students belonging to non-IT departments also take some IT courses as a part of their major field of study. This is because the general IT education is not enough for such students.
In Japan, a student willing to become a high school teacher must have a teacher license. Many Japanese universities provide education program for the teacher license for each subject such as IT, mathematics, etc.
C: General IT Education
1-st Year
Computer/network literacy, fundamentals of software and hardware

4. Campus network, servers, LMS, educational software
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Survey Type A～E
Type
Survey Description
Presenter A
IT Education at a department or a course majored in IT discipline - B
IT Education at a non-IT department or a course as part of their major field of study
Kakeshita C
General IT education for all university students typically at the first or second academic year D
IT education program for high school teacher license on IT education
Sumi E
Computing environment for IT education
Ohtsuki
Considering the typical organization of IT education at Japanese universities, we defined five types of survey. The survey type A is for the IT education at an IT department or course. The survey type B is for the IT education at a non-IT department or a course as a part of their major field of study. Survey type C is for the general IT education for all university students so that a university typically responds to the survey type C. The survey type D is for the IT education program for high school teacher license on IT education.
In addition to the above four types of surveys, we also define survey type E for the computing environment for IT education. ★クリック★ Survey type E covers campus network, various types of servers, lecture management system, PCs, educational software etc. These are necessary for successful IT education at the universities.
Campus network, servers, LMS, educational software

5. Survey Questions for Type A～D
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Survey Questions for Type A～D
Organization Name
University, Faculty, Department, Course
Respondent
Education committee member, secretariat staff, faculty member
Program Organization
Daytime, night or remote program
Category of specialty
Specific domain within computing discipline
Required # of credits for graduation
# of subjects
Quality and Quantity of Educational Achievement
Enrolled Students
Academic year
# of students
Future course after graduation
Teaching Staff
# of faculty members, educational background, specialized field, tenure
Support staff
Teaching Assistant
Educational Environment
Computer System
Student’s own PC
Student PC utilization
Educational programming language
Other Topics
Future Plan, Strength, IT certification, etc.
This is a list of survey questions for type A to D. Although the detailed questions are different, overall organization of the questions are common. The survey questions are selected to cover all aspects of the IT education.
We first ask organization name and the information about the respondent. The program organization such as category of specialty and the required number of credits for graduation is collected as fundamental attributes of each department or a faculty. We also collected the data about students, teaching staff, and educational environment.
The main part of the survey is the quality and quantity of educational achievement. Its details are explained in the next slide.

6. Survey Schedule Preparation Phase (Oct. 2016) Contract with MEXT
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Survey Schedule
Preparation Phase (Oct. 2016)
Contract with MEXT
Define Survey Questions
Survey system set up
Document Preparation (User Manual, Detailed Instruction)
Formal Request Letter
Survey Phase (Nov-Dec. 2016)
Accepting Registration
Provide Answers to Questions
FAQ Preparation
Progress report (MEXT)
Deadline Extension
Excel Macro Development
Analysis Phase (Jan-Mar. 2017)
Review of Answers
Request for Correction
Data Analysis
Accepting Answers after Deadline
Analysis Report
Symposium
The five types of surveys are executed last autumn. We prepared the survey during last October. We defined the survey questions and set up the web-based survey system. After the preparation of various user document such as user manual and detailed instruction of the survey questions, we sent the formal request letter to the 750 universities in Japan.
The survey starts at the beginning of November. We received more than 500 questions from the universities during the suvery and answered to all of them. Through the survey, we collected about 3000 answers from the universities. The survey end at the end of last December.
From the beginning of this year, we reviewed the collected answers and request the users for possible correction. Although the analysis is still in progress, this presentation contains the preliminary analysis result.

7. Response Rate Summary University Type Total National Public Private
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Response Rate Summary
University Type
Total
National
Public
Private
# of Universities 82 86
590
758
# of Universities which create at least one account at the survey system 79 73
499
651
N/A (Quitting, do not provide IT education) 7
Response Rate
96.3%
84.9%
85.6%
86.7%
Now I will explain the preliminary result of the survey.
This is the summary of the response rate. There are 758 universities in Japan. We sent the request letter to all of them. Among these universities, 651 created at least one account at the survey system. The overall response rate is 86.7%. The response rate is particularly high for national universities. This response rate is achieved under the support of the Japanese Ministry of Education. The seven universities are not applicable because they are quitting or they do not provide IT education. Anyway, these are the quite rare cases. You can understand from this table that the reliability of our survey is quite high.

8. Number of Answers for Each Survey Type
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Number of Answers for Each Survey Type
Survey Type
University Type
Total
National
Public
Private
A: IT Department 84 35
177
296
B: non-IT Faculty/Department
302 64
632
998
C: General IT Education 96 69
574
739
D: IT Education for High School Teacher License on IT 85 18
235
338
E: Educational Computer System
128 73
368
569
695
259
1,986
2,940
This table illustrates the number of answers for each survey type. As a total, we collected 2940 answers for the five types of surveys. ★クリック★ Note that each answer is provided by a university, faculty, department or a course. So you should note that the number of answers do not correspond to the actual number of department or faculties.
Note
Answer is provided by univ., faculty, dept. or course
Number of answers do not correspond to the actual number of departments/faculties

9. Analysis of Survey Type B non-IT department and course
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Analysis of Survey Type B non-IT department and course
I would like to explain the analysis result of survey type B from the next slide.

10. Survey Type B: non-IT Faculty/Dept.
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Survey Type B: non-IT Faculty/Dept.
IT Educations
All
Academic Discipline
# of
Answers
# of Students
Our Survey
National Stat.
Ratio
Medicine and Dentistry 40
3,438
11,765
29%
Physical Science 79
4,969
18,523
27%
Engineering
227
23,151
88,062
26%
Social Science
253
31,428
204,933
15%
Others
102
7,979
56,019
14%
Agriculture 33
1,824
18,042
10%
Pharmacy and Nursing 85
5,734
58,824
Education 56
2,599
46,475 6%
Domestic Science 22
926
17,787 5%
Humanities 82
4,568
88,246
Art 19
645
18,189 4%
Total
998
87,261
626,865
High necessity
This table represents the number of answers and students belonging to survey type B, non-IT faculty and department. We can observe that all academic disciplines requires IT education as a part of their educational program. So we recognize that IT is a meta science, which is closely related to all academic disciplines. This is one point. Next observe the number of students. ★クリック★ These are the numbers of the students we collected through the survey type B taking the IT education. At least 87,000 students are learning IT at non-IT faculty or department. ★クリック★ These are the number of all students collected by the Japanese government through annual national statistics. The ratio of these two numbers corresponds to the necessity of IT education at each academic discipline. ★クリック★ Such necessity is high at medicine and dentistry, physical science and engineering. But the necessity is low at domestic science, humanities and art. General IT education is considered to be enough at these academic disciplines.
Low necessity

11. Survey of Educational Achievement
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Survey of Educational Achievement
Estimate Quality and Quantity of Achievement in IT Education
6 Achievement Levels
Knowledge Level
Skill Level
21 Domain, 90 Topic
Reference Standard BOK for Informatics
J07-GEBOK
Level
Knowledge
Skill
No Knowledge
No Skill 1
Simple Exercise 2
Know
Some Exercise 3
Explain
Complex Exercise 4
Explain Relationship
Autonomously Perform 5
Teach Knowledge
Teach Skill
The survey of educational achievement is executed to estimate quality and quantity of IT education.
In order to estimate quality, we define six achievement levels for knowledge and skill represented in this table. For the knowledge level, we define five levels know, explain, explain relationship with related concepts, and teach the concept to others. For the skill, three levels are defined based on the complexity of the exercise. At level 4, student can perform the requested skill by himself. This is a typical level achieved through the graduation research project.
We also define body of knowledge utilizing the reference standard for informatics. The BOK contains 90 topics classified by 21 domains.

12. Sections, Domains and Topics of BOK
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Sections, Domains and Topics of BOK
Section
Domain
# of Topics
J07-GEBOK
General IT Education 9
Reference Standard for Informatics
(A) General Principles of Information 6
(B) Principles of information processing by computers
Information Transformation and Transmission 4
Information Representation, Accumulation and Management
Information Recognition and Analysis
Computation
Algorithm 8
(C) Technologies for constructing computers that process information
Computer Hardware 3
I/O Device
Fundamental Software
(D) Understanding humans and societies that process information
Process and Mechanism for Information Creation and Transmission 2
Human Characteristics and Social System
Economic System and Information
IT-based Culture
Transition from Modern Society to Post Modern Society
(E) Technologies and organizations for constructing and operating systems that process information in societies
Technics for Information System Development 7
Technics to Obtain Information System Effect
Social System Related to Information
Principle and Design Methodology for HCI
Professional Competency for IT Students
Generic Skill for IT Students
This is the list of 21 domains. Among the domains, one comes from general IT education. The other domains come from the reference standard for informatics. The reference standard contains five sections A to E representing the knowledge areas of informatics. The knowledge areas are the general principles of information, principles of information processing by computers, technologies for constructing computers that process information, understanding humans and societies that process information, and technologies and organizations for constructing and operating systems that process information in societies.
The variety of sections indicates the diversity of the informatics. It should also be noted that the reference standard defines professional competency and generic skill for IT students. This implies the importance of practical skill and competency related to IT.

13. Knowledge Effort Classified by BOK Section
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Knowledge Effort Classified by BOK Section
This is the ratio of effort at each section of the common body of knowledge. The effort is calculated by a multiplication of the achievement level and the number of students and by summing up the multiplied values. The distribution of the effort values represents focus of computing education at each academic discipline. For example, health and agriculture focus on general computing education. Engineering and physical science disciplines focus on section B, princicples of information processing by computers.

14. Cluster Dendrogram of Academic Disciplines
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Cluster Dendrogram of Academic Disciplines
This dendrogram represents similarity among academic disciplines. The similarity is defined by the distance of the effort distribution at each section of the common BOK. The height represents the similarity. So physical science and engineering are most similar among the disciplines. The pairs of agriculture and education, social science and others are also similar. This implies that similar academic disciplines can share the same computing curriculum. On the other hand, different computing curricula will be required for these two academic clusters. We are planning to call for cooperation to these academic disciplines to develop computing curricula suitable for their disciplines.

15. Achievement Level Summary
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Achievement Level Summary
Engineering Discipline
This boxplot represents the distributions of the achievement levels for the BOK sections of the engineering discipline. The upper boxplot represents knowledge level distribution. The lower boxplot represents skill level distribution. You can observe that non-IT departments are focused on general IT education represented by GEBOK. Particularly these departments are more focused on teaching knowledge rather than skill since the median of the knowledge level is 1 for GEBOK.

16. Detailed Achievement Level Distribution
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Detailed Achievement Level Distribution
Let’s examine the detailed level distribution of each topic of the GEBOK, representing general computing education. Meaning of the topics 101 to 109 are described here. You can observe that the knowledge level is highest for topic 109, computer literacy, while the knowledge level is lowest for topics 101 and 107, i.e. information and communication, and information systems. The knowledge levels for these 5 topics are higher than 2 so that we can expect that at least half of the departments is teaching these topics. As for the skill, the levels for topics 104 and 109 are high, i.e. algorithm and programming, and computer literacy. Such level distribution is useful to determine realistic levels for each topic.
101: Information and Communication, 102: Digitalization of Information, 103: Computing Elements and Organization, 104: Algorithm and Programming, 105: Data Modeling and Operation, 106: Information Network, 107: Information Systems, 108: Information Ethics and Security, 109: Computer Literacy

17. Ratio of Faculty Members Teaching Computing Subject
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Ratio of Faculty Members Teaching Computing Subject
This is the ratio of faculty members teaching computing subject. About 9000 teachers are employed to teach computing subjects at non-IT departments. The ratio of full-time teacher is higher at national universities than private universities. This is because private universities do not usually have enough budget to hire full time faculty members. Since it is often observed that communication among part-time teachers, students and full-time faculty members becomes insufficient, there is a risk of insufficient computing education at these universities.

18. 2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Ratio of Computing Department Graduates and Faculty Members Majored in Computing Discipline
It is important that the faculty members teaching computing subjects have enough ability and expertise on computing discipline. So we checked the ratio of teachers whose major is computing and the ratio of computing department graduates. The result is illustrated in this figure. Unfortunately the ratio is not high. It is often observed that a department does not have enough number of full-time teachers majored in computing discipline so that the department hires part-time teacher with more expertise in computing discipline. There are two major reasons of this. One is that the number of Ph.D holders of the computing discipline is not enough. The other is that non-IT department tends to hire a specialist of their own major.

19. Summary and Future Work
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Summary and Future Work
Observed Facts
87,261 students are taking IT subjects as non-IT major
IT education required at many academic disciplines
Difference of effort distribution among academic disciplines
Lack of teachers majored in computing discipline
Utilization of Survey Result
J17 curriculum development (computing education as a minor)
Improvement of IT education at Japanese universities
Future Plan
Relationship analysis among survey types A to E
We obtained various facts through the national survey on IT education at Japanese universities. In case of the survey type B for computing education at non-IT department, at least 100,000 students are taking IT subjects as non-IT major. The number of students taking IT subject is more than three times larger than the number of students majored in computing discipline. This means that IT education is required at many academic disciplines. We also analyzed the difference of computing education at various academic disciplines by using effort distribution. The analysis result will be utilized to develop new curriculum for computing education as a minor discipline. We also have a plan to analyze relationship among various survey types as a future plan.
This is the end of the explanation of the survey type B. I will make another presentation for the survey type C for general computing education. Please wait until the end of the presentation for possible comments and questions.

20. 2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan

21. Survey Worksheet for Educational Achievement
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Survey Worksheet for Educational Achievement
Download survey worksheet
Fill out the worksheet
Upload the completed worksheet
Knowledge Level Definition
Skill Level Definition
Knowledge Level
Topics of General IT Educations
Skill Level
This is the survey worksheet for educational outcome. The users download the survey worksheet from the survey web site. The worksheet contains the definitions of knowledge and skill levels. ★クリック★ These are the topics of the general IT education. The remaining domains and topics come from the reference standard for informatics. Each user is requested to fill these three columns. ★クリック★ This column represent the knowledge level at each topic. This column presents the skill level. So these two columns represents quality of education at each topic. ★クリック★ The third column represents the number of students taking the courses so it represents quantity of educational outcome at each topic.
# of Students taking the courses
Domains and Topics of Reference Standard for Informatics

22. Web-based Survey System Cresie
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Web-based Survey System Cresie
Designed to be used for various kind of surveys related to educational outcome and/or requirement
A survey responder needs to create an account at the survey system
We have developed the web-based survey system named cresie. The system was designed to be used for various kind of educational surveys. A survey responder first needs to create an account at the survey system for corresponding survey type. This is necessary since we do not know all of the departments teaching IT in advance. ★クリック★ When a responder log-in to the survey system, the responder can answer to the survey questions by filling out these blanks. ★クリック★ A responder downloads the survey worksheet for the educational achievement from this window. ★クリック★ This is a sample of the survey worksheet.

23. Number of Responses Univ. Type Course Department Faculty or University
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Number of Responses
Univ. Type
Course
Department
Faculty or
University
Total
National 62
173 67
302
Public 12 34 18 64
Private
456
109
632
141
663
194
998
This table represents the number of courses, departments and faculties which respond to the survey. Although specialized computing education is usually provided by either a course or a department, we allow a faculty or a university to respond to the survey by combining multiple courses and/or departments. A national university is founded by the Japanese government while a public university is founded by a local government such as a city or a prefecture. From this table, we can say that computing education is mainly provided by departments at non-IT department and courses.

24. Number of Required Credits for Computing Subjects
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Number of Required Credits for Computing Subjects
This figure represents the distribution of the number of required credits for computing subjects for each academic discipline. The distribution is illustrated using box plot. The thick line represents the median value. So you can observe that engineering discipline assigns the largest number of credits to the computing education. The right side of each box represents the upper 25% value. The left side of each box represents the lower 25% value. These values can be utilized to determine realistic guideline for curriculum development. For example, the lower 25% value can be used to determine minimum requirement at each discipline. The upper 25% value can be used to determine recommendation.

25. Distribution of the Number of Students per Teacher
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Distribution of the Number of Students per Teacher
This figure represents the distribution of the number of students per teacher for the computing subject. The distribution greatly change depending on the academic disciplines. For example, let’s examine the engineering discipline. The range of the number of students per teacher is lower than % of the departments belong to this range so that it is reasonable to define an accreditation criteria for the number of students per teacher at the upper bound of the range. Is the number of students per teacher is less than the lower bound, then it will become a strong point of the department.

26. Support Staff and Teaching Assistant for Computing Subject
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Support Staff and Teaching Assistant for Computing Subject
Univ. Type
Support Staff
Teaching Assistant
# of Staffs
# of Subjects
Workload
(man hour)
# of subjects
National
166 74
42,390
818
Public 3 4
13,785
111
Private
434
432
73,125
1,889
Total
603
510
129,300
2,818
This table represent the statistics of the support staff, usually full-time staff, and teaching assistant, usually students working as part timers. The number of computing subjects supported by them is greatly different for the two cases. Again this is mainly caused by the financial restriction. But from this table, we can observe that teaching assistants are quite important for exercise in computing subjects.

27. Utilization of Educational Computer System
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Utilization of Educational Computer System
Utilization
# of Answers
# of Enrolled Students
Shared Computer System at University
356
38,148
Shared Computer System at Campus
141
12,839
Shared Computer System at Faculty 69
6,298
Private Computer System at Department 59
4,306
Computer System is provided but unused 43
4,201
No Educational Computer System
330
21,471
Total
998
87,261
This table illustrates the utilization of educational computer system provided by the university side. Such computer system is typically composed of training rooms equipped with PCs and educational software. LMS servers may also be equipped. Such educational computer system is important to provide computer exercises for the skill up of the students. Although the departments usually have some kind of educational computer systems, 1/3 of the departments do not have any educational computer system. Financial support will be required for such departments. Since the percentage of the number of students is lower than the percentage of the number of answers, many of such departments are small departments.

28. Utilization of Student PC
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Utilization of Student PC
Utilization
# of
Answers
# of Enrolled
Students
All Students of the University must have PC 69
4,384
All Students of the Faculty must have PC 34
3,496
All Students of the Department/Course must have PC 26
2,335
Students are recommended to purchase PC 65
4,744
Purchasing of Student’s own PC is optional
804
72,304
Total
998
87,261
This table represents the utilization of student PC. Although PC price is getting down, 80% of the departments do not require students to purchase PC. We also find the departments with no educational computer system and which do not require students to purchase PC. We are interested in the computing education at such departments. Visiting of such departments are left as future work.

29. Popular Educational Programming Language
2017/9/12
Tetsuro Kakeshita, ICDIM 2017, Fukuoka, Japan
Popular Educational Programming Language
Programming
Language
Score C
466
Visual Basic
254
Java
146
C++
108
JavaScript 77
Fortran 63
SQL 31
Programming
Language
Score
Python 29
Ruby 25
PHP 22 R 20
Processing 15
Assembly Language 13
Matlab 11
This is a ranking of popular educational programming languages. Although many programming languages are utilized, popular languages are the top 4 of this list. They are rather traditional ones.