1. Purpose of “visualization”

To identify the workforce’s learning needs in various sectors within the industry, as this would provide effective insights for universities and other educational institutes that seek to examine the state of their own education curricula. To compare learning needs in different industry categories and professions in order to help faculties and university departments improve their education system.

Visualization based on questionnaire surveys filled out by the industry workforce is used to analyze longitudinal changes in their specialized knowledge acquisition needs.

Visualization of how people educated in university educated people are contributing to the society, and are treated in it,the society is used to promote industry and universities for the purpose of developinguniversityes to aim develop more effective human resource development.

2. “Visualization” method

2.1 Survey projects used for “visualization”

A) An Industrial Science and Technology Survey Project (METI 2014FY) called “Mismatch survey of qualitative and quantitative supply and demand of human resources in industry and educational institutes” was conducted (a web-based questionnaire, commissioned to Cross Marketing Inc.) from late January to early February, 2015. The total number of responses was 73,612. Details of the survey are available at:

https://dl.ndl.go.jp/info:ndljp/pid/11280295

B) An Industrial Science and Survey Project (METI 2016FY) called “Fact-finding survey of education in specialized fields and at universities sought for industry personnel, especially in science and engineering” was conducted (a web-based questionnaire, commissioned to Cross Marketing Inc.) in January 2017. The total number of responses was 66,528. Details of the survey are available at:

https://dl.ndl.go.jp/info:ndljp/pid/11274020

C) A Science and Technology Basic Survey Outsourcing Project (Cabinet Office 2019FY) called “Matching survey of qualitative and quantitative supply and demand for industry and educational institute personnel” was conducted (a web-based questionnaire, commissioned to Cross Marketing Inc.) from December 2019 to January 2020. The total number of responses was 78,351.

2.2 Data and related information used for “visualization”

2.2.1 Basic information of questionnaire respondents

Responses were tallied from adults aged between 20 and 44 years, who graduated from a technical college, university, or graduate school, and are employed full-time, on a contract, or are self-employed.

2.2.2 Main question items

Respondents reported the following: the field of their specialized knowledge they obtained at university laboratories (field of specialty) (one field), the correlation between their field of specialty and their work, job satisfaction, annual income level, specializations that arefields of specialty important for their present work (top three fields), and specialization fields that areof specialty important for the future development and growth of their business (top three fields).

Specialized knowledge fields were categorized into 265 items corresponding to detailed items for Grants-in-Aid for Scientific Research (KAKENHI).

2.2.3 Implementation

The FY 2014 and FY 2016 surveys were conducted by METI; the FY 2019 survey was conducted by the Cabinet Office (commissioned to Kawaijuku Educational Institution).

3. “Visualization” results

3.1 How much the field of specialty relates to work, job satisfaction, and annual income level

3.1.1 Analysis according to differences in professions

3.1.2 Analysis according to differences in educational backgroundsbackground in technical, administrative, and professional fields

Across different professionsWhatever the profession, relevance to work, job satisfaction, and income levels, the effects of educationlevel tend to be least to most importantgreater, in the following order: of technical college/bachelor’s degree < master’s degree < doctoral degree.  

People with doctoral degrees are likely to work as instructors and researchers at universities involved in technology research and development or professional positions, whereas they seldom work as administrative staff.

In all professions, annual income levels tend to increase with age, such that someone in their 30s and 40s will earn more than in their 20s. In recent years, however, the annual income levels of people with doctoral degrees are notably high in the category of technology research for people in their 20s.

3.1.3 Analysis according to regular and non-regular employment in industrial research and development and academic research

Regular staff with doctoral degrees tend to show high levels of job satisfaction in industrial or academic research, as well as high annual income levels. In addition, annual income levels also tend to increase with age.

There are many non-regular employees with doctoral degrees in academic research, showing high levels of job satisfaction and low levels of annual income. In addition, annual income levels do not increase with age.

In recent years, regular technology research staff with a doctoral degree have shown a marked increase in annual income levels in their 20s.

3.1.4 Analysis of people with doctoral degrees and high annual income levels in the industry, and non-regular staff in academia

Those with doctoral degrees working as regular research staff in the industry tend to show a relatively high annual income level in their 20s; over half of them work in the mechanical field.

Few people with doctoral degrees work as non-regular research staff in the industry, and there they is have no inclination in toward a particular their specialized fields of specialty.

There is a relatively high number of non-regular research staff with doctoral degrees working in academia, and most of them specialize in the fields of humanities and biology.

3.2 Specialized fields critical to corporate management, business development, and growth

3.2.1 Analysis of trends per type of company and industry

When examining trends onin the needs of education and research in industry categories with many respondents -, such as information, machinery, and electricity -, there is a lot ofgreat variation in the in needs, depending on the type of industry.

On average, education needs in the information, mechanical, and electrical fields tend to be high. Need for research is markedly enriched in certain fields, such as artificial intelligence and robotics, as well as mechanics and electrics.

3.2.2 Analysis of trends by educational background

In terms of needs according to different educational backgrounds, there is a rising trend of higher educational needs for those with a bachelor’s degree in the information, mechanical, and electrical fields.

The higher the level of education, the higher the needs in education and research across diverse fields of specialization, especially for those with a doctoral degree, as many of them work in industry research.

In terms of the need for research in artificial intelligence, there is a rising need for people with a master’s or doctoral degree.

3.2.3 Analysis per field of specialty

Many graduates in the specialized fields of machinery, electricity, chemistry, biology, and food work in the mechanical, electrical, and chemical industries, and the tendency is to match the field of industry with the graduate field of specialization.

In the information industry, a high percentage of those working are humanities and sociology students, and not just specialists in the information field. The lack of IT engineers in the industry has often been pointed out, which suggests that a lot of talent in the information industry is recruited from humanities departments.

4. Materials

The above reports can be obtained in pdf format.