Kanazawa Institute of Technology (KIT) set out to transform its methods of guiding students from more of an art to a science and distill the pathways to success from the experiences of former students.
The ability to provide evidence-based self-growth guidance is helping the institute attract new students in a tightly competitive market.
Increased recruitmentof undergraduate/graduate students expected as a result of more sophisticated career placement capab
Improved alignmentexpected between the KIT curriculum and skills demand in the workplace
Strengthens collaborationand partnership between the institute’s academic staff and the business community
Business challenge story
In Japan, a long-term decline in birthrates along with an extended period of economic malaise has intensified competition among universities for a shrinking pool of new student enrollees. As a local university, KIT was especially conscious of the threat posed by demography-driven enrollment declines. To offset this threat, the institute resolved to focus its efforts on recruiting undergraduate/graduate students. To gain an edge in recruiting such students, KIT sought to differentiate itself from competing institutions in the area of career placement services.
Traditionally, career placement services have relied on close collaboration with guidance counselors to help students better understand themselves—particularly their strengths and preferences—to help them decide which career path would provide the best match with the skills demanded in the job market. The university’s vision was to create a more structured approach that would incorporate more evidence from more sources and use cognitive, self-learning algorithms to provide personalized recommendations for each undergraduate/graduate student.
As part of an initiative known as the Cognitive Campus Project, KIT—working with teams from IBM Software Group Lab Services and IBM Cognitive Business Solutions—implemented an analytics-based advisory service focused on job placement and campus life. Running on a hosted cloud platform, the solution’s fundamental cognitive function is multi-parametric matching performed in two stages.
First, the solution creates an extremely detailed, evidence-based profile of each student’s educational identity using a large base of structured and unstructured student data extracted from the institute’s internal systems.
With this foundation established, the solution’s second function is to analyze the data to learn the linkages between educational parameters on one side and known career placement outcomes on the other.
The practical value of the solution is the ability to sort through these logical connections to offer each student customized advice on which steps to take to achieve a particular career outcome. Suppose, for instance, a student identifies his career placement outcome as living in Silicon Valley and working for a trade firm. The solution’s algorithms—automatically factoring in the student’s background and larger historical patterns—can estimate the value of taking additional English courses, along with recommending additional measures such as taking courses in specific technology subject matter areas.
In addition to suggesting the best path to a particular career outcome, the solution has the capability to recommend particular career options that the student may not have been aware of or considered. Using the same basic algorithmic logic, this capability finds the closest matches between the background parameters of the particular undergraduate/graduate student and those of undergraduate/graduate students who have moved on to careers. The solution would present this information as a case study, saying, in effect, “A student with your background followed this particular course and is now working in this particular field.”
KIT expects to increase the number of undergraduate/graduate student applicants drawn by its more sophisticated career placement capabilities. In parallel with this, one organic cultural change expected to unfold over time is an improved alignment between the institute’s curriculum and the demand for skills and academic backgrounds in the workplace. The institute believes that as it gets better at identifying the patterns of success, academics, counselors and curriculum planners will be in a position to make more informed decisions and will therefore be more likely to take proactive steps to keep the curriculum in line with market needs. The same dynamic is also expected to promote closer collaboration and partnership between the institute’s academic staff and the business community.
The KIT solution is game-changing because it uses machine learning technology against large amounts of unstructured data to determine which combination of skills, educational background and activities can maximize a student’s likelihood of succeeding along a particular career path. This ability to provide evidence-based recommendations is likely to improve already good career placement rates for the institute, strengthening its competitive position.
Traditionally, career placement efforts required academic counselors to offer suggestions to students—which skills to improve, which courses to take and which activities to involve themselves in—from their own past experiences. This less-than-objective approach relied on limited inputs and subjective judgment. The new solution takes an entirely objective, fresh and bottom-up look at which factors are most important to success, thereby increasing the likelihood of success and eliminating potential judgment bias in career-related recommendations.
The KIT solution relies on data drawn from its internal systems. Unstructured sources include interview transcripts, class reports, extracurricular activities and course syllabi. Structured data includes course histories, academic records and other elements from the institute’s internal student databases.
About Kanazawa Institute of Technology
Based in Kanazawa, Japan, Kanazawa Institute of Technology (KIT) is a technically focused university with four areas of study: engineering; informatics and human communication; environmental engineering and architecture; and bioscience and chemistry. Initially established in 1957 for the purpose of training radio engineers, KIT is now known for an education culture that places a high degree of importance on student initiative.
- Educ: Open and Aligned Learning
- Watson Implementation Services