Scenario-Based Career Path Decision Support Services in Human Capital Development

Scenario-Based Career Path Decision Support Services in Human Capital Development

Tokuro Matsuo, Yoshihito Saito, Takanori Terashima, Takayuki Fujimoto
DOI: 10.4018/jhcitp.2012010102
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This paper proposes a new career support system for students’ decision-making using past student information in a university. Past students information contains a lot of useful information such as trend of taken classes, getting jobs, and their correlations. The authors explain a method to clarify the correlation of lectures and jobs. The system provides career services to students. The system shows pattern and scenario to take lecture based on student’s goal and job family in which they want to get. And also, the system realizes to support the student by providing appropriate candidates of job families from students’ career, pattern, and order of taking classes.
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Universities and colleges have huge amount of information and such information can be used to enhance rationality of educational activities (Cox & Emmott, 2007; Hsu, Hamilton, & Wang, 2010; Matsuo & Fujimoto, 2010). Campus information includes faculty information, lecture information, student information, career information, facility and equipment information, and several others. In this paper, we focus on a decision support system for students to choose lecture and job based on their profile and history. Student information is one of the most frequently updated data in campus information because it should be updated every semester. And also, Students who newly entered university and students graduate the university after earning required credits. These individual history data are preserved in student section and career section in the university. Thus, university preserves a lot of cumulative students’ information for years and years.

Student information is normally managed in a student section and is referred by students, faculties and staffs (Glatthorn, 1994; Negnevitsky, 1998). Since students belong the university over a protracted period of time, their information are preserved in a lot of sections. For example, student individual information is preserved in student section and student credit information is preserved in an education section. However, students’ information is not always reused to make effective instructions and tutoring. Universities cumulatively preserve multiple information of former student (alumnae and alumni). The information includes student career history of taking classes, place of employment of job family after their graduation. From a point of collective intelligence research view, collective information provides averagely rational activities of the students (Pentland, 2006; Jung & Nguyen, 2008). If these former students’ information can be reused and analyzed, university can help current students to learn and understand something (Couros, 2009; Miller, 1976). The information can be used in decision making for students regarding getting jobs and finding appropriate classes for their purposes and intentions.

In this paper, we propose a new career support method by collected information. Generally, mentoring programs are provided to enhance student’s understanding and keep his/her motivations in universities (Casado-Lumbreras, 2009; Chao, 1992). Also, there are some researches to monitor students learning in professional education viewpoints (Garcia-Crespo, 2009a, 2009b; Martin, 1998; Soto-Acosta, 2010). On the other hands, in this paper, apart from subject learning, we focus on career understanding for students. The system provides useful information for students about pattern and scenario to take lecture based on student’s goal. And also, job family in which he/she wants to be based on computational analysis are retrieved. Further, our proposed method realizes to support the student providing appropriate candidates of job families from students’ career, and history and order of taking classes.

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