Hybrid occupation recommendation for adolescents on interest, profile, and behavior

Abstract

Young people in high school or college make critical decisions regarding what major to study and which career path to pursue. But, many students enter post-secondary education without a clear idea of their major and future career plans. Discovering students’ suitable occupations as early as possible can help them to choose an appropriate vocational learning direction and to build the skills and the abilities for the prospective occupation. For those reasons, students need an automatic counseling system. In order to do this, recommendation methods were employed; it aims to counsel suitable occupation for students, to discover their occupational interests and to guide them to improve their skills. We implemented a hybrid recommendation system called occupation recommendation (OCCREC) that integrates content-based and collaborative filtering methods. We involved three sets of information including student’s profiles, vocational interests, and their behaviors. The student profile contains two types of data, namely, background and interest/hobby retrieved from Facebook. In the experiment, the students from four countries consisted of Mongolia, Sri Lanka, Taiwan, and Thailand used the OCCREC. And, five occupations were shown to the students by using five similarity measures which are Euclidean, Intersection, Cosine, Jaccard, and Pearson. Finally, OCCREC allows students to rate the results accordingly based on user’s satisfied scores and to share their experiences on Facebook.

Introduction

Students make initial but critical decisions regarding what to study and which career path to pursue (Ferry, 2006). A mass of students has decided their majors/occupations out of proper and professional advice from school services. Mismatch of the major choice and lack of information through professional study is one of the reasons for them to change major. Such changes are wasteful in time and resources, and it is the cause of financial and emotional stresses of students. An approximated twenty to fifty percent of students enter college as undecided major; and an approximated seventy-five percent of students change their major at least once before graduation (Gordon, 2007). On the other hand, the students’ major choices are influenced by the society, the education environment, and mostly their families. Those pitfalls are potentially the causes of a mismatch major between academic achievements, personality, interest and abilities of students. It would be useful to understand how students’ choice of the academic majors depends on personal characteristics, competencies, and vocational interests. Most of the students do not possess adequate information about meaning of occupations/majors, what careers can be reached by which majors, and what kind of skills and abilities are needed for a particular occupation/major. Especially, even some parents are unfamiliar with the contemporary occupations/majors.

The main goal of this paper is to construct an occupation recommendation system by using data mining method. In the experiment, we focus on testing Mongolian, Sri Lankan, Taiwanese and Thai students. The system can provide details of occupations and can assist the students for major choices, as well as the careers to pursue. Furthermore, the research goal incorporates a set of results, which are recommended using similarity measurements and recommendation techniques. We called this a hybridization system. These methods serve as a base for recommending occupations that meet interests and competencies of students.

The rest of the paper is organized as follows. Section 2 presents related works about Content-based, Collaborative filtering, and hybrid techniques. In Section 3, we introduce the proposed system its methods and functions. Section 4 provides experimental results. Finally, Section 5 contains the conclusion and future work.