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A major choice in high school or undergraduate stage is an important decision in the human life. To discover students’ suitable majors as early as possible can help them to choose the appropriate vocational learning direction and to build the skills and the abilities for the prospective major. The main issue of difficulty making the decisions of major choices for the students is a lack of knowledge and information about majors and occupations. A mass of students has decided their majors out of proper and professional advice from school services. On the other hand, the major choices of students are influenced by a society, an environment, and their family mostly. Those difficulties are potentially the causes of a mismatch between academic achievements, personality, interest, and abilities of students. Hence, it is necessary to build an Occupation Recommendation System (ORS) to students with a capacity to meet all the needs where it provides the orientation and the counsel to students in selecting the major that fits with their interests and skills.
In the first study, ORS driven by model-based recommendation technique using the regression approach on the item-based collaborative filtering for giving suitable occupation recommendation based on the personality, learning style, and vocational interest of students were implemented. Furthermore, the system provides the two Top-N occupation lists; one is based on the regression model using personality and learning style while the other is based on the vocational interests. Mongolian high school’s 190 students participated the experiment. The result of the regression analysis revealed that assessment of the all domains of interests, personality and learning style has several advantages for assisting the students exploring a vocational major. Moreover, the influences of the major choice of the students were investigated.
In the second study, hybrid 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 from the questionnaire using Holland code, and their behaviors. The student profile contains two types of data, namely, background and interest/hobby retrieved from Facebook. In the experiment, the students are from four countries. 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.
Finally, the third study employed a flipped classroom model on google classroom using the Open Educational Resources (OER). The flipped learning on career counseling course is the first time conducting in Mongolia. An experiment has conducted that students discover and explore the occupations with ORS and OCCREC as well as the guidance and counseling are being provided. | en_US |