Humanized Computing for Mass Customization Application in Curriculum Management

Universities may set similar courses due to disciplinary crossing. Facing the problem that undergraduates have numerous tasks and limited time, we designed a mass customization model which will automatically provide every student with a suitable curriculum to maximize their degree of satisfaction when the student enters a set of courses. Our calculating model of curriculum satisfaction is based on the assumptions that curriculum satisfaction is proportional to its similarity and that curriculum satisfaction is inversely proportional to credits. With regard to a student who chooses n courses, his satisfaction model is total degree of satisfaction divided by total credits. We manually screened out 84 pairs of courses about science and engineering, social science and humanities, and made use of their Chinese names and Chinese course description on the site of Office of Educational Administration, and segmented words based on statistical principles and calculated the course similarity by using vector space. In addition, we make supplement to curriculum similarity by the use of artificially-designed questionnaires.