Abstract
Career indecision is a difficult obstacle in front of adolescents. Traditional vocational assessment research measure it by means of questionnaires and diagnose the potential sources of career indecision. Based on the diagnostic outcomes, career consolers develop the treatment plans tailor to students. However, because of personal motives and the architecture of the mind, it may be difficult for students to know themselves, so that the outcome of questionnaires can not fully reflect their inner states and statuses. Self-perception theory suggest students’ behavior could be used as clue for inference. Thus, we proposed a data-driven framework for forecast student career choice of graduation based on their behavior in and around the campus, playing an important role in supporting career counseling and career guiding. By evaluating on 10M behavior data of over four thousand students, we show the potential of this framework in these functionality.
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Nie, M., Yang, L., Ding, B., Xia, H., Xu, H., Lian, D. (2016). Forecasting Career Choice for College Students Based on Campus Big Data. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9931. Springer, Cham. https://doi.org/10.1007/978-3-319-45814-4_29
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DOI: https://doi.org/10.1007/978-3-319-45814-4_29
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