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Advanced forecasting of career choices for college students based on campus big data

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Abstract

Career indecision is a difficult obstacle confronting adolescents. Traditional vocational assessment research measures it by means of questionnaires and diagnoses the potential sources of career indecision. Based on the diagnostic outcomes, career counselors develop treatment plans tailored to students. However, because of personal motives and the architecture of the mind, it may be difficult for students to know themselves, and the outcome of questionnaires may not fully reflect their inner states and statuses. Self-perception theory suggests that students’ behavior could be used as a clue for inference. Thus, we proposed a data-driven framework for forecasting student career choice upon graduation based on their behavior in and around the campus, thereby playing an important role in supporting career counseling and career guidance. By evaluating on 10M behavior data of over four thousand students, we show the potential of this framework for this functionality.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61502077, 61631005) and the Fundamental Research Funds for the Central Universities (ZYGX2014Z012).

Author information

Authors and Affiliations

  1. Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Min Nie, Lei Yang, Jun Sun, Han Su, Hu Xia & Defu Lian

  2. Information Center, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Kai Yan

Authors
  1. Min Nie
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  2. Lei Yang
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  3. Jun Sun
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  4. Han Su
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  5. Hu Xia
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  6. Defu Lian
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  7. Kai Yan
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Corresponding author

Correspondence to Kai Yan.

Additional information

Min Nie is now pursuing the PhD degree at University of Electronic Science and Technology of China, China after receiving the BS degree there. His research interests include educational data mining, big data architecture, and distributed computing system.

Lei Yang received the BS and PhD degrees in computer science both from University of Science and Technology of China, China in 2009 and 2014 respectively. His research interests include big data pre-processing and data mining, particularly in educational data mining.

Jun Sun is an algorithm engineer at Xundao Technology Corporation, China. He received the bachelor and master degrees both from University of Electronic Science and Technology of China, China in 2013 and 2016, respectively. His research interests include big data analytics and visualization

Han Su received the PhD degree in computer science from the University of Queensland, Australia in 2015. She is currently an associate researcher at University of Electronic Science and Technology of China, China. Her research interests include big data querying and mining.

Hu Xia received the PhD degree in computer science from University of Electronic Science and Technology of China (UESTC), China. He is currently an associate researcher in UESTC. His research interests include educational big data and big data architecture.

Defu Lian received the BS and PhD degrees both from University of Science and Technology of China (UESTC), China in 2009 and 2014 respectively. He is now a lecturer in UESTC. His research interests include temporal-spatial data mining and recommendation.

Kai Yan is a PhD student and the associate director of Information Center at University of Electronic Science and Technology of China, China. Her research interest is platform virtualization.

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Nie, M., Yang, L., Sun, J. et al. Advanced forecasting of career choices for college students based on campus big data. Front. Comput. Sci. 12, 494–503 (2018). https://doi.org/10.1007/s11704-017-6498-6

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  • DOI: https://doi.org/10.1007/s11704-017-6498-6

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