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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Front. Comput. Sci.    2018, Vol. 12 Issue (3) : 494-503    https://doi.org/10.1007/s11704-017-6498-6
RESEARCH ARTICLE
Advanced forecasting of career choices for college students based on campus big data
Min NIE1, Lei YANG1, Jun SUN1, Han SU1, Hu XIA1, Defu LIAN1, Kai YAN2()
1. Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China
2. Information Center, University of Electronic Science and Technology of China, Chengdu 611731, China
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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. Selfperception 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.

Keywords campus big data      career identity      career choice prediction      self-knowledge     
Corresponding Author(s): Kai YAN   
Just Accepted Date: 28 March 2017   Online First Date: 08 December 2017    Issue Date: 02 May 2018
 Cite this article:   
Min NIE,Lei YANG,Jun SUN, et al. Advanced forecasting of career choices for college students based on campus big data[J]. Front. Comput. Sci., 2018, 12(3): 494-503.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-017-6498-6
https://academic.hep.com.cn/fcs/EN/Y2018/V12/I3/494
1 Erikson E H. Identity: Youth and Crisis. No. 7. New York: W. W. Norton & Company, 1994
2 Marcia J E, Waterman A S, Matteson D R, Archer S L, Orlofsky J L. Ego Identity: A Handbook for Psychosocial Research. New York: Springer Science & Business Media, 2012
3 Lopez F G. A paradoxical approach to vocational indecision. The Personnel and Guidance Journal, 1983, 61(7): 410–412
https://doi.org/10.1111/j.2164-4918.1983.tb00056.x
4 Savickas Mark L. Identity in vocational development. Journal of Vocational Behavior, 1985, 27(3): 329–337
https://doi.org/10.1016/0001-8791(85)90040-5
5 Gati I, Krausz M, Osipow S H. A taxonomy of difficulties in career decision making. Journal of Counseling Psychology, 1996, 43(4): 510
https://doi.org/10.1037/0022-0167.43.4.510
6 Savickas M L. The transition from school to work: a developmental perspective. The Career Development Quarterly, 1999, 47(4): 326–336
https://doi.org/10.1002/j.2161-0045.1999.tb00741.x
7 Wilson T D, Dunn E W. Self-knowledge: its limits, value, and potential for improvement. Psychology, 2004, 55
https://doi.org/10.1146/annurev.psych.55.090902.141954
8 Bem D J. Self-perception theory. Advances in Experimental Social Psychology, 1972, 6: 1–62
https://doi.org/10.1016/S0065-2601(08)60024-6
9 Albion M J, Fogarty G J. Factors influencing career decision making in adolescents and adults. Journal of Career Assessment, 2002, 10(1): 91–126
https://doi.org/10.1177/1069072702010001006
10 Dudley N M, Orvis K A, Lebiecki J E, Cortina J M. A meta-analytic investigation of conscientiousness in the prediction of job performance: examining the intercorrelations and the incremental validity of narrow traits. Journal of Applied Psychology, 2006, 91(1): 40
https://doi.org/10.1037/0021-9010.91.1.40
11 Thompson M N, Subich L M. The relation of social status to the career decision-making process. Journal of Vocational Behavior, 2006, 69(2): 289–301
https://doi.org/10.1016/j.jvb.2006.04.008
12 Festinger L. A theory of social comparison processes. Human Relations, 1954, 7(2): 117–140
https://doi.org/10.1177/001872675400700202
13 Reichling T, Wulf V. Expert recommender systems in practice: evaluating semi-automatic profile generation. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2009, 59–68
https://doi.org/10.1145/1518701.1518712
14 Balog K, de Rijke M. Finding experts and their eetails in e-mail corpora. In: Proceedings of the 15th ACM International Conference on World Wide Web. 2006, 1035–1036
https://doi.org/10.1145/1135777.1136002
15 Guy I, Avraham U, Carmel D, Ur S, Jacovi M, Ronen I. Mining expertise and interests from social media. In: Proceedings of the 22nd ACM International Conference on World Wide Web. 2013, 515–526
https://doi.org/10.1145/2488388.2488434
16 Varshney K R, Chenthamarakshan V, Fancher S W, Wang J, Fang D, Mojsilović A. Predicting employee expertise for talent management in the enterprise. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2014, 1729–1738
https://doi.org/10.1145/2623330.2623337
17 Varshney K R, Wang J, Mojsilovic A, Fang D P, Bauer J H. Predicting and recommending skills in the social enterprise. In: Proceedings of AAAI ICWSM Workshop on Social Computing for Workforce. 2013, 20–23
18 Baruch Y. Transforming careers: from linear to multidirectional career paths: organizational and individual perspectives. Career Development International, 2004, 9(1): 58–73
https://doi.org/10.1108/13620430410518147
19 Wang J, Zhang Y, Posse C, Bhasin A. Is it time for a career switch? In: Proceedings of the 22nd ACM International Conference on World Wide Web. 2013, 1377–1388
https://doi.org/10.1145/2488388.2488509
20 Deville P, Wang D S, Sinatra R, Song C M, Blondel V D, Barabási A L. Career on the move: geography, stratification, and scientific impact. Scientific Reports. 2014
21 Xu H, Yu Z W, Xiong H, Guo B, Zhu H S. Learning career mobility and human activity patterns for job change analysis. In: Proceedings of IEEE International Conference on Data Mining. 2015, 1057–1062
https://doi.org/10.1109/ICDM.2015.122
22 Hadiji F, Mladenov M, Bauckhage C, Kersting K. Computer science on the move: inferring migration regularities from the web via compressed label propagation. In: Proceedings of IJCAI. 2015, 171–177
23 Wang J G, Huang J Z, Guo J F, Lan Y Y. Recommending high-utility search engine queries via a query recommending model. Neurocomputing, 2015, 167: 195–208
https://doi.org/10.1016/j.neucom.2015.04.076
24 Paparrizos I, Cambazoglu B B, Gionis A. Machine learned job recommendation. In: Proceedings of the 5th ACM Conference on Recommender Systems. 2011, 325–328
https://doi.org/10.1145/2043932.2043994
25 Li J Q, Liu C C, Liu B, Mao R, Wang Y C, Chen S, Yang J J, Pan H, Wang Q. Diversity-aware retrieval of medical records. Computers in Industry, 2015, 69: 81–91
https://doi.org/10.1016/j.compind.2014.09.004
26 Hong W X, Li L, Li T, Pan W F. iHR: an online recruiting system for Xiamen talent service center. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2013, 1177–1185
https://doi.org/10.1145/2487575.2488199
27 Mao R, Xu H L, Wu W B, Li J Q, Li Y, Lu M H. Overcoming the challenge of variety: big data abstraction, the next evolution of data management for AAL communication systems. IEEE Communications Magazine, 2015, 53(1): 42–47
https://doi.org/10.1109/MCOM.2015.7010514
28 Xu Y, Li Z, Gupta A, Bugdayci A, Bhasin A. Modeling professional similarity by mining professional career trajectories. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2014, 1945–1954
https://doi.org/10.1145/2623330.2623368
29 Mao R, Zhang P H, Li X L, Liu X, Lu M H. Pivot selection for metricspace indexing. International Journal of Machine Learning and Cybernetics, 2016, 7(2): 311–323
https://doi.org/10.1007/s13042-016-0504-4
30 Parsons F. Choosing a Vocation. Boston, MA: Houghton Mifflin, 1909
31 Holland J L. Making vocational choices: a theory of vocational personalities and work environments. Psychological Assessment Resources, 1997
32 Super D E. A life-span, life-space approach to career development. Journal of Vocational Behavior, 1980, 16(3): 282–298
https://doi.org/10.1016/0001-8791(80)90056-1
33 Schein E H. Career Anchors: Discovering Your Real Values. San Francisco: Jossey Bass Pfeiffer, 1990
34 Krumboltz J D, Mitchell A M, Jones G B. A social learning theory of career selection. The Counseling Psychologist, 1976, 6(1): 71–81
https://doi.org/10.1177/001100007600600117
35 Wu R Z, Liu Q, Liu Y P, Chen E H, Su Y, Chen Z G, Hu G P. Cognitive modelling for predicting examinee performance. In: Proceedings of International Conference on Artificial Intelligence. 2015: 1017–1024
36 Guan C, Lu X J, Li X L, Chen E H, Zhou W J, Xiong H. Discovery of college students in financial hardship. In: Proceedings of IEEE International Conference on Data Mining. 2015, 141–150
https://doi.org/10.1109/ICDM.2015.49
37 Desmarais M C. Mapping question items to skills with nonnegative matrix factorization. ACM SIGKDD Explorations Newsletter, 2012, 13(2): 30–36
https://doi.org/10.1145/2207243.2207248
38 Nie M, Yang L, Ding B, Xia H, Xu H C, Lian D F. Forecasting career choice for college students based on campus big data. In: Proceeding of Asia-Pacific Web Conference. 2016, 359–370
https://doi.org/10.1007/978-3-319-45814-4_29
39 Lian D F, Liu Q, Zhu W Y, Xie X, Xiong H. Mutual reinforcement of academic performance prediction and library book recommendation. In Proceedings of the 16th IEEE International Conference on Data Mining. 2016, 1023–1028
https://doi.org/10.1109/ICDM.2016.0130
40 Lian D F, Ge Y, Zhang F Z, Yuan N J, Xie X, Zhou T, Rui Y. Contentaware collaborative filtering for location recommendation based on human mobility data. In: Proceedings of IEEE International Conference on Data Mining. 2015, 261–270
41 Chen Y P, Yang J Y, Liou S N, Lee G Y, Wang J S. Online classifier construction algorithm for human activity detection using a tri-axial accelerometer. Applied Mathematics and Computation, 2008, 205(2): 849–860
https://doi.org/10.1016/j.amc.2008.05.099
42 Yang Y M. An evaluation of statistical approaches to text categorization. Information Retrieval, 1999, 1(1–2): 69–90
https://doi.org/10.1023/A:1009982220290
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