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

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...
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Autor*in:	Nie, Min [verfasserIn] Yang, Lei [verfasserIn] Sun, Jun [verfasserIn] Su, Han [verfasserIn] Xia, Hu [verfasserIn] Lian, Defu [verfasserIn] Yan, Kai [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	campus big data career identity career choice prediction self-knowledge

Übergeordnetes Werk:	Enthalten in: Frontiers of computer science in China - Beijing : Higher Education Press, 2007, 12(2018), 3 vom: 11. Mai, Seite 494-503
Übergeordnetes Werk:	volume:12 ; year:2018 ; number:3 ; day:11 ; month:05 ; pages:494-503

Links:	Volltext

DOI / URN:	10.1007/s11704-017-6498-6

Katalog-ID:	SPR021941130

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spelling	10.1007/s11704-017-6498-6 doi (DE-627)SPR021941130 (SPR)s11704-017-6498-6-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Nie, Min verfasserin aut Advanced forecasting of career choices for college students based on campus big data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. campus big data (dpeaa)DE-He213 career identity (dpeaa)DE-He213 career choice prediction (dpeaa)DE-He213 self-knowledge (dpeaa)DE-He213 Yang, Lei verfasserin aut Sun, Jun verfasserin aut Su, Han verfasserin aut Xia, Hu verfasserin aut Lian, Defu verfasserin aut Yan, Kai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 12(2018), 3 vom: 11. Mai, Seite 494-503 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:12 year:2018 number:3 day:11 month:05 pages:494-503 https://dx.doi.org/10.1007/s11704-017-6498-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 12 2018 3 11 05 494-503
allfields_unstemmed	10.1007/s11704-017-6498-6 doi (DE-627)SPR021941130 (SPR)s11704-017-6498-6-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Nie, Min verfasserin aut Advanced forecasting of career choices for college students based on campus big data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. campus big data (dpeaa)DE-He213 career identity (dpeaa)DE-He213 career choice prediction (dpeaa)DE-He213 self-knowledge (dpeaa)DE-He213 Yang, Lei verfasserin aut Sun, Jun verfasserin aut Su, Han verfasserin aut Xia, Hu verfasserin aut Lian, Defu verfasserin aut Yan, Kai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 12(2018), 3 vom: 11. Mai, Seite 494-503 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:12 year:2018 number:3 day:11 month:05 pages:494-503 https://dx.doi.org/10.1007/s11704-017-6498-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 12 2018 3 11 05 494-503
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allfieldsSound	10.1007/s11704-017-6498-6 doi (DE-627)SPR021941130 (SPR)s11704-017-6498-6-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Nie, Min verfasserin aut Advanced forecasting of career choices for college students based on campus big data 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. campus big data (dpeaa)DE-He213 career identity (dpeaa)DE-He213 career choice prediction (dpeaa)DE-He213 self-knowledge (dpeaa)DE-He213 Yang, Lei verfasserin aut Sun, Jun verfasserin aut Su, Han verfasserin aut Xia, Hu verfasserin aut Lian, Defu verfasserin aut Yan, Kai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 12(2018), 3 vom: 11. Mai, Seite 494-503 (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:12 year:2018 number:3 day:11 month:05 pages:494-503 https://dx.doi.org/10.1007/s11704-017-6498-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2005 54.00 ASE AR 12 2018 3 11 05 494-503
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source	Enthalten in Frontiers of computer science in China 12(2018), 3 vom: 11. Mai, Seite 494-503 volume:12 year:2018 number:3 day:11 month:05 pages:494-503
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author	Nie, Min
spellingShingle	Nie, Min ddc 004 bkl 54.00 misc campus big data misc career identity misc career choice prediction misc self-knowledge Advanced forecasting of career choices for college students based on campus big data
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topic_title	004 ASE 54.00 bkl Advanced forecasting of career choices for college students based on campus big data campus big data (dpeaa)DE-He213 career identity (dpeaa)DE-He213 career choice prediction (dpeaa)DE-He213 self-knowledge (dpeaa)DE-He213
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title	Advanced forecasting of career choices for college students based on campus big data
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title_full	Advanced forecasting of career choices for college students based on campus big data
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title_sort	advanced forecasting of career choices for college students based on campus big data
title_auth	Advanced forecasting of career choices for college students based on campus big data
abstract	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.
abstractGer	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.
abstract_unstemmed	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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title_short	Advanced forecasting of career choices for college students based on campus big data
url	https://dx.doi.org/10.1007/s11704-017-6498-6
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author2	Yang, Lei Sun, Jun Su, Han Xia, Hu Lian, Defu Yan, Kai
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