A talent assessment model based on learning behaviors and patterns

Haoran XIE; Yi CAI; Tak-Lam WONG; Di ZOU; Fu Lee WANG

doi:10.1109/ISET.2019.00011

A talent assessment model based on learning behaviors and patterns

Haoran XIE, Yi CAI, Tak-Lam WONG, Di ZOU, Fu Lee WANG

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

Talent assessment is an important topic in various areas like enterprise management, education, and psychology. However, it is also a challenging topic as the conventional assessment methods and models are unsuitable for talent assessment due to the following two aspects: (i) domain-dependent. The assessment of talent is highly depended on a specific domain which requires a large volume of domain knowledge in the assessment model; and (ii) behavior-based (or pattern-based). The characteristics of talents are reflected by a wide range of factors like their behaviors (patterns), emotions, self-identities, and metacognition. In this paper, we propose a talent assessment model based on online learning behaviors and patterns by using fuzzy models. Specifically, we attempt to develop a talent assessment model by identifying their learning data as we believe that the learning behaviors in the online learning platforms like massive open online courses (MOOCs) can reflect some characteristics of talents. Furthermore, we discuss what are the data sources, the learning behaviors and the potential computational methods in this assessment model in details. In addition, the potential limitations and possible improvement plans are introduced.

Original language	English
Title of host publication	Proceedings : 2019 International Symposium on Educational Technology, ISET 2019
Editors	Fu Lee WANG, Oliver AU, Blanka KLIMOVA, Josef HYNEK, Petra HYNEK
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3-6
Number of pages	4
ISBN (Electronic)	9781728133874
ISBN (Print)	9781728133898
DOIs	https://doi.org/10.1109/ISET.2019.00011
Publication status	Published - Jul 2019
Externally published	Yes
Event	2019 International Symposium on Educational Technology - Hradec Kralove, Czech Republic Duration: 2 Jul 2019 → 4 Jul 2019

Conference

Conference	2019 International Symposium on Educational Technology
Abbreviated title	ISET 2019
Country/Territory	Czech Republic
City	Hradec Kralove
Period	2/07/19 → 4/07/19

Bibliographical note

The research in this paper was supported by the Innovation and Technology Fund (Project No. GHP/022/17GD) from the Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region, and the Science and Technology Planning Project of Guangdong Province (No.2016A030310423, 2017B050506004).

Keywords

Fuzzy model
Learning behavior
Learning pattern
Talent assessment

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10.1109/ISET.2019.00011

Cite this

XIE, H., CAI, Y., WONG, T.-L., ZOU, D., & WANG, F. L. (2019). A talent assessment model based on learning behaviors and patterns. In F. L. WANG, O. AU, B. KLIMOVA, J. HYNEK, & P. HYNEK (Eds.), Proceedings : 2019 International Symposium on Educational Technology, ISET 2019 (pp. 3-6). Article 8782210 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISET.2019.00011

@inproceedings{451c882651354f88a557949ff3ec3153,

title = "A talent assessment model based on learning behaviors and patterns",

abstract = "Talent assessment is an important topic in various areas like enterprise management, education, and psychology. However, it is also a challenging topic as the conventional assessment methods and models are unsuitable for talent assessment due to the following two aspects: (i) domain-dependent. The assessment of talent is highly depended on a specific domain which requires a large volume of domain knowledge in the assessment model; and (ii) behavior-based (or pattern-based). The characteristics of talents are reflected by a wide range of factors like their behaviors (patterns), emotions, self-identities, and metacognition. In this paper, we propose a talent assessment model based on online learning behaviors and patterns by using fuzzy models. Specifically, we attempt to develop a talent assessment model by identifying their learning data as we believe that the learning behaviors in the online learning platforms like massive open online courses (MOOCs) can reflect some characteristics of talents. Furthermore, we discuss what are the data sources, the learning behaviors and the potential computational methods in this assessment model in details. In addition, the potential limitations and possible improvement plans are introduced.",

keywords = "Fuzzy model, Learning behavior, Learning pattern, Talent assessment",

author = "Haoran XIE and Yi CAI and Tak-Lam WONG and Di ZOU and WANG, {Fu Lee}",

note = "The research in this paper was supported by the Innovation and Technology Fund (Project No. GHP/022/17GD) from the Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region, and the Science and Technology Planning Project of Guangdong Province (No.2016A030310423, 2017B050506004). ; 2019 International Symposium on Educational Technology, ISET 2019 ; Conference date: 02-07-2019 Through 04-07-2019",

year = "2019",

month = jul,

doi = "10.1109/ISET.2019.00011",

language = "English",

isbn = "9781728133898",

pages = "3--6",

editor = "WANG, {Fu Lee} and Oliver AU and Blanka KLIMOVA and Josef HYNEK and Petra HYNEK",

booktitle = "Proceedings : 2019 International Symposium on Educational Technology, ISET 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

XIE, H, CAI, Y, WONG, T-L, ZOU, D & WANG, FL 2019, A talent assessment model based on learning behaviors and patterns. in FL WANG, O AU, B KLIMOVA, J HYNEK & P HYNEK (eds), Proceedings : 2019 International Symposium on Educational Technology, ISET 2019., 8782210, Institute of Electrical and Electronics Engineers Inc., pp. 3-6, 2019 International Symposium on Educational Technology, Hradec Kralove, Czech Republic, 2/07/19. https://doi.org/10.1109/ISET.2019.00011

A talent assessment model based on learning behaviors and patterns. / XIE, Haoran; CAI, Yi; WONG, Tak-Lam et al.
Proceedings : 2019 International Symposium on Educational Technology, ISET 2019. ed. / Fu Lee WANG; Oliver AU; Blanka KLIMOVA; Josef HYNEK; Petra HYNEK. Institute of Electrical and Electronics Engineers Inc., 2019. p. 3-6 8782210.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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AU - ZOU, Di

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N1 - The research in this paper was supported by the Innovation and Technology Fund (Project No. GHP/022/17GD) from the Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region, and the Science and Technology Planning Project of Guangdong Province (No.2016A030310423, 2017B050506004).

PY - 2019/7

Y1 - 2019/7

N2 - Talent assessment is an important topic in various areas like enterprise management, education, and psychology. However, it is also a challenging topic as the conventional assessment methods and models are unsuitable for talent assessment due to the following two aspects: (i) domain-dependent. The assessment of talent is highly depended on a specific domain which requires a large volume of domain knowledge in the assessment model; and (ii) behavior-based (or pattern-based). The characteristics of talents are reflected by a wide range of factors like their behaviors (patterns), emotions, self-identities, and metacognition. In this paper, we propose a talent assessment model based on online learning behaviors and patterns by using fuzzy models. Specifically, we attempt to develop a talent assessment model by identifying their learning data as we believe that the learning behaviors in the online learning platforms like massive open online courses (MOOCs) can reflect some characteristics of talents. Furthermore, we discuss what are the data sources, the learning behaviors and the potential computational methods in this assessment model in details. In addition, the potential limitations and possible improvement plans are introduced.

AB - Talent assessment is an important topic in various areas like enterprise management, education, and psychology. However, it is also a challenging topic as the conventional assessment methods and models are unsuitable for talent assessment due to the following two aspects: (i) domain-dependent. The assessment of talent is highly depended on a specific domain which requires a large volume of domain knowledge in the assessment model; and (ii) behavior-based (or pattern-based). The characteristics of talents are reflected by a wide range of factors like their behaviors (patterns), emotions, self-identities, and metacognition. In this paper, we propose a talent assessment model based on online learning behaviors and patterns by using fuzzy models. Specifically, we attempt to develop a talent assessment model by identifying their learning data as we believe that the learning behaviors in the online learning platforms like massive open online courses (MOOCs) can reflect some characteristics of talents. Furthermore, we discuss what are the data sources, the learning behaviors and the potential computational methods in this assessment model in details. In addition, the potential limitations and possible improvement plans are introduced.

KW - Fuzzy model

KW - Learning behavior

KW - Learning pattern

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DO - 10.1109/ISET.2019.00011

M3 - Conference paper (refereed)

SN - 9781728133898

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EP - 6

BT - Proceedings : 2019 International Symposium on Educational Technology, ISET 2019

A2 - WANG, Fu Lee

A2 - AU, Oliver

A2 - KLIMOVA, Blanka

A2 - HYNEK, Josef

A2 - HYNEK, Petra

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 International Symposium on Educational Technology

Y2 - 2 July 2019 through 4 July 2019

ER -

A talent assessment model based on learning behaviors and patterns

Abstract

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Bibliographical note

Keywords

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