Latent class analysis of student artefacts

P. K. Chan; C. H. Shek

doi:10.1145/3290511.3290521

Latent class analysis of student artefacts

P. K. Chan
, C. H. Shek

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

City University of Hong Kong has implemented Discovery-enriched Curriculum (DEC) since 2012. Teaching staff has submitted student artefacts as the explementary evidences for DEC implementation. In this report, the data in form of student artefacts were analyzed using latent class analysis (LCA) performed in R software to show whether there is any relationship between the type of student artefacts, academic background and sources of evidences. Results showed that these student artefacts could be categorized into 4 latent classes based on their type of expression and authenticity. Students from different academic background showed different probability to 4 latent classes. Furthermore, students tended to create evidences and achieve authentic tasks, related to artistic or entrepreneurial activities, from their personal work rather than course work. Results demonstrated that under CityU DEC framework, students were able to create knowledge and make discovery in form of the outcomes classified as the 4 latent classes. © 2018 Association for Computing Machinery

Original language	English
Title of host publication	ICETC '18: Proceedings of the 10th International Conference on Education Technology and Computers
Publisher	Association for Computing Machinery
Pages	302-307
ISBN (Print)	9781450365178
DOIs	https://doi.org/10.1145/3290511.3290521
Publication status	Published - Oct 2018
Event	10th International Conference on Education Technology and Computers (ICETC 2018) - Tokyo, Japan Duration: 26 Oct 2018 → 28 Oct 2018 https://www.icetc.org/2018.html

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	10th International Conference on Education Technology and Computers (ICETC 2018)
Place	Japan
City	Tokyo
Period	26/10/18 → 28/10/18
Internet address	https://www.icetc.org/2018.html

Research Keywords

Authentic tasks
Clustering
Latent class analysis
Student artefacts

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10.1145/3290511.3290521

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@inproceedings{03c285ea87274f67aeab7d9c5f775122,

title = "Latent class analysis of student artefacts",

abstract = "City University of Hong Kong has implemented Discovery-enriched Curriculum (DEC) since 2012. Teaching staff has submitted student artefacts as the explementary evidences for DEC implementation. In this report, the data in form of student artefacts were analyzed using latent class analysis (LCA) performed in R software to show whether there is any relationship between the type of student artefacts, academic background and sources of evidences. Results showed that these student artefacts could be categorized into 4 latent classes based on their type of expression and authenticity. Students from different academic background showed different probability to 4 latent classes. Furthermore, students tended to create evidences and achieve authentic tasks, related to artistic or entrepreneurial activities, from their personal work rather than course work. Results demonstrated that under CityU DEC framework, students were able to create knowledge and make discovery in form of the outcomes classified as the 4 latent classes. {\textcopyright} 2018 Association for Computing Machinery",

keywords = "Authentic tasks, Clustering, Latent class analysis, Student artefacts",

author = "Chan, \{P. K.\} and Shek, \{C. H.\}",

year = "2018",

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isbn = "9781450365178",

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pages = "302--307",

booktitle = "ICETC '18: Proceedings of the 10th International Conference on Education Technology and Computers",

address = "United States",

note = "10th International Conference on Education Technology and Computers (ICETC 2018) ; Conference date: 26-10-2018 Through 28-10-2018",

url = "https://www.icetc.org/2018.html",

}

Chan, PK & Shek, CH 2018, Latent class analysis of student artefacts. in ICETC '18: Proceedings of the 10th International Conference on Education Technology and Computers. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 302-307, 10th International Conference on Education Technology and Computers (ICETC 2018), Tokyo, Japan, 26/10/18. https://doi.org/10.1145/3290511.3290521

Latent class analysis of student artefacts. / Chan, P. K.; Shek, C. H.
ICETC '18: Proceedings of the 10th International Conference on Education Technology and Computers. Association for Computing Machinery, 2018. p. 302-307 (ACM International Conference Proceeding Series).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Latent class analysis of student artefacts

AU - Chan, P. K.

AU - Shek, C. H.

PY - 2018/10

Y1 - 2018/10

N2 - City University of Hong Kong has implemented Discovery-enriched Curriculum (DEC) since 2012. Teaching staff has submitted student artefacts as the explementary evidences for DEC implementation. In this report, the data in form of student artefacts were analyzed using latent class analysis (LCA) performed in R software to show whether there is any relationship between the type of student artefacts, academic background and sources of evidences. Results showed that these student artefacts could be categorized into 4 latent classes based on their type of expression and authenticity. Students from different academic background showed different probability to 4 latent classes. Furthermore, students tended to create evidences and achieve authentic tasks, related to artistic or entrepreneurial activities, from their personal work rather than course work. Results demonstrated that under CityU DEC framework, students were able to create knowledge and make discovery in form of the outcomes classified as the 4 latent classes. © 2018 Association for Computing Machinery

AB - City University of Hong Kong has implemented Discovery-enriched Curriculum (DEC) since 2012. Teaching staff has submitted student artefacts as the explementary evidences for DEC implementation. In this report, the data in form of student artefacts were analyzed using latent class analysis (LCA) performed in R software to show whether there is any relationship between the type of student artefacts, academic background and sources of evidences. Results showed that these student artefacts could be categorized into 4 latent classes based on their type of expression and authenticity. Students from different academic background showed different probability to 4 latent classes. Furthermore, students tended to create evidences and achieve authentic tasks, related to artistic or entrepreneurial activities, from their personal work rather than course work. Results demonstrated that under CityU DEC framework, students were able to create knowledge and make discovery in form of the outcomes classified as the 4 latent classes. © 2018 Association for Computing Machinery

KW - Authentic tasks

KW - Clustering

KW - Latent class analysis

KW - Student artefacts

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DO - 10.1145/3290511.3290521

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781450365178

T3 - ACM International Conference Proceeding Series

SP - 302

EP - 307

BT - ICETC '18: Proceedings of the 10th International Conference on Education Technology and Computers

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ER -

Latent class analysis of student artefacts

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