Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy

Owen H.T. Lu; Anna Y.Q. Huang; Che Yu Kuo; Irene Y.L. Chen; Stephen J.H. Yang

Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy

Owen H.T. Lu, Anna Y.Q. Huang, Che Yu Kuo, Irene Y.L. Chen, Stephen J.H. Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

SQ3R (survey, question, read, recite, and review) is an efficient reading method that has confirmed the benefits of learning performance in numerous studies. To demonstrate that the e-book reading environment can also obtain the benefits of SQ3R, we conducted a course with 60 students, classify students into two groups based on the SQ3R ability. The results show that in the context of e-book reading, students' behavior: (1) create a memo and modify it regarding the reviewing content (CMeP) and (2) create a memo and modify it at the next login (CMeO) is related to recite and review steps in SQ3R. Furthermore, the above two e-book reading behaviors are positively related to students' learning performance and learning engagement.

Original language	English
Title of host publication	ICCE 2020 - 28th International Conference on Computers in Education, Proceedings
Editors	Hyo-Jeong So, Ma. Mercedes Rodrigo, Jon Mason, Antonija Mitrovic, Daniel Bodemer, Weichao Chen, Zhi-Hong Chen, Brendan Flanagan, Marc Jansen, Roger Nkambou, Longkai Wu
Publisher	Asia-Pacific Society for Computers in Education
Pages	307-311
Number of pages	5
ISBN (Electronic)	9789869721455
State	Published - 23 Nov 2020
Event	28th International Conference on Computers in Education, ICCE 2020 - Virtual, Online Duration: 23 Nov 2020 → 27 Nov 2020

Publication series

Name	ICCE 2020 - 28th International Conference on Computers in Education, Proceedings
Volume	1

Conference

Conference	28th International Conference on Computers in Education, ICCE 2020
City	Virtual, Online
Period	23/11/20 → 27/11/20

Keywords

Computer-assisted learning
Reading strategy
SQ3R

The Research of Applying Educational Big Data and Learning Analytics to Improve Self-Regulated Learning in Programming(1/3)
Yang, S. J. H. (PI)
1/08/20 → 31/07/21
Project: Research
An Empirical Study on the Cultivation and Learning Analytics of Computational Thinking Skills(2/3)
Yang, S. J. H. (PI)
1/08/20 → 31/07/21
Project: Research
The Research of Applying Big Data to Improving Moocs Learning Analytics：An Empirical Study of College Calculus(3/3)
Yang, S. J. H. (PI)
1/08/19 → 31/07/20
Project: Research

Cite this

Lu, O. H. T., Huang, A. Y. Q., Kuo, C. Y., Chen, I. Y. L., & Yang, S. J. H. (2020). Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy. In H.-J. So, M. M. Rodrigo, J. Mason, A. Mitrovic, D. Bodemer, W. Chen, Z.-H. Chen, B. Flanagan, M. Jansen, R. Nkambou, & L. Wu (Eds.), ICCE 2020 - 28th International Conference on Computers in Education, Proceedings (pp. 307-311). (ICCE 2020 - 28th International Conference on Computers in Education, Proceedings; Vol. 1). Asia-Pacific Society for Computers in Education.

Lu, Owen H.T. ; Huang, Anna Y.Q. ; Kuo, Che Yu et al. / Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy. ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. editor / Hyo-Jeong So ; Ma. Mercedes Rodrigo ; Jon Mason ; Antonija Mitrovic ; Daniel Bodemer ; Weichao Chen ; Zhi-Hong Chen ; Brendan Flanagan ; Marc Jansen ; Roger Nkambou ; Longkai Wu. Asia-Pacific Society for Computers in Education, 2020. pp. 307-311 (ICCE 2020 - 28th International Conference on Computers in Education, Proceedings).

@inproceedings{e9f2f7d76663458b9d093cc5c3d3d6fb,

title = "Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy",

abstract = "SQ3R (survey, question, read, recite, and review) is an efficient reading method that has confirmed the benefits of learning performance in numerous studies. To demonstrate that the e-book reading environment can also obtain the benefits of SQ3R, we conducted a course with 60 students, classify students into two groups based on the SQ3R ability. The results show that in the context of e-book reading, students' behavior: (1) create a memo and modify it regarding the reviewing content (CMeP) and (2) create a memo and modify it at the next login (CMeO) is related to recite and review steps in SQ3R. Furthermore, the above two e-book reading behaviors are positively related to students' learning performance and learning engagement.",

keywords = "Computer-assisted learning, Reading strategy, SQ3R",

author = "Lu, {Owen H.T.} and Huang, {Anna Y.Q.} and Kuo, {Che Yu} and Chen, {Irene Y.L.} and Yang, {Stephen J.H.}",

note = "Publisher Copyright: {\textcopyright} ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. All rights reserved.; 28th International Conference on Computers in Education, ICCE 2020 ; Conference date: 23-11-2020 Through 27-11-2020",

year = "2020",

month = nov,

day = "23",

language = "???core.languages.en_GB???",

series = "ICCE 2020 - 28th International Conference on Computers in Education, Proceedings",

publisher = "Asia-Pacific Society for Computers in Education",

pages = "307--311",

editor = "Hyo-Jeong So and Rodrigo, {Ma. Mercedes} and Jon Mason and Antonija Mitrovic and Daniel Bodemer and Weichao Chen and Zhi-Hong Chen and Brendan Flanagan and Marc Jansen and Roger Nkambou and Longkai Wu",

booktitle = "ICCE 2020 - 28th International Conference on Computers in Education, Proceedings",

}

Lu, OHT, Huang, AYQ, Kuo, CY, Chen, IYL & Yang, SJH 2020, Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy. in H-J So, MM Rodrigo, J Mason, A Mitrovic, D Bodemer, W Chen, Z-H Chen, B Flanagan, M Jansen, R Nkambou & L Wu (eds), ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. ICCE 2020 - 28th International Conference on Computers in Education, Proceedings, vol. 1, Asia-Pacific Society for Computers in Education, pp. 307-311, 28th International Conference on Computers in Education, ICCE 2020, Virtual, Online, 23/11/20.

Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy. / Lu, Owen H.T.; Huang, Anna Y.Q.; Kuo, Che Yu et al.
ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. ed. / Hyo-Jeong So; Ma. Mercedes Rodrigo; Jon Mason; Antonija Mitrovic; Daniel Bodemer; Weichao Chen; Zhi-Hong Chen; Brendan Flanagan; Marc Jansen; Roger Nkambou; Longkai Wu. Asia-Pacific Society for Computers in Education, 2020. p. 307-311 (ICCE 2020 - 28th International Conference on Computers in Education, Proceedings; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy

AU - Lu, Owen H.T.

AU - Huang, Anna Y.Q.

AU - Kuo, Che Yu

AU - Chen, Irene Y.L.

AU - Yang, Stephen J.H.

PY - 2020/11/23

Y1 - 2020/11/23

N2 - SQ3R (survey, question, read, recite, and review) is an efficient reading method that has confirmed the benefits of learning performance in numerous studies. To demonstrate that the e-book reading environment can also obtain the benefits of SQ3R, we conducted a course with 60 students, classify students into two groups based on the SQ3R ability. The results show that in the context of e-book reading, students' behavior: (1) create a memo and modify it regarding the reviewing content (CMeP) and (2) create a memo and modify it at the next login (CMeO) is related to recite and review steps in SQ3R. Furthermore, the above two e-book reading behaviors are positively related to students' learning performance and learning engagement.

AB - SQ3R (survey, question, read, recite, and review) is an efficient reading method that has confirmed the benefits of learning performance in numerous studies. To demonstrate that the e-book reading environment can also obtain the benefits of SQ3R, we conducted a course with 60 students, classify students into two groups based on the SQ3R ability. The results show that in the context of e-book reading, students' behavior: (1) create a memo and modify it regarding the reviewing content (CMeP) and (2) create a memo and modify it at the next login (CMeO) is related to recite and review steps in SQ3R. Furthermore, the above two e-book reading behaviors are positively related to students' learning performance and learning engagement.

KW - Computer-assisted learning

KW - Reading strategy

KW - SQ3R

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M3 - 會議論文篇章

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T3 - ICCE 2020 - 28th International Conference on Computers in Education, Proceedings

SP - 307

EP - 311

BT - ICCE 2020 - 28th International Conference on Computers in Education, Proceedings

A2 - So, Hyo-Jeong

A2 - Rodrigo, Ma. Mercedes

A2 - Mason, Jon

A2 - Mitrovic, Antonija

A2 - Bodemer, Daniel

A2 - Chen, Weichao

A2 - Chen, Zhi-Hong

A2 - Flanagan, Brendan

A2 - Jansen, Marc

A2 - Nkambou, Roger

A2 - Wu, Longkai

PB - Asia-Pacific Society for Computers in Education

T2 - 28th International Conference on Computers in Education, ICCE 2020

Y2 - 23 November 2020 through 27 November 2020

ER -

Lu OHT, Huang AYQ, Kuo CY, Chen IYL, Yang SJH. Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy. In So HJ, Rodrigo MM, Mason J, Mitrovic A, Bodemer D, Chen W, Chen ZH, Flanagan B, Jansen M, Nkambou R, Wu L, editors, ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. Asia-Pacific Society for Computers in Education. 2020. p. 307-311. (ICCE 2020 - 28th International Conference on Computers in Education, Proceedings).

Sequence pattern mining for the identification of reading behavior based on SQ3R reading strategy

Abstract

Publication series

Conference

Keywords

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Projects

The Research of Applying Educational Big Data and Learning Analytics to Improve Self-Regulated Learning in Programming(1/3)

An Empirical Study on the Cultivation and Learning Analytics of Computational Thinking Skills(2/3)

The Research of Applying Big Data to Improving Moocs Learning Analytics：An Empirical Study of College Calculus(3/3)

Cite this