A personalised task recommendation system for vocabulary learning based on readability and diversity

Haoran XIE; Minhong WANG; Di ZOU; Fu Lee WANG

doi:10.1007/978-3-030-21562-0_7

A personalised task recommendation system for vocabulary learning based on readability and diversity

Haoran XIE, Minhong WANG, Di ZOU, Fu Lee WANG

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

9 Citations (Scopus)

Abstract

Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners’ vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants’ learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners.

Original language	English
Title of host publication	Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings
Editors	Simon K. S. CHEUNG, Lap-Kei LEE, Ivana SIMONOVA, Tomas KOZEL, Lam-For KWOK
Place of Publication	Switzerland
Publisher	Springer Nature Switzerland AG
Pages	82-92
Number of pages	11
ISBN (Electronic)	9783030215620
ISBN (Print)	9783030215613
DOIs	https://doi.org/10.1007/978-3-030-21562-0_7
Publication status	Published - 2019
Externally published	Yes
Event	12th International Conference on Blended Learning - Hradec Kralove, Czech Republic Duration: 2 Jul 2019 → 4 Jul 2019 http://www.aimtech.cityu.edu.hk/icbl2019/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11546 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Blended Learning
Abbreviated title	ICBL 2019
Country/Territory	Czech Republic
Period	2/07/19 → 4/07/19
Internet address	http://www.aimtech.cityu.edu.hk/icbl2019/

Keywords

Diversity
Personalized learning
Readability
Recommendation system
Word learning

Access to Document

10.1007/978-3-030-21562-0_7

Cite this

XIE, H., WANG, M., ZOU, D., & WANG, F. L. (2019). A personalised task recommendation system for vocabulary learning based on readability and diversity. In S. K. S. CHEUNG, L.-K. LEE, I. SIMONOVA, T. KOZEL, & L.-F. KWOK (Eds.), Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings (pp. 82-92). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11546 LNCS). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-21562-0_7

XIE, Haoran ; WANG, Minhong ; ZOU, Di et al. / A personalised task recommendation system for vocabulary learning based on readability and diversity. Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings. editor / Simon K. S. CHEUNG ; Lap-Kei LEE ; Ivana SIMONOVA ; Tomas KOZEL ; Lam-For KWOK. Switzerland : Springer Nature Switzerland AG, 2019. pp. 82-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A personalised task recommendation system for vocabulary learning based on readability and diversity",

abstract = "Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners{\textquoteright} vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants{\textquoteright} learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners.",

keywords = "Diversity, Personalized learning, Readability, Recommendation system, Word learning",

author = "Haoran XIE and Minhong WANG and Di ZOU and WANG, {Fu Lee}",

year = "2019",

doi = "10.1007/978-3-030-21562-0_7",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings",

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XIE, H, WANG, M, ZOU, D & WANG, FL 2019, A personalised task recommendation system for vocabulary learning based on readability and diversity. in SKS CHEUNG, L-K LEE, I SIMONOVA, T KOZEL & L-F KWOK (eds), Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11546 LNCS, Springer Nature Switzerland AG, Switzerland, pp. 82-92, 12th International Conference on Blended Learning, Czech Republic, 2/07/19. https://doi.org/10.1007/978-3-030-21562-0_7

A personalised task recommendation system for vocabulary learning based on readability and diversity. / XIE, Haoran; WANG, Minhong; ZOU, Di et al.
Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings. ed. / Simon K. S. CHEUNG; Lap-Kei LEE; Ivana SIMONOVA; Tomas KOZEL; Lam-For KWOK. Switzerland: Springer Nature Switzerland AG, 2019. p. 82-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11546 LNCS).

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

TY - GEN

T1 - A personalised task recommendation system for vocabulary learning based on readability and diversity

AU - XIE, Haoran

AU - WANG, Minhong

AU - ZOU, Di

AU - WANG, Fu Lee

PY - 2019

Y1 - 2019

N2 - Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners’ vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants’ learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners.

AB - Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners’ vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants’ learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners.

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KW - Personalized learning

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KW - Word learning

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M3 - Conference paper (refereed)

SN - 9783030215613

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings

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A2 - LEE, Lap-Kei

A2 - SIMONOVA, Ivana

A2 - KOZEL, Tomas

A2 - KWOK, Lam-For

PB - Springer Nature Switzerland AG

CY - Switzerland

T2 - 12th International Conference on Blended Learning

Y2 - 2 July 2019 through 4 July 2019

ER -

XIE H, WANG M, ZOU D, WANG FL. A personalised task recommendation system for vocabulary learning based on readability and diversity. In CHEUNG SKS, LEE LK, SIMONOVA I, KOZEL T, KWOK LF, editors, Blended Learning : Educational Innovation for Personalized Learning : 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2–4, 2019, proceedings. Switzerland: Springer Nature Switzerland AG. 2019. p. 82-92. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2019 May 31. doi: 10.1007/978-3-030-21562-0_7

A personalised task recommendation system for vocabulary learning based on readability and diversity

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Keywords

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