UM  > Faculty of Education
Residential Collegefalse
Status已發表Published
Identifying Key Contextual Factors of Digital Reading Literacy Through a Machine Learning Approach
Chen, Fu1; Sakyi, Alfred2; Cui, Ying3
2022-12
Source PublicationJOURNAL OF EDUCATIONAL COMPUTING RESEARCH
ISSN0735-6331
Volume60Issue:7Pages:1763-1795
Abstract

Few of previous reading studies comprehensively examined the contributing factors of students’ digital reading literacy. To fill this gap, based upon the ecological perspective, this study aims to investigate which factors from the student, home, and school context are more important in discriminating high-performing digital readers from non–high-performing digital readers. The data of the Progress in International Reading Literacy Study 2016 with 74,692 Grade 4 students from 14 countries and economies was analyzed using the machine learning approach of support vector machine with recursive feature elimination. Results showed that except print reading levels, students’ reading self-efficacy, home resources for learning, talking about what have read in class, and the number of books in the home are the most influential contextual factors contributing to the high performance of digital readers. The selected 20 key contextual factors render a high prediction power for discriminating digital readers. Our findings show that, in general, home-related factors have overarching influences on children’s digital reading development; at the school level, instruction-related features are more influential than school characteristics.

KeywordDigital Reading Reading Literacy Large-scale Assessment Machine Learning Support Vector Machine
DOI10.1177/07356331221083215
URLView the original
Indexed BySSCI
Language英語English
WOS Research AreaEducation & Educational Research
WOS SubjectEducation & Educational Research
WOS IDWOS:000780191600001
PublisherSAGE PUBLICATIONS INC, 2455 TELLER RD, THOUSAND OAKS, CA 91320
Scopus ID2-s2.0-85129212755
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Education
Corresponding AuthorChen, Fu
Affiliation1.Faculty of Education, University of Macau, Macao
2.Research Branch, Alberta Education, Edmonton, Canada
3.Department of Educational Psychology, University of Alberta, Edmonton, Canada
First Author AffilicationFaculty of Education
Corresponding Author AffilicationFaculty of Education
Recommended Citation
GB/T 7714
Chen, Fu,Sakyi, Alfred,Cui, Ying. Identifying Key Contextual Factors of Digital Reading Literacy Through a Machine Learning Approach[J]. JOURNAL OF EDUCATIONAL COMPUTING RESEARCH, 2022, 60(7), 1763-1795.
APA Chen, Fu., Sakyi, Alfred., & Cui, Ying (2022). Identifying Key Contextual Factors of Digital Reading Literacy Through a Machine Learning Approach. JOURNAL OF EDUCATIONAL COMPUTING RESEARCH, 60(7), 1763-1795.
MLA Chen, Fu,et al."Identifying Key Contextual Factors of Digital Reading Literacy Through a Machine Learning Approach".JOURNAL OF EDUCATIONAL COMPUTING RESEARCH 60.7(2022):1763-1795.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chen, Fu]'s Articles
[Sakyi, Alfred]'s Articles
[Cui, Ying]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen, Fu]'s Articles
[Sakyi, Alfred]'s Articles
[Cui, Ying]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen, Fu]'s Articles
[Sakyi, Alfred]'s Articles
[Cui, Ying]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.