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Factors Affecting English Reading in Macao, Hong Kong, and Singapore : = Combining Machine Learning Methods and Hierarchical Linear Regressions Using PISA 2018 Data.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Factors Affecting English Reading in Macao, Hong Kong, and Singapore :/
Reminder of title:	Combining Machine Learning Methods and Hierarchical Linear Regressions Using PISA 2018 Data.
Author:	Luo, Shuqiong.
Description:	1 online resource (191 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-03, Section: A.
Contained By:	Dissertations Abstracts International85-03A.
Subject:	Education. -
Online resource:	click for full text (PQDT)
ISBN:	9798380412810

Factors Affecting English Reading in Macao, Hong Kong, and Singapore : = Combining Machine Learning Methods and Hierarchical Linear Regressions Using PISA 2018 Data.
Luo, Shuqiong.

Factors Affecting English Reading in Macao, Hong Kong, and Singapore :Combining Machine Learning Methods and Hierarchical Linear Regressions Using PISA 2018 Data. - 1 online resource (191 pages)

Source: Dissertations Abstracts International, Volume: 85-03, Section: A.

Thesis (Ph.D.)--University of Macau, 2023.

Includes bibliographical references

In the digital era, increasing attention has been paid to students' digital reading achievement. However, the existing literature only paid attention to a limited set of factors that may influence digital reading achievement. Situated in Macao, Hong Kong, and Singapore, this doctoral thesis aimed to (1) provide a holistic perspective of English digital reading achievement by identifying the key predictors, (2) examine how language exposure interacts with socioeconomic status (SES) in predicting students' English digital reading achievement, (3) explore the relation between growth mindset, SES, and English digital reading achievement, and (4) investigate the influence of ICT competencies on English digital reading achievement.Four related studies were designed utilizing the Program for International Student Assessment (PISA) 2018 data, including 7703 15-year-old students from Macao, Hong Kong, and Singapore. Grounded by the socio-ecological theory, study 1 comprehensively explored the relative importance of the 22 individual, microsystem, mesosystem variables on English digital reading achievement with a machine learning approach (i.e., random forest regression). This study identified eleven key factors that best predicted students' English digital reading achievement. Results from study 2 revealed: 1) the negative relationship between language exposure from mother and English digital reading achievement; 2) language exposure from best friends and siblings showed a positive influence on English digital reading achievement; 3) the effects of language exposure from schoolmates differed among the three economies; 4) SES did not moderate the relationship between language exposure and English digital reading achievement. The results of study 3 showed that growth mindset and socioeconomic status were positively related to students' English digital reading achievement, while the moderating role of socioeconomic status in the link between growth mindset and English digital reading achievement was not significant in the three economies. The results of study 4 revealed that students' ICT literacy was negatively correlated with their English digital reading achievement, while the influence of attitudes toward ICT varied. In general, this doctoral dissertation may shed light on extending the understanding of digital reading achievement in English in Macao, Hong Kong, and Singapore.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380412810Subjects--Topical Terms:

555912
Education.
Subjects--Index Terms:

English digital reading achievementIndex Terms--Genre/Form:

554714
Electronic books.

Factors Affecting English Reading in Macao, Hong Kong, and Singapore : = Combining Machine Learning Methods and Hierarchical Linear Regressions Using PISA 2018 Data.
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