Synergistic effects of instruction and affect factors on high- and low-ability disparities in elementary students’ reading literacy
Abstract This study examined the combined effects of teachers’ instructional practices and students’ reading-related affective engagement on predicting the high and low levels of elementary reading literacy from a linguistically and culturally comparative perspective. Data were based on 9748 student...
Ausführliche Beschreibung
Autor*in: |
Chen, Jiangping [verfasserIn] |
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Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Anmerkung: |
© Springer Nature B.V. 2020 |
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Übergeordnetes Werk: |
Enthalten in: Reading and writing - Springer Netherlands, 1989, 34(2020), 1 vom: 13. Juli, Seite 199-230 |
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Übergeordnetes Werk: |
volume:34 ; year:2020 ; number:1 ; day:13 ; month:07 ; pages:199-230 |
Links: |
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DOI / URN: |
10.1007/s11145-020-10070-0 |
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OLC2122911352 |
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10.1007/s11145-020-10070-0 doi (DE-627)OLC2122911352 (DE-He213)s11145-020-10070-0-p DE-627 ger DE-627 rakwb eng 150 400 VZ 24,1 5,3 7,11 ssgn LING DE-30 fid Chen, Jiangping verfasserin aut Synergistic effects of instruction and affect factors on high- and low-ability disparities in elementary students’ reading literacy 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract This study examined the combined effects of teachers’ instructional practices and students’ reading-related affective engagement on predicting the high and low levels of elementary reading literacy from a linguistically and culturally comparative perspective. Data were based on 9748 students from 4 English-speaking and 3 Chinese-speaking education systems participating in the Progress in International Reading Literacy Study 2016. A mixed theory-based and data-driven approach was adopted. Four machine learning algorithms, specifically logistic regression, support vector machine, decision tree, and extreme gradient boosting, were simultaneously used to classify and predict high- and low-proficiency readers and to identify the most important factors for the ability separation. The findings showed that for both system groups, those factors together were sufficiently powerful to discriminate the readers and that the affective constructs, particularly students’ self-concepts, played a predominant role. The Chinese-speaking systems, compared with their English counterparts, applied more effective pedagogies to nurture sophisticated readers. Data mining Effective reading pedagogies Elementary reading literacy PIRLS 2016 Reading self-concepts Zhang, Yang aut Hu, Jie (orcid)0000-0003-2219-2587 aut Enthalten in Reading and writing Springer Netherlands, 1989 34(2020), 1 vom: 13. Juli, Seite 199-230 (DE-627)182284557 (DE-600)1193661-7 (DE-576)515052175 0922-4777 nnns volume:34 year:2020 number:1 day:13 month:07 pages:199-230 https://doi.org/10.1007/s11145-020-10070-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-LING SSG-OLC-BUB SSG-OPC-BBI AR 34 2020 1 13 07 199-230 |
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10.1007/s11145-020-10070-0 doi (DE-627)OLC2122911352 (DE-He213)s11145-020-10070-0-p DE-627 ger DE-627 rakwb eng 150 400 VZ 24,1 5,3 7,11 ssgn LING DE-30 fid Chen, Jiangping verfasserin aut Synergistic effects of instruction and affect factors on high- and low-ability disparities in elementary students’ reading literacy 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract This study examined the combined effects of teachers’ instructional practices and students’ reading-related affective engagement on predicting the high and low levels of elementary reading literacy from a linguistically and culturally comparative perspective. Data were based on 9748 students from 4 English-speaking and 3 Chinese-speaking education systems participating in the Progress in International Reading Literacy Study 2016. A mixed theory-based and data-driven approach was adopted. Four machine learning algorithms, specifically logistic regression, support vector machine, decision tree, and extreme gradient boosting, were simultaneously used to classify and predict high- and low-proficiency readers and to identify the most important factors for the ability separation. The findings showed that for both system groups, those factors together were sufficiently powerful to discriminate the readers and that the affective constructs, particularly students’ self-concepts, played a predominant role. The Chinese-speaking systems, compared with their English counterparts, applied more effective pedagogies to nurture sophisticated readers. Data mining Effective reading pedagogies Elementary reading literacy PIRLS 2016 Reading self-concepts Zhang, Yang aut Hu, Jie (orcid)0000-0003-2219-2587 aut Enthalten in Reading and writing Springer Netherlands, 1989 34(2020), 1 vom: 13. Juli, Seite 199-230 (DE-627)182284557 (DE-600)1193661-7 (DE-576)515052175 0922-4777 nnns volume:34 year:2020 number:1 day:13 month:07 pages:199-230 https://doi.org/10.1007/s11145-020-10070-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-LING SSG-OLC-BUB SSG-OPC-BBI AR 34 2020 1 13 07 199-230 |
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abstract |
Abstract This study examined the combined effects of teachers’ instructional practices and students’ reading-related affective engagement on predicting the high and low levels of elementary reading literacy from a linguistically and culturally comparative perspective. Data were based on 9748 students from 4 English-speaking and 3 Chinese-speaking education systems participating in the Progress in International Reading Literacy Study 2016. A mixed theory-based and data-driven approach was adopted. Four machine learning algorithms, specifically logistic regression, support vector machine, decision tree, and extreme gradient boosting, were simultaneously used to classify and predict high- and low-proficiency readers and to identify the most important factors for the ability separation. The findings showed that for both system groups, those factors together were sufficiently powerful to discriminate the readers and that the affective constructs, particularly students’ self-concepts, played a predominant role. The Chinese-speaking systems, compared with their English counterparts, applied more effective pedagogies to nurture sophisticated readers. © Springer Nature B.V. 2020 |
abstractGer |
Abstract This study examined the combined effects of teachers’ instructional practices and students’ reading-related affective engagement on predicting the high and low levels of elementary reading literacy from a linguistically and culturally comparative perspective. Data were based on 9748 students from 4 English-speaking and 3 Chinese-speaking education systems participating in the Progress in International Reading Literacy Study 2016. A mixed theory-based and data-driven approach was adopted. Four machine learning algorithms, specifically logistic regression, support vector machine, decision tree, and extreme gradient boosting, were simultaneously used to classify and predict high- and low-proficiency readers and to identify the most important factors for the ability separation. The findings showed that for both system groups, those factors together were sufficiently powerful to discriminate the readers and that the affective constructs, particularly students’ self-concepts, played a predominant role. The Chinese-speaking systems, compared with their English counterparts, applied more effective pedagogies to nurture sophisticated readers. © Springer Nature B.V. 2020 |
abstract_unstemmed |
Abstract This study examined the combined effects of teachers’ instructional practices and students’ reading-related affective engagement on predicting the high and low levels of elementary reading literacy from a linguistically and culturally comparative perspective. Data were based on 9748 students from 4 English-speaking and 3 Chinese-speaking education systems participating in the Progress in International Reading Literacy Study 2016. A mixed theory-based and data-driven approach was adopted. Four machine learning algorithms, specifically logistic regression, support vector machine, decision tree, and extreme gradient boosting, were simultaneously used to classify and predict high- and low-proficiency readers and to identify the most important factors for the ability separation. The findings showed that for both system groups, those factors together were sufficiently powerful to discriminate the readers and that the affective constructs, particularly students’ self-concepts, played a predominant role. The Chinese-speaking systems, compared with their English counterparts, applied more effective pedagogies to nurture sophisticated readers. © Springer Nature B.V. 2020 |
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title_short |
Synergistic effects of instruction and affect factors on high- and low-ability disparities in elementary students’ reading literacy |
url |
https://doi.org/10.1007/s11145-020-10070-0 |
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author2 |
Zhang, Yang Hu, Jie |
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Zhang, Yang Hu, Jie |
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doi_str |
10.1007/s11145-020-10070-0 |
up_date |
2024-07-03T15:22:59.423Z |
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