Parental support in education and social integration of migrant children in urban public schools in China

Hu, Bo; Wu, Wenjie

doi:10.1016/j.cities.2020.102870

Cited by 14 publications

(13 citation statements)

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“…Furthermore, we were also interested in the effect of perceived social support from family and friends in the change in school belonging. This was important since previous research indicated that peer support had a positive impact on school belonging (Allen et al, 2018;Ambrose, 2020;Ho et al, 2017), as well as family support at home (Allen et al, 2018;Hu & Wu, 2020). Investigating the effects of social support structures was also pertinent as previous research indicates that migrant students experienced challenges to participation in online teaching during Covid-19 school closures (OECD, 2021;Primdahl et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…School belonging has been established in the literature as a positive predictor of educational achievement, academic self-efficacy and attitudes (Fong Lam et al, 2015;Niehaus et al, 2012), andwellbeing (Kia-Keating &Ellis, 2007;Nuttman-Shwartz, 2019;Scharpf et al, 2020). Previous research has shown that positive peer relationships, connectedness with friends (Allen et al, 2018;Ambrose, 2020;Delgado et al, 2016;DeNicolo et al, 2017;Van Caudenberg et al, 2020), and parental support at home (Allen et al, 2018;Hu & Wu, 2020) are linked to increased feelings of school belonging. Research has also found that school belonging forms a protective factor against the development of mental health problems (Kia-Keating & Ellis, 2007;Nuttman-Shwartz, 2019;Scharpf et al, 2020).…”

Section: Theoretical Underpinnings Of School Belonging and Literature...mentioning

confidence: 99%

“…DeNicolo et al ( 2017) identify the quality of teacher-student and peer relationships, as well as migrant students' agency, as key components in creating a positive sense of belonging for migrant students. Friendships and social support from peers and family can foster belonging and wellbeing (Allen et al, 2018;Ho et al, 2017;Hu & Wu, 2020;Nuttman-Shwartz, 2019). Schools can enhance feelings of belonging by facilitating newcomers' settlement in a new country, and by building positive social relationships in schools (Schweitzer et al, 2021).…”

Section: Theoretical Underpinnings Of School Belonging and Literature...mentioning

confidence: 99%

See 2 more Smart Citations

Migrant Students’ Sense of Belonging and the Covid‐19 Pandemic: Implications for Educational Inclusion

Szelei

Devlieger

Verelst

et al. 2022

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This article investigates school belonging among migrant students and how this changed during the Covid‐19 pandemic. Drawing on quantitative data gathered from 751 migrant students in secondary schools in six European countries (Belgium, Denmark, Finland, Norway, Sweden, and the UK), we examined the impact of Covid‐19 school closures, social support, and post‐traumatic stress symptoms on changes in school belonging. Linear regression showed a non‐significant decrease in school belonging, and none of the studied variables had a significant effect on this change in our whole sample. However, sensitivity analysis on a subsample from three countries (Denmark, Finland, and the UK) showed a small but significant negative effect of increasing post‐traumatic stress symptoms on school belonging during Covid‐19 school closures. Given that scholarship on school belonging during Covid‐19 is emergent, this study delineates some key areas for future research on the relationship between wellbeing, school belonging, and inclusion.

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Section: Discussionmentioning

confidence: 99%

Section: Theoretical Underpinnings Of School Belonging and Literature...mentioning

confidence: 99%

Section: Theoretical Underpinnings Of School Belonging and Literature...mentioning

confidence: 99%

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Migrant Students’ Sense of Belonging and the Covid‐19 Pandemic: Implications for Educational Inclusion

Szelei

Devlieger

Verelst

et al. 2022

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“…However, the proportion of migrant children in grades 1 and 2 is significantly higher than that of local children ( p < 0.05). The high proportions of migrant children in the grades 1 and 2 may be because the children are so young that the parents want to take them and care them themselves ( Hu and Wu, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

The Influencing Legal and Factors of Migrant Children’s Educational Integration Based on Convolutional Neural Network

Zhang

Wang

Zhou³

et al. 2022

Front. Psychol.

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This research aims to analyze the influencing factors of migrant children’s education integration based on the convolutional neural network (CNN) algorithm. The attention mechanism, LSTM, and GRU are introduced based on the CNN algorithm, to establish an ALGCNN model for text classification. Film and television review data set (MR), Stanford sentiment data set (SST), and news opinion data set (MPQA) are used to analyze the classification accuracy, loss value, Hamming loss (HL), precision (Pre), recall (Re), and micro-F1 (F1) of the ALGCNN model. Then, on the big data platform, data in the Comprehensive Management System of Floating Population and Rental Housing, Student Status Information Management System, and Student Information Management System of Beijing city are taken as samples. The ALGCNN model is used to classify and compare related data. It is found that in the MR, STT, and MPQA data sets, the classification accuracy and loss value of the ALGCNN model are better than other algorithms. HL is the lowest (15.2 ± 1.38%), the Pre is second only to the BERT algorithm, and the Re and F1 are both higher than other algorithms. From 2015 to 2019, the number of migrant children in different grades of elementary school shows a gradual increase. Among migrant children, the number of migrant children from other counties in this province is evidently higher than the number of migrant children from other provinces. Among children of migrant workers, the number of immigrants from other counties in this province is also notably higher than the number of immigrants from other provinces. With the gradual increase in the years, the proportion of township-level expenses shows a gradual decrease, whereas the proportion of district and county-level expenses shows a gradual increase. Moreover, the accuracy of the ALGCNN model in migrant children and local children data classification is 98.6 and 98.9%, respectively. The proportion of migrant children in the first and second grades of a primary school in Beijing city is obviously higher than that of local children (p < 0.05). The average final score of local children was greatly higher than that of migrant children (p < 0.05), whereas the scores of migrant children’s listening methods, learning skills, and learning environment adaptability are lower, which shows that an effective text classification model (ALGCNN) is established based on the CNN algorithm. In short, the children’s education costs, listening methods, learning skills, and learning environment adaptability are the main factors affecting migrant children’s educational integration, and this work provides a reference for the analysis of migrant children’s educational integration.

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“…This work defines the EP as the policies and regulations determined by national legislation to ensure that MC in the stage of CE can obtain the same educational opportunities as local children. Its purpose is to ensure the education of MC, especially to promote their integration into local society (Hu and Wu, 2020).…”

Section: Education Policy Evaluation Modelingmentioning

confidence: 99%

Influence Analysis of Education Policy on Migrant Children’s Education Integration Using Artificial Intelligence and Deep Learning

Chen

Song²,

Yuan³

et al. 2022

Front. Psychol.

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This work intends to solve the problem that the traditional education system cannot reasonably adjust the educational integration of children with the arrival of labor force in a short time, and support the education of migrant children (MC) in the education policy (EP) to integrate them into the local educational environment as soon as possible. Firstly, this work defines the surplus labor force and MC. Secondly, the principles of Artificial Intelligence (AI) and Deep Learning (DL) are introduced. Thirdly, it analyzes the education of MC and relevant policies, and the data of the education effect of MC are collected and the evaluation effect model is built. Finally, the evaluation model of MC’s education effect is applied to test the effect of EP. The results show that using AI technology combined with DL technology to model the education effect of MC can establish an effective and accurate evaluation model of the education effect of MC, effectively evaluate the impact of local education policies on the education of MC, and give an effective effect analysis of relevant education policies in each period. The result of Adaptive Resonance Theory (ART)–Back Propagation algorithm is 65 ∼ 96%, which is much higher than the efficiency of traditional algorithms. This shows that the education integration evaluation model of MC based on AI technology and DL technology can effectively and accurately evaluate the integration effect of MC on the local education system, and then provide reference for local and even national adjustment of education policies. The results provide a new idea for the application of new technology in EP.

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Parental support in education and social integration of migrant children in urban public schools in China

Cited by 14 publications

References 47 publications

Migrant Students’ Sense of Belonging and the Covid‐19 Pandemic: Implications for Educational Inclusion

Migrant Students’ Sense of Belonging and the Covid‐19 Pandemic: Implications for Educational Inclusion

The Influencing Legal and Factors of Migrant Children’s Educational Integration Based on Convolutional Neural Network

Influence Analysis of Education Policy on Migrant Children’s Education Integration Using Artificial Intelligence and Deep Learning

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