Pub Date : 2024-07-26DOI: 10.1186/s40536-024-00211-0
John Ainley, Wolfram Schulz
Religious attachment has been identified as an important correlate of civic participation, civic engagement, and civil participation among adults. This study investigates two aspects of relationships between religiosity and intended political engagement among lower secondary school students in 2009 and 2016. One aspect is the extent to which religious attachment is associated with an endorsement of the influence of religion in society. This can be viewed as the converse of secularity which asks for the separation of social and political institutions from religion. A second aspect investigated is the extent to which religious attachment is associated with expected adult electoral participation and expected adult active political participation after controlling for the effects of other characteristics. While the results from this study show no strong or consistent relationships between religious background and expected political participation among lower-secondary students, findings suggest that young people’s endorsement of religious influence in society depends strongly on their religious background and in turn shows associations with expected active political participation.
{"title":"The influence of religious attachment on intended political engagement among lower-secondary students","authors":"John Ainley, Wolfram Schulz","doi":"10.1186/s40536-024-00211-0","DOIUrl":"https://doi.org/10.1186/s40536-024-00211-0","url":null,"abstract":"Religious attachment has been identified as an important correlate of civic participation, civic engagement, and civil participation among adults. This study investigates two aspects of relationships between religiosity and intended political engagement among lower secondary school students in 2009 and 2016. One aspect is the extent to which religious attachment is associated with an endorsement of the influence of religion in society. This can be viewed as the converse of secularity which asks for the separation of social and political institutions from religion. A second aspect investigated is the extent to which religious attachment is associated with expected adult electoral participation and expected adult active political participation after controlling for the effects of other characteristics. While the results from this study show no strong or consistent relationships between religious background and expected political participation among lower-secondary students, findings suggest that young people’s endorsement of religious influence in society depends strongly on their religious background and in turn shows associations with expected active political participation.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-22DOI: 10.1186/s40536-024-00200-3
Qi Huang, Daniel M. Bolt, Weicong Lyu
Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification. Determining the validity of the source of DIF has implications for how it is handled in practice. We demonstrate a form of sensitivity analysis that can point to model misspecification induced by item complexity as a possible cause of DIF, and show how such a cause of DIF might be accommodated through attempts to generalize the IRT model for the studied item(s) in psychometrically and psychologically plausible ways. In both simulated illustrations and empirical data from TIMSS 2011 and TIMSS 2019 4th and 8th Grade Math and Science, we have found that using a form of proposed IRT model generalization can substantially reduce DIF when IRT model misspecification is at least a partial cause of the observed DIF. By demonstrating item complexity as a possible valid source of DIF and showing the effectiveness of the proposed approach, we recommend additional attention toward model generalizations as a means of addressing and/or understanding DIF.
{"title":"Investigating item complexity as a source of cross-national DIF in TIMSS math and science","authors":"Qi Huang, Daniel M. Bolt, Weicong Lyu","doi":"10.1186/s40536-024-00200-3","DOIUrl":"https://doi.org/10.1186/s40536-024-00200-3","url":null,"abstract":"Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification. Determining the validity of the source of DIF has implications for how it is handled in practice. We demonstrate a form of sensitivity analysis that can point to model misspecification induced by item complexity as a possible cause of DIF, and show how such a cause of DIF might be accommodated through attempts to generalize the IRT model for the studied item(s) in psychometrically and psychologically plausible ways. In both simulated illustrations and empirical data from TIMSS 2011 and TIMSS 2019 4th and 8th Grade Math and Science, we have found that using a form of proposed IRT model generalization can substantially reduce DIF when IRT model misspecification is at least a partial cause of the observed DIF. By demonstrating item complexity as a possible valid source of DIF and showing the effectiveness of the proposed approach, we recommend additional attention toward model generalizations as a means of addressing and/or understanding DIF.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140635996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-12DOI: 10.1186/s40536-024-00198-8
Jiyoun Kim, Chia-Wen Chen, Yi-Jhen Wu
Learning strategies have been recognized as important predictors of mathematical achievement. In recent studies, it has been found that Asian students use combined learning strategies, primarily including metacognitive strategies, rather than rote memorization. To the best of the authors’ knowledge, there is only one prior study including South Korea in investigations of the relationship between learning strategies and mathematics achievement in PISA 2012. In that study, students were classified into groups using specific learning strategies, and their mathematics achievements were compared. There are two research gaps: (1) previous studies insufficiently explored how students use learning strategies in the South Korean education system, and (2) there is little research applying the nominal response model (NRM) to explore the association between learning strategy use and mathematics achievement in PISA 2012. Thus, the present study explores to what extent the NRM fits the data compared to the generalized partial credit model (GPCM). We created a learning strategy score from the NRM for South Korean students in PISA 2012 (N = 3,310). Then, using correlation analysis and quadratic regression analysis, we identified linear and nonlinear relations between learning strategy scores from the NRM and mathematics achievement. The findings indicated that (1) NRM was a better fit for creating learning strategy scores than GPCM, (2) the average correlation coefficient between the learning strategy score and mathematics achievement was 0.18 (p < .05), and (3) for the curvilinear relationship between the learning strategy score and mathematics achievement, the standardized quadratic coefficient was − 0.090 (p < .001). Overall, the NRM represents an appropriate model for explaining the relationship between learning strategy and mathematical achievement. Additionally, high-performing South Korean students tend to primarily use metacognitive strategies with memorization. The negative quadratic coefficient captured the limited effect of the primary use of metacognitive strategies with memorization. The implications for the South Korean education system are discussed.
{"title":"Exploration of the linear and nonlinear relationships between learning strategies and mathematics achievement in South Korea using the nominal response model : PISA 2012","authors":"Jiyoun Kim, Chia-Wen Chen, Yi-Jhen Wu","doi":"10.1186/s40536-024-00198-8","DOIUrl":"https://doi.org/10.1186/s40536-024-00198-8","url":null,"abstract":"Learning strategies have been recognized as important predictors of mathematical achievement. In recent studies, it has been found that Asian students use combined learning strategies, primarily including metacognitive strategies, rather than rote memorization. To the best of the authors’ knowledge, there is only one prior study including South Korea in investigations of the relationship between learning strategies and mathematics achievement in PISA 2012. In that study, students were classified into groups using specific learning strategies, and their mathematics achievements were compared. There are two research gaps: (1) previous studies insufficiently explored how students use learning strategies in the South Korean education system, and (2) there is little research applying the nominal response model (NRM) to explore the association between learning strategy use and mathematics achievement in PISA 2012. Thus, the present study explores to what extent the NRM fits the data compared to the generalized partial credit model (GPCM). We created a learning strategy score from the NRM for South Korean students in PISA 2012 (N = 3,310). Then, using correlation analysis and quadratic regression analysis, we identified linear and nonlinear relations between learning strategy scores from the NRM and mathematics achievement. The findings indicated that (1) NRM was a better fit for creating learning strategy scores than GPCM, (2) the average correlation coefficient between the learning strategy score and mathematics achievement was 0.18 (p < .05), and (3) for the curvilinear relationship between the learning strategy score and mathematics achievement, the standardized quadratic coefficient was − 0.090 (p < .001). Overall, the NRM represents an appropriate model for explaining the relationship between learning strategy and mathematical achievement. Additionally, high-performing South Korean students tend to primarily use metacognitive strategies with memorization. The negative quadratic coefficient captured the limited effect of the primary use of metacognitive strategies with memorization. The implications for the South Korean education system are discussed.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140576908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-08DOI: 10.1186/s40536-024-00199-7
Ji Yoon Jung, Lillian Tyack, Matthias von Davier
Artificial intelligence (AI) is rapidly changing communication and technology-driven content creation and is also being used more frequently in education. Despite these advancements, AI-powered automated scoring in international large-scale assessments (ILSAs) remains largely unexplored due to the scoring challenges associated with processing large amounts of multilingual responses. However, due to their low-stakes nature, ILSAs are an ideal ground for innovations and exploring new methodologies. This study proposes combining state-of-the-art machine translations (i.e., Google Translate & ChatGPT) and artificial neural networks (ANNs) to mitigate two key concerns of human scoring: inconsistency and high expense. We applied AI-based automated scoring to multilingual student responses from eight countries and six different languages, using six constructed response items from TIMSS 2019. Automated scoring displayed comparable performance to human scoring, especially when the ANNs were trained and tested on ChatGPT-translated responses. Furthermore, psychometric characteristics derived from machine scores generally exhibited similarity to those obtained from human scores. These results can be considered as supportive evidence for the validity of automated scoring for survey assessments. This study highlights that automated scoring integrated with the recent machine translation holds great promise for consistent and resource-efficient scoring in ILSAs.
{"title":"Combining machine translation and automated scoring in international large-scale assessments","authors":"Ji Yoon Jung, Lillian Tyack, Matthias von Davier","doi":"10.1186/s40536-024-00199-7","DOIUrl":"https://doi.org/10.1186/s40536-024-00199-7","url":null,"abstract":"Artificial intelligence (AI) is rapidly changing communication and technology-driven content creation and is also being used more frequently in education. Despite these advancements, AI-powered automated scoring in international large-scale assessments (ILSAs) remains largely unexplored due to the scoring challenges associated with processing large amounts of multilingual responses. However, due to their low-stakes nature, ILSAs are an ideal ground for innovations and exploring new methodologies. This study proposes combining state-of-the-art machine translations (i.e., Google Translate & ChatGPT) and artificial neural networks (ANNs) to mitigate two key concerns of human scoring: inconsistency and high expense. We applied AI-based automated scoring to multilingual student responses from eight countries and six different languages, using six constructed response items from TIMSS 2019. Automated scoring displayed comparable performance to human scoring, especially when the ANNs were trained and tested on ChatGPT-translated responses. Furthermore, psychometric characteristics derived from machine scores generally exhibited similarity to those obtained from human scores. These results can be considered as supportive evidence for the validity of automated scoring for survey assessments. This study highlights that automated scoring integrated with the recent machine translation holds great promise for consistent and resource-efficient scoring in ILSAs.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140576310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1186/s40536-024-00196-w
Gary N. Marks
In this journal, Sciffer et al. (Large-scale Assessments in Education 10:1–22, 2022), hereafter SP&M, conclude that school socioeconomic compositional (SEC) or school socioeconomic status (school-SES) effects in Australia are substantial and substantively important for research and policy. This paper demonstrates that these claims are unwarranted. Their SEC estimates are much larger than estimates from comparable studies and a metastudy. Despite plausible theoretical reasons and empirical evidence, SP&M do not consider that school academic composition is a significant predictor of student achievement independent of SEC. SEC effects are confounded by academic composition and are typically trivial when considering academic composition. The second part of this paper compares SP&M’s estimates with analysis of the same data, from the Australian National Assessments in Performance—Literacy and Numeracy (NAPLAN). In a model corresponding to SP&M analyses comprising demographics, SES, school-SES, and student-level prior achievement, the effects of school-SES are small, with standardized effects mostly less than 0.10. With the addition of academic composition measured by school-level prior achievement, school-SES effects are effectively zero. In contrast, academic composition has significant, albeit small, impacts on student achievement. Therefore, contrary to SP&M’s (2022) conclusion, school-SES effects on student achievement in NAPLAN are negligible, whereas school-level prior achievement has small effects. That is not to say that school-SES is always irrelevant, but any assessment of its importance must consider both student- and school-level prior achievement.
{"title":"No substantive effects of school socioeconomic composition on student achievement in Australia: a response to Sciffer, Perry and McConney","authors":"Gary N. Marks","doi":"10.1186/s40536-024-00196-w","DOIUrl":"https://doi.org/10.1186/s40536-024-00196-w","url":null,"abstract":"In this journal, Sciffer et al. (Large-scale Assessments in Education 10:1–22, 2022), hereafter SP&M, conclude that school socioeconomic compositional (SEC) or school socioeconomic status (school-SES) effects in Australia are substantial and substantively important for research and policy. This paper demonstrates that these claims are unwarranted. Their SEC estimates are much larger than estimates from comparable studies and a metastudy. Despite plausible theoretical reasons and empirical evidence, SP&M do not consider that school academic composition is a significant predictor of student achievement independent of SEC. SEC effects are confounded by academic composition and are typically trivial when considering academic composition. The second part of this paper compares SP&M’s estimates with analysis of the same data, from the Australian National Assessments in Performance—Literacy and Numeracy (NAPLAN). In a model corresponding to SP&M analyses comprising demographics, SES, school-SES, and student-level prior achievement, the effects of school-SES are small, with standardized effects mostly less than 0.10. With the addition of academic composition measured by school-level prior achievement, school-SES effects are effectively zero. In contrast, academic composition has significant, albeit small, impacts on student achievement. Therefore, contrary to SP&M’s (2022) conclusion, school-SES effects on student achievement in NAPLAN are negligible, whereas school-level prior achievement has small effects. That is not to say that school-SES is always irrelevant, but any assessment of its importance must consider both student- and school-level prior achievement.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140150142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-07DOI: 10.1186/s40536-024-00192-0
Francis L. Huang
The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional functions in R that extend the functionality of the WeMix (Bailey et al., 2023) package to allow for the automatic pooling of plausible values. In addition, functions for model comparisons using plausible values and the ability to export output to different formats (e.g., Word, html) are also provided.
在过去的十年中，大规模评估（LSA）在教育领域的应用日益增多，但使用 R 语言的多层次模型（MLM）对 LSA 进行分析却很有限。使用有限的一个原因可能是在 LSA 数据的多层次分析中纳入可信值和加权分析的复杂性。我们在 R 中提供了额外的函数，扩展了 WeMix（Bailey 等人，2023 年）软件包的功能，允许自动汇集可信值。此外，我们还提供了使用可信值进行模型比较的函数，以及将输出导出为不同格式（如 Word、html）的功能。
{"title":"Using plausible values when fitting multilevel models with large-scale assessment data using R","authors":"Francis L. Huang","doi":"10.1186/s40536-024-00192-0","DOIUrl":"https://doi.org/10.1186/s40536-024-00192-0","url":null,"abstract":"The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional functions in R that extend the functionality of the WeMix (Bailey et al., 2023) package to allow for the automatic pooling of plausible values. In addition, functions for model comparisons using plausible values and the ability to export output to different formats (e.g., Word, html) are also provided.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.1186/s40536-024-00195-x
Alice Bertoletti, Zbigniew Karpiński
The Covid-19 pandemic has triggered a rapid and unprecedented transformation of global educational systems. The research community has uncovered important impacts of the pandemic on education worldwide, including detrimental effects on student learning, a decline in the well-being of teachers and students, and the exacerbation of educational disparities. Within this context, the Response to Education Disruption Survey (REDS) database stands out as one of the first large-scale international surveys specifically designed to examine the disruption caused by Covid-19 in education. This database serves as an initial step towards providing a more comprehensive understanding of the worldwide effects of the pandemic on education. The relevance of this database has inspired the creation of this special issue, collecting six studies that analyse the consequences of Covid-19 using REDS data.
{"title":"Investigating the effect of COVID-19 disruption in education using REDS data","authors":"Alice Bertoletti, Zbigniew Karpiński","doi":"10.1186/s40536-024-00195-x","DOIUrl":"https://doi.org/10.1186/s40536-024-00195-x","url":null,"abstract":"The Covid-19 pandemic has triggered a rapid and unprecedented transformation of global educational systems. The research community has uncovered important impacts of the pandemic on education worldwide, including detrimental effects on student learning, a decline in the well-being of teachers and students, and the exacerbation of educational disparities. Within this context, the Response to Education Disruption Survey (REDS) database stands out as one of the first large-scale international surveys specifically designed to examine the disruption caused by Covid-19 in education. This database serves as an initial step towards providing a more comprehensive understanding of the worldwide effects of the pandemic on education. The relevance of this database has inspired the creation of this special issue, collecting six studies that analyse the consequences of Covid-19 using REDS data.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"788 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140006507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emirati children’s reading skills have consistently lagged behind global standards on international standardized tests. Given the United Arab Emirates’s Vision 2031, which aims for a world-class education system, and given the importance of Arabic literacy in preserving national identity and cultural heritage, there is an urgent need to investigate the factors that influence Arabic literacy among Emirati children. Therefore, this study, using data from the Progress in International Reading Literacy Study (PIRLS) 2016 database, aimed to examine the relationships between parents’ attitudes toward reading, early literacy activities, early literacy tasks, and Arabic literacy. Specifically, the study aimed to (1) determine the predictive value of parental attitudes toward reading for Arabic reading literacy among Emirati children; (2) examine how early literacy activities and tasks contribute to Arabic reading literacy; and (3) examine the mediating role of early literacy activities and tasks in the relationship between parental attitudes and Arabic reading literacy. The results of the study suggest that parental attitudes toward reading are an important predictor of their children’s Arabic reading literacy. Participation in early literacy activities before primary school and mastery of early literacy tasks at the beginning of primary school were both associated with reading proficiency in Arabic. Furthermore, both early literacy activities and early literacy tasks significantly mediated the relationship between parental attitudes toward reading and children’s reading proficiency in Arabic. The findings are critical for educators to adapt teaching methods, curricula, and parental involvement programs to more effectively support Arabic literacy development. The study highlights the need for an inclusive approach involving parents, educators, and policymakers to create an enabling environment for the development of Arabic literacy, which is essential for academic success and cultural preservation.
{"title":"Investigating the relationship between parental attitudes toward reading, early literacy activities, and reading literacy in Arabic among Emirati children","authors":"Yahia Alramamneh, Sumaya Saqr, Shaljan Areepattamannil","doi":"10.1186/s40536-023-00187-3","DOIUrl":"https://doi.org/10.1186/s40536-023-00187-3","url":null,"abstract":"Emirati children’s reading skills have consistently lagged behind global standards on international standardized tests. Given the United Arab Emirates’s Vision 2031, which aims for a world-class education system, and given the importance of Arabic literacy in preserving national identity and cultural heritage, there is an urgent need to investigate the factors that influence Arabic literacy among Emirati children. Therefore, this study, using data from the Progress in International Reading Literacy Study (PIRLS) 2016 database, aimed to examine the relationships between parents’ attitudes toward reading, early literacy activities, early literacy tasks, and Arabic literacy. Specifically, the study aimed to (1) determine the predictive value of parental attitudes toward reading for Arabic reading literacy among Emirati children; (2) examine how early literacy activities and tasks contribute to Arabic reading literacy; and (3) examine the mediating role of early literacy activities and tasks in the relationship between parental attitudes and Arabic reading literacy. The results of the study suggest that parental attitudes toward reading are an important predictor of their children’s Arabic reading literacy. Participation in early literacy activities before primary school and mastery of early literacy tasks at the beginning of primary school were both associated with reading proficiency in Arabic. Furthermore, both early literacy activities and early literacy tasks significantly mediated the relationship between parental attitudes toward reading and children’s reading proficiency in Arabic. The findings are critical for educators to adapt teaching methods, curricula, and parental involvement programs to more effectively support Arabic literacy development. The study highlights the need for an inclusive approach involving parents, educators, and policymakers to create an enabling environment for the development of Arabic literacy, which is essential for academic success and cultural preservation.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"15 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138508897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-11DOI: 10.1186/s40536-022-00125-9
Glassow, Leah Natasha, Jerrim, John
Unequal access to qualified teachers for children of different socioeconomic status—also known as inequitable teacher sorting—has been increasingly put forth as one potential factor contributing to the socioeconomic achievement gap. Despite this, few studies have investigated cross-national differences in teacher sorting, and none have examined it within-countries over time. International large-scale assessments in education are uniquely positioned to answer such questions due to their longitudinal nature at the system level. This study uses six waves of data from the Trends in International Mathematics and Science Study (TIMSS) from 1999 to 2019 for 32 education systems. We compare differences in grade 8 mathematics teacher qualifications for each country at each time point, across top and bottom groups on the student socioeconomic spectrum. Results show that on the whole many countries display negligible gaps in access to teacher quality, with some key exceptions. With respect to inequity in novice teacher sorting, the problem is most prevalent in low- and middle- income education systems (i.e. in Turkey, Morocco, Tunisia and Indonesia). Inequity in sorting based on mathematics education is less common, with no clear pattern in regards to level of economic development (i.e. in Chile, Australia, New Zealand, and Chinese Taipei). Socio-economic inequality in teacher sorting has also remained broadly stable over time. Based on experience and mathematics education, less than a handful of systems show systematic upward trends in teacher sorting inequity (i.e. in Chile, Morocco, Singapore, and New Zealand). Given the increasing focus on inequity in access to teacher competence, these results have economic and policy implications for tackling the socioeconomic achievement gap.
{"title":"Is inequitable teacher sorting on the rise? Cross-national evidence from 20 years of TIMSS","authors":"Glassow, Leah Natasha, Jerrim, John","doi":"10.1186/s40536-022-00125-9","DOIUrl":"https://doi.org/10.1186/s40536-022-00125-9","url":null,"abstract":"Unequal access to qualified teachers for children of different socioeconomic status—also known as inequitable teacher sorting—has been increasingly put forth as one potential factor contributing to the socioeconomic achievement gap. Despite this, few studies have investigated cross-national differences in teacher sorting, and none have examined it within-countries over time. International large-scale assessments in education are uniquely positioned to answer such questions due to their longitudinal nature at the system level. This study uses six waves of data from the Trends in International Mathematics and Science Study (TIMSS) from 1999 to 2019 for 32 education systems. We compare differences in grade 8 mathematics teacher qualifications for each country at each time point, across top and bottom groups on the student socioeconomic spectrum. Results show that on the whole many countries display negligible gaps in access to teacher quality, with some key exceptions. With respect to inequity in novice teacher sorting, the problem is most prevalent in low- and middle- income education systems (i.e. in Turkey, Morocco, Tunisia and Indonesia). Inequity in sorting based on mathematics education is less common, with no clear pattern in regards to level of economic development (i.e. in Chile, Australia, New Zealand, and Chinese Taipei). Socio-economic inequality in teacher sorting has also remained broadly stable over time. Based on experience and mathematics education, less than a handful of systems show systematic upward trends in teacher sorting inequity (i.e. in Chile, Morocco, Singapore, and New Zealand). Given the increasing focus on inequity in access to teacher competence, these results have economic and policy implications for tackling the socioeconomic achievement gap.","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140884679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1186/S40327-019-0068-Y
S. Oliver
{"title":"Communication and trust: rethinking the way construction industry professionals and software vendors utilise computer communication mediums","authors":"S. Oliver","doi":"10.1186/S40327-019-0068-Y","DOIUrl":"https://doi.org/10.1186/S40327-019-0068-Y","url":null,"abstract":"","PeriodicalId":37417,"journal":{"name":"Visualization in Engineering","volume":"7 1","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/S40327-019-0068-Y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42131087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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