Large-Scale Assessments in Education最新文献

{"title":"Supportive climates and science achievement in the Nordic countries: lessons learned from the 2015 PISA study","authors":"Anubha Rohatgi, Ove E. Hatlevik, Julius K. Björnsson","doi":"10.1186/s40536-022-00123-x","DOIUrl":"https://doi.org/10.1186/s40536-022-00123-x","url":null,"abstract":"<p>Teacher-student interactions are crucial in understanding the role of a supportive climate in instructional practices. The present study investigates the perceptions of 15-year-old Nordic students regarding four aspects of their science class: teacher support, fairness, feedback, and class discipline. Multilevel modelling analysis is used to examine the extent to which a perceived supportive climate can explain variation in the Nordic students’ science achievements. Overall, the main findings based on The Programme for International Student Assessment (PISA) 2015 data from Denmark, Finland, Iceland, Norway, and Sweden indicate that at the student level, perceived feedback from teachers and students perceiving their teachers as fair explains significant variations in science achievement. The study provides practical and theoretical implications about the importance of strong teacher-student relationships in comprehending the concept of a supportive climate.</p>","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"20 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496854","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}

{"title":"Does the material well-being at schools successfully compensate for socioeconomic disadvantages? Analysis of resilient schools in Sweden","authors":"Deborah Elin Siebecke, Maria Jarl","doi":"10.1186/s40536-022-00130-y","DOIUrl":"https://doi.org/10.1186/s40536-022-00130-y","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>A variety of studies point to a deterioration of educational equity in Sweden and increasing school segregation with respect to achievement and socioeconomic composition. Some schools are resilient to socioeconomic disadvantages in their student body and demonstrate high levels of achievement. However, little attention has been given to these resilient schools. Material well-being, as one important dimension of student well-being, comprises the student’s home background and school resources. The relationship between home background and achievement is well-established but less literature includes school-level factors of material well-being. In comparing the material well-being at resilient, non-resilient, and more advantaged schools, this study aims at detecting possible patterns that may provide crucial information as to why some schools succeed better in compensating for disadvantages.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Using Swedish data from the Programme for International Student Assessment (PISA) from 2000 to 2018, the shares of resilient, non-resilient, and more advantaged school groups with different achievement levels were identified by using aggregated achievement and socioeconomic background measures. Making use of a well-being framework specifically designed for PISA data, the school groups were compared regarding their material well-being as measured by the perceived shortage of material resources and teachers, the percentage of teachers fully certified, the availability of computers, and extracurricular activities. This comparison of school groups was computed using the nonparametric Kruskal-Wallis test and a Bonferroni-adjusted pairwise comparison.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The shares of resilient schools decreased considerably from 14% in 2000 to 3% in 2015. Yet, the comparison of the material well-being at resilient and other school groups led to mostly non-significant results. Overall, disadvantaged schools reported higher teacher shortages than advantaged schools, which indicates the need for a more compensatory allocation of (human) resources.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>The study concluded that the landscape of resilient schools is under continuous change. As no patterns of significant differences between resilient and other school groups were found, the study shows no indication that the material well-being at school compensates for disadvantages in a school’s student body. The findings call for further research regarding changes in the presence of resilient schools and their possible relationship with school material well-being.</p>","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"20 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496853","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}

{"title":"Evaluating the effects of analytical decisions in large-scale assessments: analyzing PISA mathematics 2003-2012","authors":"Jörg-Henrik Heine, Alexander Robitzsch","doi":"10.1186/s40536-022-00129-5","DOIUrl":"https://doi.org/10.1186/s40536-022-00129-5","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Research question</h3><p>This paper examines the overarching question of to what extent different analytic choices may influence the inference about country-specific cross-sectional and trend estimates in international large-scale assessments. We take data from the assessment of PISA mathematics proficiency from the four rounds from 2003 to 2012 as a case study.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>In particular, four key methodological factors are considered as analytical choices in the rescaling and analysis of the data: (1) The selection of country sub-samples for item calibration differing at three factor levels. (2) The item sample refering to two sets of mathematics items used within PISA. (3) The estimation method used for item calibration: marginal maximum likelihood estimation method as implemented in R package TAM or an pairwise row averaging approach as implemented in the R package pairwise. (4) The type of linking method: concurrent calibration or separate calibration with successive chain linking.</p><h3 data-test=\"abstract-sub-heading\">Findings</h3><p>It turned out that analytical decisions for scaling did affect the PISA outcomes. The factors of choosing different calibration samples, estimation method and linking method tend to show only small effects on the country-specific cross-sectional and trend estimates. However, the selection of different link items seems to have a decisive influence on country ranking and development trends between and within countries.</p>","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"20 5","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496852","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}

{"title":"Do immigrants experience labor market mismatch? New evidence from the US PIAAC","authors":"Margarita Pivovarova, Jeanne M. Powers","doi":"10.1186/s40536-022-00127-7","DOIUrl":"https://doi.org/10.1186/s40536-022-00127-7","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>One way of evaluating immigrants’ labor market outcomes is to assess the extent to which immigrants are able to enter into jobs that are commensurate with their education and experience. An imperfect alignment between workers’ educational qualifications and these required for their current job, or education-job mismatch, has implications for both the broader economy and individual workers. In this study, we investigate the factors associated with education-job mismatches among US workers by immigrant generation.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>We analyzed the data from the US sample of the Program for the International Assessment of Adult Competencies (PIAAC) 2012/2014. Our analytic sample included 4022 employed (full and part-time) individuals between the ages of 20–65 years. We documented the distribution of education-job mismatches across selected independent variables and estimated the relationship between the individual characteristics of workers such as race, gender, presence of children, location, time in the country and knowledge of English for first-generation immigrant workers, and education-job mismatch using multinomial logistic regressions for the full sample and for the sample of first- and second-generation workers.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>We found that on average, immigrant workers in the US labor market were more likely to hold jobs which required less education that they had (being overmatched for the job), with first-generation workers being overmatched more frequently than second-generation workers. The probability of being overmatched for immigrant workers declines with the length of stay, and workers who are proficient in English are less likely to be overmatched. Our results also suggest that there may be labor market disadvantages to immigrant status that persist beyond the first-generation.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>Previous research demonstrated that over-education depresses wages and lowers workers’ standards of living and their abilities to accumulate wealth. Our findings confirm that this dynamic may be particularly acute for first- and second-generation workers who are finding it difficult to become fully integrated into US labor markets, even though the factors behind the mismatch differs between the two immigrant generations.</p>","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"20 6","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496851","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}

{"title":"The influence of ICT use and related attitudes on students’ math and science performance: multilevel analyses of the last decade’s PISA surveys","authors":"Matthew Courtney, M. Karakus, Zara Ersozlu, K. Nurumov","doi":"10.1186/s40536-022-00128-6","DOIUrl":"https://doi.org/10.1186/s40536-022-00128-6","url":null,"abstract":"","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"35 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65693035","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}

{"title":"Practical significance of item misfit and its manifestations in constructs assessed in large-scale studies","authors":"Katharina Fährmann, Carmen Köhler, J. Hartig, Jörg-Henrik Heine","doi":"10.1186/s40536-022-00124-w","DOIUrl":"https://doi.org/10.1186/s40536-022-00124-w","url":null,"abstract":"","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"10 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65692977","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}

{"title":"A primer on continuous-time modeling in educational research: an exemplary application of a continuous-time latent curve model with structured residuals (CT-LCM-SR) to PISA Data","authors":"Julian F. Lohmann, Steffen Zitzmann, Manuel C. Voelkle, Martin Hecht","doi":"10.1186/s40536-022-00126-8","DOIUrl":"https://doi.org/10.1186/s40536-022-00126-8","url":null,"abstract":"<p>One major challenge of longitudinal data analysis is to find an appropriate statistical model that corresponds to the theory of change and the research questions at hand. In the present article, we argue that <i>continuous-time models</i> are well suited to study the continuously developing constructs of primary interest in the education sciences and outline key advantages of using this type of model. Furthermore, we propose the <i>continuous-time latent curve model with structured residuals</i> (CT-LCM-SR) as a suitable model for many research questions in the education sciences. The CT-LCM-SR combines growth and dynamic modeling and thus provides descriptions of both trends and process dynamics. We illustrate the application of the CT-LCM-SR with data from PISA reading literacy assessment of 2000 to 2018 and provide a tutorial and annotated code for setting up the CT-LCM-SR model.</p>","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"20 9","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496850","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}

{"title":"Generating group-level scores under response accuracy-time conditional dependence","authors":"Hyo Jeong Shin, Paul A. Jewsbury, Peter W. van Rijn","doi":"10.1186/s40536-022-00122-y","DOIUrl":"https://doi.org/10.1186/s40536-022-00122-y","url":null,"abstract":"<p>The present paper investigates and examines the conditional dependencies between cognitive responses (RA; Response Accuracy) and process data, in particular, response times (RT) in large-scale educational assessments. Using two prominent large-scale assessments, NAEP and PISA, we examined the RA-RT conditional dependencies within each item in the measurement model and the structural model. Evidence for RA-RT conditional dependencies was observed in data from both programs, presenting a challenge in incorporating RT to the current operational models in NAEP and PISA that do not account for RA-RT conditional dependencies. However, inclusion of RT in the model had a relatively large contribution to improving the measurement of ability (residual variance decrease of 11% in NAEP and 18% in PISA), in contrast to relatively modest difference in parameter estimation from neglecting the conditional dependencies (e.g., estimated difference on residual variance of 1% in both NAEP and PISA). We conclude that the benefits of incorporating RT in the operational models for large-scale educational assessments may outweigh the costs.</p>","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"20 10","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496849","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}

{"title":"Equity in mathematics education in Hong Kong: evidence from TIMSS 2011 to 2019","authors":"Xue-Lan Qiu, F. Leung","doi":"10.1186/s40536-022-00121-z","DOIUrl":"https://doi.org/10.1186/s40536-022-00121-z","url":null,"abstract":"","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"10 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65692960","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}

{"title":"Equal opportunities for all? Analyzing within-country variation in school effectiveness","authors":"Isa Steinmann, R. Olsen","doi":"10.1186/s40536-022-00120-0","DOIUrl":"https://doi.org/10.1186/s40536-022-00120-0","url":null,"abstract":"","PeriodicalId":37009,"journal":{"name":"Large-Scale Assessments in Education","volume":"10 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65692646","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}