References of "Keller, Ulrich 50002080"
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See detailThe Impact of the COVID-19 Pandemic on the Luxembourgish Education System: Differences between students based on background characteristics in elementary and secondary school
Fischbach, Antoine UL; Colling, Joanne UL; Levy, Jessica UL et al

Scientific Conference (2021, November)

Policy responses to the COVID-19 pandemic (e.g., school closure, home-schooling) have affected students at various stages of education all over the world and were found to increase inequalities in ... [more ▼]

Policy responses to the COVID-19 pandemic (e.g., school closure, home-schooling) have affected students at various stages of education all over the world and were found to increase inequalities in academic achievement (OECD, 2021). The present study is based on fully representative large-scale data from the Luxembourg School Monitoring Programme (Épreuves Standardisées; ÉpStan; LUCET, 2021). The ÉpStan are assessing key competencies of primary and secondary school students in different subjects (e.g., German, French and Math). To allow a fair performance comparison, socio-economic and socio-cultural backgrounds of students (e.g., gender, migration and language background) are systematically taken into consideration. The ÉpStan 2020 entail data from approximatively 25.000 students from five different grades (elementary and secondary school), from 15.000 parents (elementary school) and comparative data from 160.000 students from previous cohorts, thus providing key empirical findings on the pandemic’s impact on the Luxembourgish education system. In the present contribution, we analyze a) how the results of standardized achievement tests compare to previous cohorts and under consideration of students’ socio-economical and socio-cultural background, as well as b) how parents and students perceived home-schooling with regard to aspects such as coping, technical equipment, motivation or contact to teachers. First results indicate that in Grades 1, 5, 7 and 9, standardized achievement scores were generally stable in comparison to previous years. However, in Grade 3, students’ competency scores in German (primary language of instruction in elementary school) listening comprehension worsened substantially. Furthermore, third graders from socio-economically disadvantaged households and/or students that do not speak Luxembourgish/German at home did worse in German reading comprehension than their peers from socio-economically advantaged households and/or speaking Luxembourgish/German at home. Concerning the perception of home-schooling, students coped rather well with the situation, with German being a bit more challenging in primary school and math in secondary school. Findings concerning motivation and enjoyment of home-schooling were mixed, with primary school students’ motivation being comparably to the regular school setting but approximately half of the secondary school students being less motivated than in the regular school setting. Furthermore, all households seem to have been well equipped, with the situation being slightly more favorable in socio-economically advantaged households. For the majority of students, the contact with teachers was frequent, with teachers having adapted their type of support to the needs of their students (e.g., more personal contact towards students from socio-economically disadvantaged households). To conclude, it can be said that no systematic negative trend has been identified in students’ achievement scores. Only German listening comprehension in Grade 3 has worsened substantially and these skills should therefore be fostered as early as possible. Overall, students coped rather well with home-schooling without, however, particularly enjoying it. While students entering the pandemic with favorable background characteristics (e.g., higher socio-economic status, speaking a language of instruction at home) managed better both regarding competencies and perception of home-schooling, students with less favorable background characteristics have received more differentiated support. These findings underline that already existing inequalities in the Luxembourgish school system have in parts been intensified by the pandemic. References LUCET. (2021). Épreuves Standardisées (ÉpStan). https://epstan.lu OECD. (2021). The State of School Education: One Year into the COVID Pandemic. OECD Publishing. https://doi.org/10.1787/201dde84-en [less ▲]

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See detailLong-Term Effects of Retention in Grade 8 in Luxembourg
Klapproth, Florian; Keller, Ulrich UL; Fischbach, Antoine UL

Scientific Conference (2021, September 10)

Meta-analyses (Hattie, 2009; Jimerson, 2001) have suggested that grade retention rarely has positive effects and more often negative effects on students’ performance and psycho-emotional well-being. The ... [more ▼]

Meta-analyses (Hattie, 2009; Jimerson, 2001) have suggested that grade retention rarely has positive effects and more often negative effects on students’ performance and psycho-emotional well-being. The occurrence of negative effects may be due to the absence of new learning experiences (Pagani, Tremblay, Vitaro, Boulerice & McDuff, 2001). However, in the short term, positive effects of grade retention are quite likely to occur (Klapproth, Schaltz, Brunner, Keller, Fischbach, Ugen & Martin, 2016). In Luxembourg, more than half of the students repeat at least one grade within their entire school career (Klapproth & Schaltz, 2015). Since grade retention is applied so frequently, the aim of the current study was to examine long-term effects of grade retention, and particularly retention in grade 8. The data used in this study were drawn from 2,835 Luxembourgish students who completed primary education (grade 6) and began secondary education (grade 7) in the 2008-2009 school year. We conducted propensity-score matching to select retained and promoted students with comparable characteristics. We used the “same age-cohort, same grade, different times of measurement” approach for comparisons (Klapproth et al., 2016). The dependent variables were the school marks in the main subjects (German, French, and mathematics) in grades 10, 11, and 12, which can vary between 0 and 60 (with higher values indicating better achievement, and values below 30 indicating insufficient achievement). Our results showed that grade 8 repeaters obtain significantly lower school marks in grades 10 to 12 as compared to matched non-repeaters, with most negative effects appearing for mathematics and French (as opposed to German) and with negative effects strengthening significantly with time. These results seem to confirm results of previous meta-analyses on longer-term effects of grade retention, seemingly suggesting that grade retention is no effective means to tackle low student achievement. [less ▲]

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See detailLong-term effects of retention in grade 8 in Luxembourg
Klapproth, Florian; Keller, Ulrich UL; Fischbach, Antoine UL

Scientific Conference (2021, August 26)

Meta-analyses have suggested that grade retention rarely has positive effects and more often negative effects on students’ performance and psycho-emotional well-being. The occurrence of negative effects ... [more ▼]

Meta-analyses have suggested that grade retention rarely has positive effects and more often negative effects on students’ performance and psycho-emotional well-being. The occurrence of negative effects may be due to the absence of new learning experiences. However, in the short term, positive effects of grade retention are quite likely to occur. In Luxembourg, more than half of the students repeat at least one grade within their entire school career. Since grade retention is applied quite frequently, the aim of the current study was to examine long-term effects of grade retention. A representative sample of 2,835 Luxembourgish 8th grade students was used for this study, and propensity score matching was applied to select a control group of promoted students who were similar to the retained students on a variety of characteristics. Furthermore, a type of comparison was used by which the outcome variables of the retained and promoted students were compared at different times while the grade- and age-cohort were held equal between groups. With respect to school marks as an indicator of students’ academic achievement, this study showed that grade 8 retention lowered repeaters’ school marks, on average, in grades 10 to 13, as compared to matched non-repeaters. [less ▲]

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See detailTackling educational inequalities using school effectiveness measures
Levy, Jessica UL; Mussack, Dominic UL; Brunner, Martin et al

Scientific Conference (2020, November 11)

Detailed reference viewed: 81 (12 UL)
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See detailIs there a bilingual advantage in mathematics?
Martini, Sophie Frédérique UL; Keller, Ulrich UL; Ugen, Sonja UL

Scientific Conference (2020, November)

Detailed reference viewed: 29 (3 UL)
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See detailSelf-concept, interest, and achievement within and across math and verbal domains in first- and third-graders
van der Westhuizen, Lindie UL; Arens, A. Katrin; Keller, Ulrich UL et al

Scientific Conference (2020, April)

The generalized internal/external frame-of-reference (G)I/E model explains the formation of domain-specific motivational-affective constructs through social and dimensional comparisons. We examined the ... [more ▼]

The generalized internal/external frame-of-reference (G)I/E model explains the formation of domain-specific motivational-affective constructs through social and dimensional comparisons. We examined the associations between verbal and math achievement and corresponding domain-specific academic self-concepts (ASCs) and interests for first-graders and third-graders (N=21,192). Positive achievement-self-concept and achievement-interest relations were found within matching-domains in both grades, while negative cross-domains achievement-self-concept and achievement-interest relations were only found for third-graders. These findings suggest that while the formation of domain-specific ASCs and interests seem to rely on social and dimensional comparisons for third-graders, only social comparisons seem to be in operation for first-graders. Gender and cohort invariance was established in both grade levels. Findings are discussed within the framework of ASC differentiation and dimensional comparison theory. [less ▲]

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See detailLangzeiteffekte von Klassenwiederholungen in der Sekundarstufe
Klapproth, Florian; Keller, Ulrich UL; Fischbach, Antoine UL

Scientific Conference (2020, March)

Detailed reference viewed: 41 (5 UL)
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See detailContrasting Classical and Machine Learning Approaches in the Estimation of Value-Added Scores in Large-Scale Educational Data
Levy, Jessica UL; Mussack, Dominic UL; Brunner, Martin et al

in Frontiers in Psychology (2020), 11

There is no consensus on which statistical model estimates school value-added (VA) most accurately. To date, the two most common statistical models used for the calculation of VA scores are two classical ... [more ▼]

There is no consensus on which statistical model estimates school value-added (VA) most accurately. To date, the two most common statistical models used for the calculation of VA scores are two classical methods: linear regression and multilevel models. These models have the advantage of being relatively transparent and thus understandable for most researchers and practitioners. However, these statistical models are bound to certain assumptions (e.g., linearity) that might limit their prediction accuracy. Machine learning methods, which have yielded spectacular results in numerous fields, may be a valuable alternative to these classical models. Although big data is not new in general, it is relatively new in the realm of social sciences and education. New types of data require new data analytical approaches. Such techniques have already evolved in fields with a long tradition in crunching big data (e.g., gene technology). The objective of the present paper is to competently apply these “imported” techniques to education data, more precisely VA scores, and assess when and how they can extend or replace the classical psychometrics toolbox. The different models include linear and non-linear methods and extend classical models with the most commonly used machine learning methods (i.e., random forest, neural networks, support vector machines, and boosting). We used representative data of 3,026 students in 153 schools who took part in the standardized achievement tests of the Luxembourg School Monitoring Program in grades 1 and 3. Multilevel models outperformed classical linear and polynomial regressions, as well as different machine learning models. However, it could be observed that across all schools, school VA scores from different model types correlated highly. Yet, the percentage of disagreements as compared to multilevel models was not trivial and real-life implications for individual schools may still be dramatic depending on the model type used. Implications of these results and possible ethical concerns regarding the use of machine learning methods for decision-making in education are discussed. [less ▲]

Detailed reference viewed: 89 (11 UL)
See detailDimensional and Social Comparison Effects on Domain-Specific Academic Self-Concepts and Interests with First- and Third-Grade Students
van der Westhuizen, Lindie UL; Arens, Katrin; Keller, Ulrich UL et al

Scientific Conference (2019, November 06)

Academic self-concepts (ASCs) are self-perceptions of one’s own academic abilities. The internal/external frame of reference (I/E) model (Marsh, 1986) explains the formation of domain-specific ASCs ... [more ▼]

Academic self-concepts (ASCs) are self-perceptions of one’s own academic abilities. The internal/external frame of reference (I/E) model (Marsh, 1986) explains the formation of domain-specific ASCs through a combination of social (i.e. comparing one’s achievement in one domain with the achievement of others in the same domain) and dimensional (i.e. comparing one’s achievement in one domain with one’s achievement in another domain) comparisons. This results into positive achievement-self-concept relations within the math and verbal domains, but into negative achievement-self-concept relations across these domains. The generalized internal/external frame of reference (GI/E) model (Möller, Müller-Kalthoff, Helm, Nagy, & Marsh, 2015) extends the I/E model to the formation of other domain-specific academic self-beliefs such as interest. Research on the validity of the (G)I/E model for elementary school children is limited, especially for first-graders. This study examined the associations between verbal and math achievement and corresponding domain-specific self-concepts and interests for first-graders and third-graders. Two fully representative Luxembourgish first-grader cohorts and two fully representative third-graders cohorts (N=21,192) were used. The analyses were based on structural equation modeling. The findings fully supported the (G)I/E model for third-graders: Achievement was positively related to self-concept and interest within matching domains. Negative relations were found between achievement and self-concept and between achievement and interest across domains. For first-graders, achievement was positively related to self-concept and interest within matching domains. However, the majority of cross-domain relations were non-significant, except for the negative path between math achievement and verbal interest. Hence, while the formation of domain-specific ASCs and interests seem to rely on social and dimensional comparisons for third-graders, only social comparisons seem to be in operation for first-graders. Gender and cohort invariance was established for both grade levels. The findings are discussed within the framework of ASC differentiation and dimensional comparison theory applied to elementary school students. [less ▲]

Detailed reference viewed: 133 (7 UL)
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See detailSimilarities and differences of value-added scores from models with different covariates: A cluster analysis
Levy, Jessica UL; Brunner, Martin; Keller, Ulrich UL et al

Scientific Conference (2019, November 06)

Detailed reference viewed: 82 (6 UL)
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See detailNeed for Cognition across school tracks: The importance of learning environments
Colling, Joanne UL; Wollschläger, Rachel UL; Keller, Ulrich UL et al

Scientific Conference (2019, November 06)

Detailed reference viewed: 103 (9 UL)
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See detailValue-added models: To what extent do estimates of school effectiveness depend on the selection of covariates?
Levy, Jessica UL; Brunner, Martin; Keller, Ulrich UL et al

Scientific Conference (2019, September)

Detailed reference viewed: 90 (6 UL)
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See detailValue-added modeling in primary school: What covariates to include?
Levy, Jessica UL; Brunner, Martin; Keller, Ulrich UL et al

Scientific Conference (2019, August)

Detailed reference viewed: 130 (9 UL)
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See detailMethodological Issues in Value-Added Modeling: An International Review from 26 Countries
Levy, Jessica UL; Brunner, Martin; Keller, Ulrich UL et al

in Educational Assessment, Evaluation and Accountability (2019), 31(3), 257-287

Value-added (VA) modeling can be used to quantify teacher and school effectiveness by estimating the effect of pedagogical actions on students’ achievement. It is gaining increasing importance in ... [more ▼]

Value-added (VA) modeling can be used to quantify teacher and school effectiveness by estimating the effect of pedagogical actions on students’ achievement. It is gaining increasing importance in educational evaluation, teacher accountability, and high-stakes decisions. We analyzed 370 empirical studies on VA modeling, focusing on modeling and methodological issues to identify key factors for improvement. The studies stemmed from 26 countries (68% from the USA). Most studies applied linear regression or multilevel models. Most studies (i.e., 85%) included prior achievement as a covariate, but only 2% included noncognitive predictors of achievement (e.g., personality or affective student variables). Fifty-five percent of the studies did not apply statistical adjustments (e.g., shrinkage) to increase precision in effectiveness estimates, and 88% included no model diagnostics. We conclude that research on VA modeling can be significantly enhanced regarding the inclusion of covariates, model adjustment and diagnostics, and the clarity and transparency of reporting. [less ▲]

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See detailThe use of value-added models for the identification of schools that perform “against the odds”
Levy, Jessica UL; Brunner, Martin; Keller, Ulrich UL et al

Poster (2019, July)

Value-added (VA) modeling aims to quantify the effect of pedagogical actions on students’ achievement, independent of students’ backgrounds. VA modeling is primarily used for accountability and high ... [more ▼]

Value-added (VA) modeling aims to quantify the effect of pedagogical actions on students’ achievement, independent of students’ backgrounds. VA modeling is primarily used for accountability and high-stakes decisions. To date, there seems to be no consensus concerning the calculation of VA models. Our study aims to systematically analyze and compare different school VA models by using longitudinal large-scale data emerging from the Luxembourg School Monitoring Programme. Regarding the model covariates, first findings indicate the importance of language (i.e., language(s) spoken at home and prior language achievement) in VA models with either language or math achievement as a dependent variable, with the highest amount of explained variance in VA models for language. Concerning the congruence of different VA approaches, we found high correlations between school VA scores from the different models, but also high ranges between VA scores for single schools. We conclude that VA models should be used with caution and with awareness of the differences that may arise from methodological choices. Finally, we discuss the idea that VA models could be used for the identification of schools that perform “against the odds”, especially for those schools that have positive VA scores over several years. [less ▲]

Detailed reference viewed: 86 (6 UL)