References of "Fischbach, Antoine 50001789"
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See detailKnowledge assessment with concept maps: Opportunities and challenges
Rohles, Björn UL; Koenig, Vincent UL; Fischbach, Antoine UL et al

Presentation (2021, July)

21st-century digital society poses tremendous challenges for education and assessment. Learners have to understand the complex relations between diverse topics and learn how to learn their entire lives ... [more ▼]

21st-century digital society poses tremendous challenges for education and assessment. Learners have to understand the complex relations between diverse topics and learn how to learn their entire lives. Concept mapping is a promising approach to address these issues. It is a method that uses concepts connected by labeled links to visualize a semantic network of knowledge. Concept mapping is predestined for a digital approach because it allows for easy interactive editing, innovative test items, and incorporation of multimodal information. Concept mapping is available for summative and formative assessment and, thus, provides the opportunity to become a vital part of modern education. The biggest advantage of concept mapping (i.e., a comprehensive and yet comprehensible visualization of complex relations) also represents the biggest challenge when it comes to assessment with - and scoring of - concept maps. The first challenge is the enormous amount of indicators used for scoring concept maps in assessment. A second challenge comes from the fact that educators using concept mapping in their assessment have to understand and interpret the indicators that are used in scoring concept maps. This presentation reports on a Ph.D. project that investigates digital concept mapping in the context of knowledge assessment from a user experience perspective. The results are based on, first, a comprehensive international systematic literature review on concept map scoring, and second, three empirical studies covering the needs and experiences of learners and educators in concept mapping. It presents key findings from the iterative user experience design of a concept mapping tool as part of the online assessment platform OASYS, an overview of indicators used in concept map scoring, and research opportunities in knowledge assessment with concept maps. Finally, it stresses the value that user experience design brings to knowledge assessment with concept maps. [less ▲]

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See detailLernstörungen im multilingualen Kontext: Diagnose und Hilfestellungen.
Ugen, Sonja UL; Schiltz, Christine UL; Fischbach, Antoine UL et al

Book published by Melusina Press (2021)

Um Kinder mit einer Lernstörung durch möglichst angepasste Hilfsmaßnahmen unterstützen zu können, ist eine umfassende Diagnostik maßgeblich. Die Diagnostik von Lernstörungen stellt vor allem in ... [more ▼]

Um Kinder mit einer Lernstörung durch möglichst angepasste Hilfsmaßnahmen unterstützen zu können, ist eine umfassende Diagnostik maßgeblich. Die Diagnostik von Lernstörungen stellt vor allem in multilingualen Kontexten - wie in Luxemburg - eine Herausforderung dar. Auch werden derzeit vorwiegend im Ausland entwickelte diagnostische Tests durchgeführt, welche die luxemburgischen Besonderheiten, wie etwa das Erlernen der schriftsprachlichen und mathematischen Kompetenzen in einer Zweit- oder Drittsprache, nicht berücksichtigen. Ausgehend vom aktuellen Forschungs- und Wissensstand wird ein vertieftes Verständnis im Hinblick auf Lese- und Rechtschreibstörungen und Rechenstörungen dargelegt. Darauf aufbauend werden diagnostische Vorgehensweisen sowie pädagogische Hilfsmaßnahmen mithilfe von Erfahrungswerten praktizierender Fachkräfte aus dem luxemburgischen Förderbereich vorgestellt. [less ▲]

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See detailEinleitung: Lernstörungen im multilingualen Kontext – Eine Herausforderung
Ugen, Sonja UL; Schiltz, Christine UL; Fischbach, Antoine UL et al

in Ugen, Sonja; Schiltz, Christine; Fischbach, Antoine (Eds.) et al Lernstörungen im multilingualen Kontext: Diagnose und Hilfestellungen (2021)

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See detailExperimenter Effects in Children Using the Smileyometer Scale
Lehnert, Florence Kristin UL; Lallemand, Carine UL; Fischbach, Antoine UL et al

Scientific Conference (2020, November 19)

Researchers in the social sciences like human-computer interaction face novel challenges concerning the development of methods and tools for evaluating interactive technology with children. One of these ... [more ▼]

Researchers in the social sciences like human-computer interaction face novel challenges concerning the development of methods and tools for evaluating interactive technology with children. One of these challenges is related to the validity and reliability of user experience measurement tools. Scale designs, like the Smileyometer, have been proven to contain biases such as the tendency for children to rate almost every technology as great. This explorative paper discusses a possible effect of two experimenter styles on the distribution of 6-8 years old pupils' ratings (N= 73) to the Smileyometer. We administered the scale before and after a tablet-based assessment in two schools. Experimenter 1 employed a child-directed speech compared to a monotone speech of Experimenter 2. While brilliant (5 out of 5) was the most frequent answer option in all conditions, the mean scores were higher and associated with a lower variability across both conditions for Experimenter 2. We discuss a possible experimenter effect in the Smileyometer and implications for evaluating children’s user experiences. [less ▲]

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See detailInequalities in the Luxembourgish Educational System: Effects of Language Proficiency on Math Performance Among Different Generations of Immigrant Students
Krämer, Charlotte UL; Rivas, Salvador UL; Reichel, Yanica UL et al

Poster (2020, November 12)

Research indicates students with immigrant background are disadvantaged in educational systems of the host country (e.g., OECD, 2018). In Luxembourg, roughly half of the school population has an immigrant ... [more ▼]

Research indicates students with immigrant background are disadvantaged in educational systems of the host country (e.g., OECD, 2018). In Luxembourg, roughly half of the school population has an immigrant background (Lenz & Heinz, 2018), and several studies indicate these students are considerably disadvantaged in terms of educational achievement levels (Hadjar et al., 2015, 2018). Lower achievement may be partly due to difficulties related to displacement and settling of 1st generation immigrant students. Second and later generation students may however also experience disadvantages as they speak languages at home that are different from the two main languages of instruction (i.e., German and French), and their parents may be less familiar with the educational system and less able to provide support for their children (Alba & Foner, 2016). This may explain why educational inequalities persist; however little is known about the influence of language proficiency of different generations of immigrant students on their performance in other school subjects. Therefore, our poster focuses on the effect of generation after controlling for the effect of language on math competency. Using data from the Luxembourg School Monitoring Programme (Épreuves Standardisées) for the 2016 cohort of 9th grade students in the two main tracks of secondary school (n=4,339), we conduct regression analysis to investigate to what extent language proficiency in German and French and generational status have an impact on math performance. Data indicates that language proficiency in both German and French explains a significant proportion of variance in math performance. In addition, there is a generation effect, whereby 3rd and later generation immigrant students achieve a higher level of math competency than students of the 1st or 2nd generation. Results will be discussed in terms of social mobility and educational inequality. [less ▲]

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See detailHow do pupils experience Technology-Based Assessments? Implications for methodological approaches to measuring the User Experience based on two case studies in France and Luxembourg
Lehnert, Florence Kristin UL; Lallemand, Carine UL; Fischbach, Antoine UL et al

Scientific Conference (2020, November 12)

Technology-based assessments (TBAs) are widely used in the education field to examine whether the learning goals were achieved. To design fair and child-friendly TBAs that enable pupils to perform at ... [more ▼]

Technology-based assessments (TBAs) are widely used in the education field to examine whether the learning goals were achieved. To design fair and child-friendly TBAs that enable pupils to perform at their best (i.a. independent of individual differences in computer literacy), we must ensure reliable and valid data collection. By reducing Human-Computer Interaction issues, we provide the best possible assessment conditions and user experience (UX) with the TBA and reduce educational inequalities. Good UX is thus a prerequisite for better data validity. Building on a recent case study, we investigated how pupils perform TBAs in real-life settings. We addressed the context-dependent factors resulting from the observations that ultimately influence the UX. The first case study was conducted with pupils age 6 to 7 in three elementary schools in France (n=61) in collaboration with la direction de l’évaluation, de la prospective et de la performance (DEPP). The second case study was done with pupils age 12 to 16 in four secondary schools in Luxembourg (n=104) in collaboration with the Luxembourg Centre for Educational Testing (LUCET). This exploratory study focused on the collection of various qualitative datasets to identify factors that influence the interaction with the TBA. We also discuss the importance of teachers’ moderation style and mere system-related characteristics, such as audio protocols of the assessment data. This study contribution comprises design recommendations and implications for methodological approaches to measuring pupils’ user experience during TBAs. [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)

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See detailThe development and validation of a short conscientiousness questionnaire for large-scale educational assessment
van der Westhuizen, Lindie UL; Franzen, Patrick UL; Arens, A. Katrin et al

Scientific Conference (2020, July)

Conscientiousness and its subfacets are related to multiple learning-related outcomes. MacCann, Duckworth and Roberts (2009) developed a questionnaire measuring seven subfacets of conscientiousness with ... [more ▼]

Conscientiousness and its subfacets are related to multiple learning-related outcomes. MacCann, Duckworth and Roberts (2009) developed a questionnaire measuring seven subfacets of conscientiousness with 59 items. However, the resources required to complete such long scales often renders it unsuitable for large-scale educational assessment. Consequently, an economic and psychometrically sound conscientiousness questionnaire that is specifically customized for this context is needed. We developed and validated a short version of the MacCann et al. (2009) questionnaire. In study 1, French and German adaptations of the questionnaire were administered to a representative dataset comprising all ninth-graders in Luxembourg (N1=6325, Cohort 2017). Using an exhaustive search algorithm, we identified the optimal combination of four items for each subfacet by simultaneously considering three criteria: goodness of fit, factor saturation, and scalar measurement invariance across the German and French versions. In study 2, we validated our short 28-item questionnaire on a second, independent sample comprising 6,279 Luxembourgish ninth-graders (Cohort 2018). A 7-factor model assuming separate factors for each subfacet obtained acceptable fit (CFI=.93, RMSEA=.04, SRMR=.06). The criterion validity for each subfacet was tested by examining the relation to standardized achievement tests (SATs). In study 3, drawing on a dataset of 275 tenth-graders (linked longitudinally with the ninth-grade data from study 1), evidence of predictive validity (i.e., school grades) was examined. The subfacets of industriousness, caution and perfectionism showed the strongest relations with both SATs (study 2) and school grades (study 3). Our study delivered a short, valid and reliable questionnaire for the assessment of seven conscientiousness facets in the educational context. The scale is invariant across the German and French language versions and its brevity makes it suitable for large-scale educational assessment. [less ▲]

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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 detailDoes Conscientiousness Matter for Academic Success? Considering Different Facets of Conscientiousness and Different Educational Outcomes
Franzen, Patrick UL; van der Westhuizen, Lindie UL; Arens, A. Katrin et al

Poster (2020, April)

Conscientiousness is the strongest BIG-5 predictor of academic success. Both conscientiousness and academic success are broad concepts, consisting of multiple lower level facets. Conscientiousness facets ... [more ▼]

Conscientiousness is the strongest BIG-5 predictor of academic success. Both conscientiousness and academic success are broad concepts, consisting of multiple lower level facets. Conscientiousness facets might display differential relations to different indicators of academic success. To investigate these relations, conscientiousness facets need to be measured in an economic and valid way. We conducted two studies, validating a short conscientiousness scale measuring seven facets of conscientiousness (Industriousness, Task Planning, Perfectionism, Procrastination Refrainment, Tidiness, Control, Cautiousness), and testing the relations of these facets with GPA, test scores, school satisfaction, and engagement. The results supported the validity of the scale. Industriousness, Perfectionism, and Cautiousness revealed the highest relations to academic outcomes. GPA and test scores showed differential associations with the different conscientiousness facets. [less ▲]

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

Scientific Conference (2020, March)

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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 ▲]

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See detailCircadian preference as a typology: Latent-class analysis of adolescents' morningness/eveningness, relation with sleep behavior, and with academic outcomes
Preckel, Franzis; Fischbach, Antoine UL; Scherrer, Vsevolod et al

in Learning and Individual Differences (2020), 78

Detailed reference viewed: 168 (26 UL)