References of "Krolak-Schwerdt, Sabine 50002142"
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See detailDiagnostic competence in school transition recommendations
Gräsel, Cornelia; Nölle, Ines; Krolak-Schwerdt, Sabine UL et al

Scientific Conference (2010, October)

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See detailInformationssuche und –verarbeitung von Lehrkräften bei der Beurteilung von Schülern
Herfordt, Julia; Krolak-Schwerdt, Sabine UL

Scientific Conference (2010, September)

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See detailGrundschulempfehlungen in Luxemburg – gleiche Chancen für alle?
Glock, Sabine; Krolak-Schwerdt, Sabine UL; Zöller, Isabelle et al

Scientific Conference (2010, September)

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See detailComparison of regression-based modeling methods for judgment data.
Krolak-Schwerdt, Sabine UL; Hörstermann, Thomas UL

Scientific Conference (2010, July)

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See detailInvited talk - Leistungsbeurteilungen in der Schule
Krolak-Schwerdt, Sabine UL

Scientific Conference (2010, June)

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See detailThe role of information search in the assessment of students’ academic achievements.
Herfordt, Julia; Krolak-Schwerdt, Sabine UL

Scientific Conference (2010, June)

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See detailRelevante diagnostische Informationen bei der Erstellung der Übergangsempfehlung – Lehrerwahrnehmung und tatsächliches Entscheidungsverhalten.
Nölle, Ines; Hörstermann, Thomas UL; Gräsel, Cornelia et al

Scientific Conference (2010, March)

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See detailDie kognitive Repräsentation von Schülertypen bei angehenden Lehrkräften - Eine typologische Analyse
Hörstermann, Thomas UL; Krolak-Schwerdt, Sabine UL; Fischbach, Antoine UL

in Schweizerische Zeitschrift für Bildungswissenschaften (2010), 32

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See detailDiagnostische Kompetenz von Grundschullehrkräften bei der Erstellung der Übergangsempfehlung: eine Analyse aus der Perspektive der sozialen Urteilsbildung
Gräsel, Cornelia; Krolak-Schwerdt, Sabine UL; Nölle, Ines et al

in Zeitschrift für Pädagogik (2010), 56(Sonderheft), 286-295

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See detailStrategies of model construction for the analysis of judgment data
Krolak-Schwerdt, Sabine UL

in Fink, Andreas; Lausen, Berthold; Seidel, Wilfried (Eds.) et al Advances in data analysis, data handling and business intelligence (2010)

This paper is concerned with the types of models researchers use to analyze empirical data in the domain of social judgments and decisions. Models for the analysis of judgment data may be divided into two ... [more ▼]

This paper is concerned with the types of models researchers use to analyze empirical data in the domain of social judgments and decisions. Models for the analysis of judgment data may be divided into two classes depending on the criteria they optimize: Optimizing an internal (mathematical) criterion function with the aim to minimize the discrepancy of values predicted by the model from obtained data or incorporating a substantive underlying theory into the model where model parameters are not only formally defined, but represent specified components of judgments. Results from applying models from both classes to empirical data exhibit considerable differences between the models in construct validity, but not in empirical validity. It may be concluded that any model for the analysis of judgment data implies the selection of a formal theory about judgments. Hence, optimizing a mathematical criterion function does not induce a non-theoretical rationale or neutral tool. As a consequence, models satisfying construct validity seem superior in the domain of judgments and decisions. [less ▲]

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