Subject-specific characteristics of instructional quality in mathematics education

Schlesinger, Lena; Jentsch, Armin; Kaiser, Gabriele; König, Johannes; Blömeke, Sigrid

doi:10.1007/s11858-018-0917-5

Cited by 78 publications

(52 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…And even though the corresponding scales and coding schemes were often applied to one specific subject, in particular mathematics, the types of indicators used and their wording was conceptualized from a generic cognitive-psychological point of view. In contrast, more recently not only a fourth subjectspecific facet that includes quality criteria of mathematics education, hardly transferable to other subjects, has been added (Schlesinger et al 2018;Lipowsky and Bleck 2019) but cognitive activation has also been operationalized and phrased in a more subject-specific way (Schlesinger et al 2018).…”

Section: Discussionmentioning

confidence: 99%

“…Subject-specific INQUA represents mathematicsrelated quality. In particular, this aspect relates to how teachers address mathematical concepts and interact mathematically with students while using mathematical terms, explaining mathematical procedures, providing feedback or dealing with student errors (Hiebert and Grouws 2007;Schlesinger et al 2018). Studies provided evidence on the predictive validity of INQUA on cognitive and affectivemotivational student outcomes (e.g., Kunter et al 2013;Praetorius et al 2018).…”

Section: Teacher Performancementioning

confidence: 99%

“…To obtain a first answer to these questions, an outcome variable was needed that indicated different levels of performance quality, in our case instructional quality. The observation protocol used to assess INQUA was validated in several contexts (e.g., Schlesinger et al 2018).…”

Section: Instructional Quality and Its Relation To Teacher Competencementioning

confidence: 99%

See 2 more Smart Citations

Profiles of mathematics teachers’ competence and their relation to instructional quality

Blömeke

Kaiser

König

et al. 2020

ZDM Mathematics Education

Self Cite

View full text Add to dashboard Cite

Most of the research examining the relation between instructional quality (INQUA) and mathematics teachers' competence was restricted to a limited set of competence facets. Furthermore, mostly variable-oriented approaches were applied that assume homogeneity of teacher competence. In our study, teacher competence is conceptualized as a comprehensive multi-dimensional construct including a broad range of subject-specific and generic facets regarding mathematics teachers' knowledge, skills and beliefs, all assessed in a standardized way with well-established instruments. In our person-oriented approach, applying latent profile analysis, we examined whether it was possible to identify subgroups of teachers with different competence profiles. These profiles were then related to the generic and subject-specific INQUA implemented. The exploratory study was carried out with 77 secondary mathematics teachers from Germany as part of the projects TEDS Instruct and TEDS Validate. The data revealed four competence profiles that differed quantitatively and qualitatively. The profiles were related to different types of INQUA, and the relations indicate a need of strong levels of knowledge and skills for high INQUA but a lesser relevance of learning beliefs related to the dynamic nature of mathematics. In addition, our results indicate a need of a stronger subject-specific operationalization of INQUA in contrast to previously dominating generic conceptualizations.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Teacher Performancementioning

confidence: 99%

See 1 more Smart Citation

Profiles of mathematics teachers’ competence and their relation to instructional quality

Blömeke

Kaiser

König

et al. 2020

ZDM Mathematics Education

Self Cite

View full text Add to dashboard Cite

show abstract

“…Mathematikdidaktiker*innen betonen die fachliche Korrektheit daher oft als wichtiges ergänzendes Kriterium (z. B. Brunner 2018;Schlesinger et al 2018 Aufgrund der Kritik an ausschließlich generischen Unterrichtsqualitätsmerkmalen entwickelten Mathematikdidaktiker*innen stärker fachspezifische Instrumente, indem sie teilweise zusätzliche Dimensionen ergänzten (z. B.…”

Section: Die Diskussion Der Fachspezifität Von Unterrichtsqualität In Der Mathematikdidaktikunclassified

Fachspezifität von Unterrichtsqualität – aus der Perspektive der Mathematikdidaktik

Dreher

Leuders

2021

Unterrichtswiss

View full text Add to dashboard Cite

ZusammenfassungDer Beitrag gibt einen kurzen Überblick über die Diskussion (und aktuelle Forschung) zur Fachspezifität von Unterrichtsqualität aus der Perspektive der Mathematikdidaktik. Sowohl theoretische als auch empirische Argumente verdeutlichen, dass bei einer Konzeptualisierung von Unterrichtsqualität fachspezifische Aspekte nicht außer Acht gelassen werden sollten. Die Berücksichtigung fachspezifischer Aspekte bezieht sich derzeit meist auf die Spezifizierung von Kriterien bei der Erfassung Unterrichtsqualität durch Ratings. Wir argumentieren jedoch, dass Kriterien dabei nicht die einzige relevante Varianzquelle darstellen, in der sich Fachspezifität niederschlägt. Um der Fachspezifität von Unterrichtsqualität systematisch auf die Spur zu kommen, schlagen wir daher eine mehrdimensionale Perspektive auf die Fachspezifität von Unterrichtsqualität als Grundlage für empirische Forschungsstrategien vor. Demnach zeigt sich die Fachspezifität von Unterrichtsqualität in unterschiedlichen Varianzquellen (Kriterien, Situationen, Ratern), die sich durch verschiedene Grade an Fachspezifität systematisch auf die eingeschätzte Unterrichtsqualität auswirken können. Insbesondere illustrieren wir anhand eines Beispiels, wie das fach- und inhaltsbezogene Wissen von Ratern (und damit die Fachspezifität von Ratern) ihre Interpretationen von Kriterien und Unterrichtssituationen beeinflussen und sich systematisch in ihren Einschätzungen von Unterrichtsqualität niederschlagen können.

show abstract

“…However, while this defining characteristic was for a long time primarily related to the participation and cooperation of various academic disciplines (e.g., pedagogy, psychology, sociology, or educational studies; see Deutscher Bildungsrat [German Education Council], 1974;Gräsel, 2015), in recent years, it has gained a within-field content-related dimension with regard to the diverse school subjects under investigation. The validity of findings from mathematical and scientific contexts, on which instructional research has mainly focused so far, is being questioned with regard to disparate teaching and learning conditions and subject-specific cultures in the human and social sciences-and their generalizability, in principle, is doubted (e.g., Praetorius et al, 2018;Schlesinger et al, 2018;Wisniewski et al, 2020). So, the school subject becomes an information-bearing grouping variable at a higher level, which must be adequately considered in the data analysis.…”

Section: Introductionmentioning

confidence: 99%

Statistical Methods in Transdisciplinary Educational Research

et al. 2020

View full text Add to dashboard Cite

A central task of educational research is to examine common issues of teaching and learning in all subjects taught at school. At the same time, the focus is on identifying and investigating unique subject-specific aspects on the one hand and transdisciplinary, generalizable effects on the other. This poses various methodological challenges for educational researchers, including in particular the aggregation and evaluation of already published study effects, hierarchical data structures, measurement errors, and comprehensive data sets with a large number of potentially relevant variables. In order to adequately deal with these challenges, this paper presents the core concepts of four methodological approaches that are suitable for the analysis of transdisciplinary research questions: meta-analysis, multilevel models, latent multilevel structural equation models, and machine learning methods. Each of these approaches is briefly illustrated with an example inspired by the interdisciplinary research project FALKE (subject-specific teacher competencies in explaining). The data and analysis code used are available online at https://osf.io/5sn9j. Finally, the described methods are compared, and some application hints are given.

show abstract

Subject-specific characteristics of instructional quality in mathematics education

Cited by 78 publications

References 30 publications

Profiles of mathematics teachers’ competence and their relation to instructional quality

Profiles of mathematics teachers’ competence and their relation to instructional quality

Fachspezifität von Unterrichtsqualität – aus der Perspektive der Mathematikdidaktik

Statistical Methods in Transdisciplinary Educational Research

Contact Info

Product

Resources

About