Identifying determinants of teachers' judgment (in)accuracy regarding students' school-related motivations using a Bayesian cross-classified multi-level model

Praetorius, Anna‐Katharina; Koch, Tobias; Scheunpflug, Annette; Zeinz, Horst; Dresel, Markus

doi:10.1016/j.learninstruc.2017.06.003

Cited by 30 publications

(38 citation statements)

References 59 publications

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“…Moreover, Sommer et al (2008) pointed out that teachers more frequently attribute higher cognitive abilities to female students than to male students. Regarding the academic self-concept, Praetorius et al (2017) found higher teacher assessments for girls than for boys, in addition to higher assessments for younger students as well as for students with a very low or very high grade point average (GPA). However, students’ gender and age were not related to teachers’ assessment accuracy of students’ academic self-concept, whereas students with low or high GPAs were assessed more accurately than students with an average GPA.…”

Section: Introductionmentioning

confidence: 98%

What Do Teachers Think About Their Students’ Inclusion? Consistency of Students’ Self-Reports and Teacher Ratings

2019

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The aim of this study was to investigate the consistency between the self-reports and teacher ratings of students’ emotional and social inclusion at school as well as for their academic self-concept. The German version of the Perceptions of Inclusion Questionnaire (PIQ) was administered to 329 grade 8 students (50.8% female, M age = 14.5 years, SD age = 0.5 years) and their teachers. First, the three-dimensional structure of both PIQ versions was confirmed by confirmatory item factor analysis. The α and ω coefficients demonstrated good reliability for all scales. Second, a correlated trait-correlated method minus one model provided evidence that the method-specificity of teacher ratings was larger than the consistency between the self-reports and teacher ratings. Third, the results of a latent difference model indicated that general method effects can partly be explained by a student’s gender or special educational needs. Finally, the low consistency between self-reports and teacher rating is discussed.

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Section: Introductionmentioning

confidence: 98%

What Do Teachers Think About Their Students’ Inclusion? Consistency of Students’ Self-Reports and Teacher Ratings

2019

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“…Furthermore, we think it is interesting to find characteristics of the pupil(s), class, teacher(s) and/or school that influence the discrepancies found between the test data and the teacher judgments. This can be done in a quantitative way-using Bayesian multilevel analysis (see for instance Praetorius et al, 2017)-but also qualitatively, asking the teachers to comment on any discrepancies found. All in all, we believe the elicitation procedure opens up many opportunities to investigate tacit differences between "subjective" teacher judgments and "objective" data such as test results and to raise the diagnostic competence of teachers.…”

Section: Discussionmentioning

confidence: 99%

Development and Evaluation of a Digital Expert Elicitation Method Aimed at Fostering Elementary School Teachers' Diagnostic Competence

Lek

Schoot

2018

Front. Educ.

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Expert elicitation-an approach to systematically consult experts and quantify their insights-has been succesfully applied in fields as risk assessment, health and environmental research. Unfortunately, it has never been used within the Educational sciences, while it offers ample opportunities for educational practice, especially when used to foster the accuracy of teacher judgments; generally referred to as their "diagnostic competence." The current paper is the first to explore expert elicitation in an educational context and has two major goals. The first goal is to develop a digital expert elicitation method suitable to be used by elementary school teachers for self-reflection purposes. The second goal is to extensively test the expert elicitation method, using a test panel of 24 primary school teachers for 503 pupils in total. Results regarding the development of the elicitation method and its reliability, construct validity, face validity and feasibility are discussed as well as ideas how this elicitation method can be a valuable self-reflection instrument for teachers. The results are promising: all measures of reliability, feasibility, face validity and construct validity show positive results and teachers are enthusiastic about the possibilities of the method.

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“…The first research question refers to teachers' judgment accuracy, which can be defined as the congruence between students' self-reports and teacher reports (Praetorius, Koch, Scheunpflug, Zeinz, & Dresel, 2017). Teachers' judgment accuracy was examined with regard to the consistency coefficients at both levels (see Table 1).…”

Section: Empirical Illustrationmentioning

confidence: 99%

On the Power and Performance of a Doubly Latent Residual Approach to Explain Latent Specific Factors in Multilevel-Bifactor-(S-1) Models

Koch

Semmler-Busch

2018

Structural Equation Modeling: A Multidisciplinary Journal

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A doubly latent residual approach (DLRA) is presented to explain latent specific factors in multilevel bifactor-(S-1) models. The new approach overcomes some important limitations of the multiple indicators multiple causes (MIMIC) approach and allows researchers to predict latent specific factors at different levels. The DLRA is illustrated using real data from a largescale assessment study. Furthermore, the statistical performance and power of the DLRA is examined in a Monte Carlo simulation study. The results show that the new DLRA performs well if more than 50 clusters and more than 10 observations per cluster are sampled. The power to test structural parameters at level 2 was lower than at level 1. To test a medium effect at level 2, we recommend to sample at least 100 clusters with a minimum cluster size of 10. The advantages and limitations of the new approach are discussed and guidelines for applied researchers are provided.

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Identifying determinants of teachers' judgment (in)accuracy regarding students' school-related motivations using a Bayesian cross-classified multi-level model

Cited by 30 publications

References 59 publications

What Do Teachers Think About Their Students’ Inclusion? Consistency of Students’ Self-Reports and Teacher Ratings

What Do Teachers Think About Their Students’ Inclusion? Consistency of Students’ Self-Reports and Teacher Ratings

Development and Evaluation of a Digital Expert Elicitation Method Aimed at Fostering Elementary School Teachers' Diagnostic Competence

On the Power and Performance of a Doubly Latent Residual Approach to Explain Latent Specific Factors in Multilevel-Bifactor-(S-1) Models

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