2009
DOI: 10.1016/j.cedpsych.2008.12.001
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Assessing the impact of learning environments: How to use student ratings of classroom or school characteristics in multilevel modeling

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Cited by 412 publications
(344 citation statements)
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“…For sample A, the ICC at the octant level ranged from 0.13 to 0.31, indicating that the questionnaire could distinguish rather well between teachers. Besides the ICC, which refers to the average correlation between individual students' ratings of the same teacher, the ICC2 was also calculated, providing an estimate of the reliability of class-mean ratings (Lüdtke et al 2009). The ICC2 indicated that the classroom aggregates of the scales were rather reliable (values greater than 0.70 indicate sufficient reliability, Lüdtke et al 2009), ranging from 0.79 to 0.92 for an average class size of n = 25, and between 0.74 and 0.82 for n = 10 except for the 4-Compliant scale (0.60).…”
Section: Resultsmentioning
confidence: 99%
“…For sample A, the ICC at the octant level ranged from 0.13 to 0.31, indicating that the questionnaire could distinguish rather well between teachers. Besides the ICC, which refers to the average correlation between individual students' ratings of the same teacher, the ICC2 was also calculated, providing an estimate of the reliability of class-mean ratings (Lüdtke et al 2009). The ICC2 indicated that the classroom aggregates of the scales were rather reliable (values greater than 0.70 indicate sufficient reliability, Lüdtke et al 2009), ranging from 0.79 to 0.92 for an average class size of n = 25, and between 0.74 and 0.82 for n = 10 except for the 4-Compliant scale (0.60).…”
Section: Resultsmentioning
confidence: 99%
“…Students have encountered a variety of teachers and teaching practices and asking them to rate these is economically applicable in the classroom (Clausen, 2002;De Jong & Westerhof 2001). It has been argued that aggregated student ratings constitute a shared (and more objective) perception of teaching practices rather than representing individual perceptions (Kunter et al, 2007;Lüdtke, Robitzsch, Trautwein, & Kunter, 2009;Lüdtke, Trautwein, Kunter, & Baumert, 2006). In terms of construct validity, Wagner, Göllner, Helmke, Trautwein, and Lüdtke (2013) showed that students are able to differentiate between theoretical criteria of instructional quality and describe their teachers' teaching practices in this respect.…”
Section: Assessing Representational Practices In Science Class Througmentioning
confidence: 99%
“…Individual student variables were introduced as predictors at level 1 and aggregated variables (mean class scores) at level 2. All predictors were standardized to a common metric (z-scores) and individual student variables were centered at the group mean as recommended by Lüdtke et al (2009). Within-class and between-class effects on students' outcome could thus be clearly disentangled.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…However, it highly depends on the aims of research as to which conceptualization of instructional quality is most appropriate. Lütdke et al [31] point out that assessing characteristics of learning environments with data aggregated at the group level focuses on differences between learning environments, while assessing students' personal perceptions focuses on differences between students. Concerning motivational learning outcomes, it is unclear which conceptualization is most appropriate.…”
Section: Characteristics Of Instructional Quality Mathematics Self-comentioning
confidence: 99%
“…Instructional quality and attitudinal and affective variables were assessed using student self-report scales. Compared to objective descriptions of instructional quality, student ratings offers a range of conceptual advantages such as a high reliability due to students' extensive experiences with different teachers and experiences with the same teacher in different domains [31]. However, in particular, students' subjective perceptions of their learning environment were shown to be highly predictive for motivational learning outcomes [30].…”
Section: Characteristics Of Instructional Quality Mathematics Self-comentioning
confidence: 99%