Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation Between the Curriculum and Students' Mathematical Strategies

被引:38
作者
Auer, Marije F. Fagginger [1 ]
Hickendorff, Marian [2 ]
Van Putten, Cornelis M. [1 ]
Beguin, Anton A. [3 ]
Heiser, Willem J. [1 ]
机构
[1] Leiden Univ, Inst Psychol, NL-2300 RB Leiden, Netherlands
[2] Leiden Univ, Inst Educ & Child Studies, NL-2300 RB Leiden, Netherlands
[3] CITO Dutch Natl Inst Educ Measurement, Arnhem, Netherlands
关键词
TEACHER CHARACTERISTICS; ELEMENTARY MATHEMATICS; MONTE-CARLO; ACHIEVEMENT; VARIABLES; MODELS; SIZE;
D O I
10.1080/08957347.2016.1138959
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint inFLuence of teacher and student variables. Using data from the 2011 assessment of Dutch primary schools' mathematics, this study explores the relation between the curriculum as reported by 107 teachers and the strategy choices of their 1,619 students, while controlling for student characteristics. Considerable teacher effects are demonstrated, as well as significant relations between the intended as well as enacted curriculum and students' strategy use. Implications of these results for both more theoretical and practical educational research are discussed, as are several issues in applying MLCA and possibilities for applying MLCA to different types of educational data.
引用
收藏
页码:144 / 159
页数:16
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