Cognitive and Motivational Person Characteristics as Predictors of Diagnostic Performance: Combined Effects on Pre-Service Teachers’ Diagnostic Task Selection and Accuracy
-
Published:2022-03
Issue:1
Volume:43
Page:135-172
-
ISSN:0173-5322
-
Container-title:Journal für Mathematik-Didaktik
-
language:en
-
Short-container-title:J Math Didakt
Author:
Kron StephanieORCID, Sommerhoff Daniel, Achtner Maike, Stürmer Kathleen, Wecker Christof, Siebeck Matthias, Ufer Stefan
Abstract
AbstractThe acquisition of diagnostic competences is an essential goal of teacher education. Thus, evidence on how learning environments facilitate pre-service teachers’ acquisition of corresponding competences is important. In teacher education, approximations of practice (such as simulations) are discussed as being learning environments that can support learners in activating acquired knowledge in authentic situations. Simulated diagnostic interviews are recommended to foster teachers’ diagnostic competences.The conceptualization of diagnostic competences highlights the importance of cognitive and motivational characteristics. Motivational learning theories predict that the activation of acquired knowledge in learning situations may be influenced by motivational characteristics such as individual interest. Although teachers’ diagnostic competences constitute an increasing research focus, how cognitive and motivational characteristics interact when shaping the diagnostic process and accuracy in authentic learning situations remains an open question.To address this question, we report on data from 126 simulated diagnostic one-on-one interviews conducted by 63 pre-service secondary school mathematics teachers (students simulated by research assistants), studying the combined effects of interest and professional knowledge on the diagnostic process and accuracy. In addition to the main effect of content knowledge, interaction effects indicate that participants’ interest plays the role of a “door-opener” for the activation of knowledge during simulation-based learning. Thus, the results highlight the importance of both, cognitive and motivational characteristics. This implies that simulation-based learning environments should be designed to arouse participants’ interest to support their learning or to support less interested learners in activating relevant knowledge.
Funder
Deutsche Forschungsgemeinschaft Ludwig-Maximilians-Universität München
Publisher
Springer Science and Business Media LLC
Subject
Education,General Mathematics
Reference76 articles.
1. Ainley, M., Hidi, S., & Berndorff, D. (2002). Interest, learning and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94(3), 545–561. 2. Alibali, M. W., & Sidney, P. G. (2015). Variability in the natural number bias: Who, when, how, and why. Learning and Instruction, 37, 56–61. 3. von Aufschnaiter, C., Cappell, J., Dübbelde, G., Ennemoser, M., Mayer, J., Stiensmeier-Pelster, J., Sträßer, R., & Wolgast, A. (2015). Diagnostische Kompetenz. Theoretische Überlegungen zu einem zentralen Konstrukt der Lehrerbildung. Zeitschrift für Pädagogik, 61(5), 738–758. 4. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014). Package Lme4: linear mixed-effects models using Eigen and S4. Journal of statistical software, 67, 1–103. 5. Baumert, J., & Kunter, M. (2013). The COACTIV model of teachers’ professional competence. In M. Kunter, J. Baumert, W. Blum, U. Klusmann, S. Krauss & M. Neubrand (Eds.), Cognitive activation in the mathematics classroom and professional competence of teachers: results from the COACTIV project (pp. 25–48). Springer.
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|