Investigation of Prospective Science Teachers’ Grounded Mental Models by Mathematical Algorithms: Star Subject

Autor: Ebru Ezberci Çevik, Mehmet Altan Kurnaz
Rok vydání: 2022
Zdroj: Malaysian Online Journal of Educational Technology. 10:244-264
ISSN: 2289-2990
DOI: 10.52380/mojet.2022.10.4.262
Popis: In this study, it is aimed to reveal the models related to star subject as one of the concepts of astronomy of prospective science teachers before and after the current instruction through model analysis. This modeling situation is expressed as a Grounded Mental Model (GMM), since there will be a mental modeling that is revealed according to what is presented within the limits defined to the person. The research was conducted with an integrated case study and experimental design. The study group consisted of 73 prospective science teachers. In this study, the Star Subject Concept Test (SSCT) developed by the researchers was used as the data collection tool. In the analysis of the data, algorithms and matrices which are among the model analysis elements were used. At the end of the study, it was determined that the majority of the GMMs they had before teaching about the star concept were in Inconsistent Mixed Models, At the end of the teaching period, it was determined that the majority of the candidates had GMMs reflecting the status of the Consistent Dominant Scientific Model. According to the GMM tendencies of the class, prospective teachers were found to be inconsistent in star identity question group in terms of GMM in pre-test.
Databáze: OpenAIRE