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von Davier, Matthias; Tyack, Lillian; Khorramdel, Lale – Educational and Psychological Measurement, 2023
Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…
Descriptors: Scoring, Networks, Artificial Intelligence, Elementary Secondary Education
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Bursal, Murat; Yetis, Serap – International Journal of Research in Education and Science, 2020
This survey design study was designed to test whether the graph skills and affective states of middle school students about graphs differ by their gender, grade level, and graph types (line, bar, and pie). The data collection instruments consisted of two scales developed by the authors and a Graph Skills Test, which consisted of graph questions…
Descriptors: Middle School Students, Grade 7, Grade 8, Graphs
Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman – Online Submission, 2015
The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…
Descriptors: Science Achievement, Mathematics Achievement, Information Retrieval, Data Analysis
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Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman – Journal of Education in Science, Environment and Health, 2015
The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…
Descriptors: Science Achievement, Information Retrieval, Data Analysis, Middle School Students