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Matías Bustamante-Valdés; Danilo Díaz-Levicoy – International Electronic Journal of Mathematics Education, 2024
This study aims to analyze the graphical comprehension of 5th and 6th grade students in multigrade rural primary education in Chile. The theoretical framework considers levels of reading and semiotic levels in statistical graphs. A qualitative methodology of descriptive level is followed, using content analysis method for the responses given to a…
Descriptors: Rural Schools, Foreign Countries, Multigraded Classes, Grade 5
Dulger, Mehmet; Deniz, Hasan – International Journal of Environmental and Science Education, 2017
The purpose of this paper is to assess the validity of multiple-choice questions in measuring fourth grade students' ability to interpret graphs related to physical science topics such as motion and temperature. We administered a test including 6 multiple-choice questions to 28 fourth grade students. Students were asked to explain their thinking…
Descriptors: Test Validity, Multiple Choice Tests, Elementary School Students, Grade 4
Tunç-Pekkan, Zelha – Educational Studies in Mathematics, 2015
It is now well known that fractions are difficult concepts to learn as well as to teach. Teachers usually use circular pies, rectangular shapes and number lines on the paper as teaching tools for fraction instruction. This article contributes to the field by investigating how the widely used three external graphical representations (i.e., circle,…
Descriptors: Mathematics Instruction, Mathematical Concepts, Teaching Methods, Graphs
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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