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Ai-Chu Elisha Ding – Journal of Research on Technology in Education, 2024
Multilingual learners (MLs) often struggle with science conceptual learning partly due to the abstractness of the concepts and the complexity of scientific texts. This study presents a case of a Virtual Reality (VR) enhanced science learning unit to support middle-school students' science conceptual learning. Using a transformative mixed methods…
Descriptors: Multilingualism, Science Education, Learning Processes, Computer Simulation
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Nixon, Ryan S.; Smith, Leigh K.; Wimmer, Jennifer J. – School Science and Mathematics, 2015
This quasi-experimental study investigated how explicit instruction about multiple modes of representation (MMR) impacted grades 7 (n = 61) and 8 (n = 141) students' learning and multimodal use on end-of-unit assessments. Half of each teacher's (n = 3) students received an intervention consisting of explicit instruction on MMR in science…
Descriptors: Quasiexperimental Design, Grade 7, Grade 8, Intervention
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Gillies, Robyn M.; Nichols, Kim; Khan, Asaduzzaman – Cambridge Journal of Education, 2015
Teaching students to use and interpret representations in science is critically important if they are to become scientifically literate and learn how to communicate their understandings and learning in science. This study involved 248 students (119 boys and 129 girls) from 26 grade 6 teachers' classes in nine primary schools in Brisbane,…
Descriptors: Elementary School Science, Elementary School Students, Scientific Concepts, Concept Formation
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