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Direct linkSung, Shannon H.; Li, Chenglu; Chen, Guanhua; Huang, Xudong; Xie, Charles; Massicotte, Joyce; Shen, Ji – Journal of Science Education and Technology, 2021
In this paper, we demonstrate how machine learning could be used to quickly assess a student's multimodal representational thinking. Multimodal representational thinking is the complex construct that encodes how students form conceptual, perceptual, graphical, or mathematical symbols in their mind. The augmented reality (AR) technology is adopted…
Descriptors: Observation, Artificial Intelligence, Knowledge Representation, Grade 9
Milenkovic´, Dus?ica D.; Segedinac, Mirjana D.; Hrin, Tamara N. – Journal of Chemical Education, 2014
The central goal of this study was to examine the extent to which a teaching approach focused on the interaction between macroscopic, submicroscopic, and symbolic levels of chemistry representations could affect high school students' performance in the field of inorganic reactions, as well as to examine how the applied instruction influences…
Descriptors: Science Instruction, Chemistry, Difficulty Level, Cognitive Processes
