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Sung, 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
Golick, Douglas A.; Heng-Moss, Tiffany M.; Steckelberg, Allen L.; Brooks, David. W.; Higley, Leon G.; Fowler, David – Journal of Science Education and Technology, 2013
The purpose of the study was to determine whether undergraduate students receiving web-based instruction based on traditional, key character, or classification instruction differed in their performance of insect identification tasks. All groups showed a significant improvement in insect identifications on pre- and post-two-dimensional picture…
Descriptors: Science Instruction, College Science, Undergraduate Students, Web Based Instruction
Peer reviewedNachmias, Rafi; Tuvi, Inbal – Journal of Science Education and Technology, 2001
Discusses science educators' interest in Web-based learning (WBL). Provides a classification scheme by which scientifically-oriented educational websites can be evaluated for content level. Presents an example of site evaluation in the field of atomic structure and discusses the potential embedded in this taxonomy to assist the web site developer,…
Descriptors: Classification, Computer Uses in Education, Evaluation Criteria, Higher Education
Peer reviewedNikolopoulou, Kleopatra – Journal of Science Education and Technology, 2000
Presents an investigation of 13- and 14-year-old students' classification skills when they analyze scientific data in science lessons. Finds that less-able students could only classify according to discrete criteria, and that the scientific context influenced students' classification skills. (Contains 18 references.) (Author/WRM)
Descriptors: Academic Ability, Classification, Cognitive Processes, Computer Uses in Education

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