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Rho, Jihyun; Rau, Martina A.; Van Veen, Barry D. – International Educational Data Mining Society, 2022
Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…
Descriptors: Learning Processes, Models, Introductory Courses, Engineering Education
Langbeheim, Elon; Ben-Eliyahu, Einat; Adadan, Emine; Akaygun, Sevil; Ramnarain, Umesh Dewnarain – Chemistry Education Research and Practice, 2022
Learning progressions (LPs) are novel models for the development of assessments in science education, that often use a scale to categorize students' levels of reasoning. Pictorial representations are important in chemistry teaching and learning, and also in LPs, but the differences between pictorial and verbal items in chemistry LPs is unclear. In…
Descriptors: Science Instruction, Learning Trajectories, Chemistry, Thinking Skills
Crawford, Angela R. – Investigations in Mathematics Learning, 2022
Learning trajectories are built upon progressions of mathematical understandings that are typical of the general population of students. As such, they are useful frameworks for exploring how understandings of diverse learners may be similar or different from their peers, which has implications for tailoring instruction. The purpose of this…
Descriptors: Learning Trajectories, Mathematics Instruction, Student Diversity, Guidelines

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