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Dray, Kate E.; Dreyer, Kathleen S.; Lucks, Julius B.; Leonard, Joshua N. – Chemical Engineering Education, 2023
We present an educational unit to teach computational modeling, a vital part of chemical engineering curricula, through the lens of synthetic biology. Lectures, code, and homework questions provide conceptual and practical introductions to each computational method involved in the model development process, along with perspectives on how methods…
Descriptors: Engineering Education, Chemical Engineering, Teaching Methods, Units of Study
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Prevost, Luanna B.; Smith, Michelle K.; Knight, Jennifer K. – CBE - Life Sciences Education, 2016
Previous work has shown that students have persistent difficulties in understanding how central dogma processes can be affected by a stop codon mutation. To explore these difficulties, we modified two multiple-choice questions from the Genetics Concept Assessment into three open-ended questions that asked students to write about how a stop codon…
Descriptors: Science Instruction, Genetics, Scientific Concepts, Scoring
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Bierema, Andrea M.-K.; Schwarz, Christina V.; Stoltzfus, Jon R. – CBE - Life Sciences Education, 2017
National calls for improving science education (e.g., "Vision and Change") emphasize the need to learn disciplinary core ideas through scientific practices. To address this need, we engaged small groups of students in developing diagrammatic models within two (one large-enrollment and one medium-enrollment) undergraduate introductory…
Descriptors: Undergraduate Students, Biology, Science Education, Introductory Courses
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Cromley, Jennifer G.; Bergey, Bradley W.; Fitzhugh, Shannon; Newcombe, Nora; Wills, Theodore W.; Shipley, Thomas F.; Tanaka, Jacqueline C. – Learning and Instruction, 2013
Can students be taught to better comprehend the diagrams in their textbooks? Can such teaching transfer to uninstructed diagrams in the same domain or even in a new domain? What methods work best for these goals? Building on previous research showing positive results compared to control groups in both laboratory studies and short-term…
Descriptors: Reading Comprehension, Cooperative Learning, Biology, Control Groups
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Nicolaou, Chr. Th.; Evagorou, M.; Lymbouridou, Chr. – Science Education International, 2015
Despite the belief that emotions are important in the learning process, research in the area of emotions and learning, especially in science, is scant. Modelling and SSI argumentation have shared with respect to the emphasis in recent science standards reports as core scientific practices that need to be part of science teaching and learning. Even…
Descriptors: Elementary School Students, Science Instruction, Elementary School Science, Interviews
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Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M. – Journal of the Learning Sciences, 2013
We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Probability, Skill Development
Heekin, Jonathan Ralph Calvin – ProQuest LLC, 2013
Biology faculty at an East Coast university believed their undergraduate students were not being well served by the existing academic advising program. The purpose of this mixed methods project study was to evaluate the effectiveness of the academic advising model in a biology department. Guided by system-based organizational theory, a learning…
Descriptors: Biology, Academic Advising, Undergraduate Students, Holistic Approach
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Bowers, Jeffrey S. – Psychological Review, 2009
A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated…
Descriptors: Cytology, Brain, Schemata (Cognition), Neurological Organization