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Increasing Computational Protein Design Literacy through Cohort-Based Learning for Undergraduate Students
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Erin C. Yang; Robby Divine; Christine S. Kang; Sidney Chan; Elijah Arenas; Zoe Subol; Peter Tinker; Hayden Manninen; Alicia Feichtenbiner; Talal Mustafa; Julia Hallowell; Isiac Orr; Hugh Haddox; Brian Koepnick; Jacob O'Connor; Ian C. Haydon; Karla-Luise Herpoldt; Kandise Van Wormer; Celine Abell; David Baker; Alena Khmelinskaia; Neil P. King – Journal of Chemical Education, 2022
Undergraduate research experiences can improve student success in graduate education and STEM careers. During the COVID-19 pandemic, undergraduate researchers at our institution and many others lost their work-study research positions due to interruption of in-person research activities. This imposed a financial burden on the students and…
Descriptors: Undergraduate Students, Teaching Methods, COVID-19, Pandemics
Secondary School Genetics Instruction: Making Problem Solving Explicit and Meaningful.
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Thomson, Norman; Stewart, James – Journal of Biological Education, 1985
Explains an algorithm which details procedures for solving a broad class of genetics problems common to pre-college biology. Several flow charts (developed from the algorithm) are given with sample questions and suggestions for student use. Conclusions are based on the authors' research (which includes student interviews and textbook analyses).…
Descriptors: Algorithms, Biology, Genetics, Learning Strategies
Should Students Always Use Algorithms to Solve Problems?
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Frank, David V.; And Others – Journal of Chemical Education, 1987
Discusses the differences between problems and exercises in chemistry, and some of the difficulties that arise when the same methods are used to solve both. Proposes that algorithms are excellent models for solving exercises. Argues that algorithms not be used for solving problems. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
Generic and Harder Problems: Teaching Problem Solving.
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Middlecamp, Catherine; Kean, Elizabeth – Journal of Chemical Education, 1987
Discusses the difference between a generic chemistry problem (one which can be solved using an algorithm) and a harder chemistry problem (one for which there is no algorithm). Encourages teachers to help students recognize these categories of problems so they will be better able to find solutions. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
Using Algorithms to Teach Problem Solving.
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Schrader, C. L. – Journal of Chemical Education, 1987
Discusses the differences between problems and exercises, the levels of thinking required to solve them, and the roles that algorithms can play in helping chemistry students perform these tasks. Proposes that students be taught the logic of algorithms, their characteristics, and how to invent their own algorithms. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
A Semantic-Linguistic Method of Solving Verbal Problems.
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Hoggard, Franklin R. – Journal of Chemical Education, 1987
Suggests a method for solving verbal problems in chemistry using a linguistic algorithm that is partly adapted from two artificial intelligence languages. Provides examples of problems solved using the mental concepts of translation, rotation, mirror image symmetry, superpositioning, disjoininng, and conjoining. (TW)
Descriptors: Algorithms, Artificial Intelligence, Chemical Nomenclature, Chemical Reactions
A Simpler Way to Tame Multiple-Effect Evaporators.
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Joye, Donald D.; Koko, F. William Jr. – Chemical Engineering Education, 1988
Presents a new method to teach the subject of evaporators which is both simple enough to use in the classroom and accurate and flexible enough to be used as a design tool in practice. Gives an example using a triple evaporator series. Analyzes the effect of this method. (CW)
Descriptors: Algorithms, Chemical Engineering, Chemistry, College Science
Teaching Students to Use Algorithms for Solving Generic and Harder Problems in General Chemistry.
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Kean, Elizabeth; And Others – Journal of Chemical Education, 1988
Describes teaching strategies that help students improve problem solving skills. Lists three factors good problem solvers were found to possess. Gives step by step instructions for solving problems. (MVL)
Descriptors: Algorithms, Chemistry, College Science, Heuristics
The Role of Algorithms in Teaching Problem Solving.
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Bodner, George M. – Journal of Chemical Education, 1987
Differentiates between problems, exercises and algorithms. Discusses the role of algorithms in solving problems and exercises in chemistry. Suggests that very real differences exist between solving problems and exercises, and that problem solving steps can be and should be taught in chemistry education. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
Cognitive Restructuring as an Early Stage in Problem Solving.
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Bodner, George M.; McMillen, Theresa L. B. – Journal of Research in Science Teaching, 1986
Examines the hypothesis that there are preliminary stages in problem solving that are often neglected in teaching chemistry. Discusses correlations calculated between the student's ability to handle disembedding and cognitive restructuring tasks in the spatial domain and ability to solve chemistry problems. (TW)
Descriptors: Algorithms, Chemistry, Cognitive Processes, College Science
What Goes on in Students' Heads in Lab?
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Pickering, Miles – Journal of Chemical Education, 1987
Discusses some of the difficulties involved with chemistry laboratory experiences and some laboratory manuals. Cites studies that indicate that part of the difficulty can be attributed to constraints relating to the short-term memory of the operational information and the assumption that students have a certain level of knowledge. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
Findings--Structured Flowcharts vs. Pseudocode: The Preference for Learning Algorithms with a Graphic Method.
Scanlan, David – Engineering Education, 1988
Notes that almost all computer engineering textbooks present algorithms using only verbal methods. Poses that engineering students' ability to handle graphic representation is crucial yet information is presented verbally. Summarizes the results of 12 replications on learner preference for graphic or verbal algorithmic techniques. (MVL)
Descriptors: Algorithms, Cognitive Processes, College Science, Curriculum Design
The Relationship between M-Demand, Algorithms, and Problem Solving: A Neo-Piagetian Analysis.
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Niaz, Mansoor – Journal of Chemical Education, 1989
Defines M-demand as the maximum number of schemes that the subject must activate simultaneously in the course of executing a task. Discusses the effect of M-demand on problem solving. Uses algorithms to reduce M-demand. Describes the role of algorithms in problem solving. (MVL)
Descriptors: Algorithms, Chemistry, Cognitive Development, Cognitive Processes