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Norhaslinda Abdul Samad; Kamisah Osman; Nazrul Anuar Nayan – International Journal of Educational Methodology, 2023
This study investigated the influence of CThink4CS2 Module on computational thinking (CT) skills of form four chemistry students. The CThink4CS[superscript]2 Module integrated CT with the Engineering Design Process (EDP) in chemistry class. This study utilized quantitative research methods and quasi-experimental design. Quantitative data were…
Descriptors: Computation, Thinking Skills, Engineering, Design
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Eric D. Glendening; Steven D. Burke; John W. Moore; Frank Weinhold – Journal of Chemical Education, 2022
Traditional physical chemistry conceptions of reaction mechanism are formulated in terms of stationary points of an Arrhenius-style "energy profile" that differs sharply (in purpose and form) from the corresponding Robinson-style "arrow-pushing" mechanistic conceptions of organic chemistry. We show here how these diverse…
Descriptors: Chemistry, Science Education, Scientific Concepts, Theories
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Paul P. Martin; David Kranz; Peter Wulff; Nicole Graulich – Journal of Research in Science Teaching, 2024
Constructing arguments is essential in science subjects like chemistry. For example, students in organic chemistry should learn to argue about the plausibility of competing chemical reactions by including various sources of evidence and justifying the derived information with reasoning. While doing so, students face significant challenges in…
Descriptors: Science Education, Chemistry, Persuasive Discourse, Writing Evaluation
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Ling Yuan; Chunxiao Meng; Huiyu Hou; Hongzhang Wang; Changwei Pan; Juan Ma; Chenghao Zhu; Qingyu Gao – Journal of Chemical Education, 2022
Nonlinear chemical reactions produce interesting chemohydrodynamic patterns in an unstirred medium, which act as interesting demonstrations to display the novel phenomena in a nonequilibrium chemical system. Here, we report new outreach experiments: pH chemohydrodynamic patterns modulated by sodium polyacrylate in the bromate-sulfite-ferrocyanide…
Descriptors: Chemistry, Scientific Concepts, Science Education, Science Experiments
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Mulvey, Bridget – Science Teacher, 2016
Students best learn science through a combination of science inquiry and language learning. This article presents a series of chemistry lessons on the naming of compounds. The weeklong unit focuses on patterns across compound names and chemical formulas and addresses several of the "Next Generation Science Standards" (NGSS Lead States…
Descriptors: Science Instruction, Chemistry, Scientific Concepts, Naming
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Pinder, Patrice Juliet – Education, 2012
The primary objectives of this research were to explore achievement pattern differences and the influence of family factors on the achievement patterns of Afro-Caribbean and African American students within the United States (U.S.). The study utilized two research designs; a causal-comparative and a correlational design. A student family…
Descriptors: Academic Achievement, High School Students, African American Students, Pattern Recognition
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Adbo, Karina; Taber, Keith S. – International Journal of Science Education, 2009
The results presented here derive from a longitudinal study of Swedish upper secondary science students' (16-19 years of age) developing understanding of key chemical concepts. The informants were 18 students from two different schools. The aim of the present study was to investigate the mental models of matter at the particulate level that…
Descriptors: Foreign Countries, Secondary School Science, Chemistry, High School Students
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Olsen, Robert J. – Journal of Chemical Education, 2008
I describe how data pooling and data visualization can be employed in the first-semester general chemistry laboratory to introduce core statistical concepts such as central tendency and dispersion of a data set. The pooled data are plotted as a 1-D scatterplot, a purpose-designed number line through which statistical features of the data are…
Descriptors: Familiarity, Visualization, Chemistry, Laboratories
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Pogliani, L.; Klein, D. J.; Balaban, A. T. – International Journal of Mathematical Education in Science & Technology, 2006
Through the importance of the number three in our culture and the strange preference for a ternary pattern of our nature one can perceive how and why number theory degraded to numerology. The strong preference of our minds for simple patterns can be read as the key to understanding not only the development of numerology, but also why scientists…
Descriptors: Number Concepts, Numbers, Pattern Recognition, Models
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Schultz, Emeric – Journal of Chemical Education, 2005
An approach to learning chemical facts that starts with the periodic table and depends primarily on recognizing and completing patterns and following a few simple rules is described. This approach exploits the exceptions that arise and uses them as opportunities for further concept development.
Descriptors: Concept Formation, Pattern Recognition, Chemistry, Tables (Data)
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Schrader, C. L. – Journal of Chemical Education, 1984
Discusses instructional strategies and activities designed to help students learn to recognize patterns and to create models to explain patterns. These include laboratory investigations and an exercise in which students are challenged to find the model used for the classroom seating arrangement. (JN)
Descriptors: Chemistry, High Schools, Models, Pattern Recognition
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Sterling, Donna – Science Scope, 1996
Presents an activity that introduces the historical developments in science that led to the discovery of the periodic table and lets students experience scientific discovery firsthand. Enables students to learn about patterns among the elements and experience how scientists analyze data to discover patterns and build models. (JRH)
Descriptors: Chemistry, Classification, Data Analysis, Discovery Processes
Lawlor, Joseph – 1984
Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…
Descriptors: Artificial Intelligence, Chemistry, Cognitive Processes, Computer Science
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Fensham, Peter; Kornhauser, Aleksandra – Journal of Chemical Education, 1982
Two presentations at the 1981 International Conference on Chemical Education are summarized: (1) current and future rationales for chemistry instruction and use of Gowin's V for more effective chemistry teaching and (2) creative adaptability toward challenges of chemistry content, society, and the individual, focusing on learning chemistry by…
Descriptors: Chemistry, College Science, Concept Formation, Educational Objectives