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Download full textSalar, Riza; Turgut, Umit – Science Education International, 2021
The learning characteristics of each student are different. Differentiated instruction considers individual differences, as such guides the learning journey rather than seeing these differences as a challenge. The purpose of this research was to compare the effects of differentiated instruction and 5E learning cycle in physics classes on the…
Descriptors: Physics, Science Instruction, Science Achievement, Pretests Posttests
Direct linkHinze, Scott R.; Rapp, David N.; Williamson, Vickie M.; Shultz, Mary Jane; Deslongchamps, Ghislain; Williamson, Kenneth C. – Learning and Instruction, 2013
Students are frequently presented with novel visualizations introducing scientific concepts and processes normally unobservable to the naked eye. Despite being unfamiliar, students are expected to understand and employ the visualizations to solve problems. Domain experts exhibit more competency than novices when using complex visualizations, but…
Descriptors: Prior Learning, Individual Differences, Novices, Organic Chemistry
The Impact of Learner's Prior Knowledge on Their Use of Chemistry Computer Simulations: A Case Study
Liu, Han-Chin; Andre, Thomas; Greenbowe, Thomas – Journal of Science Education and Technology, 2008
It is complicated to design a computer simulation that adapts to students with different characteristics. This study documented cases that show how college students' prior chemistry knowledge level affected their interaction with peers and their approach to solving problems with the use of computer simulations that were designed to learn…
Descriptors: Science Instruction, Individual Differences, Knowledge Level, Prior Learning
Cook, Michelle Patrick – Science Education, 2006
Visual representations are essential for communicating ideas in the science classroom; however, the design of such representations is not always beneficial for learners. This paper presents instructional design considerations providing empirical evidence and integrating theoretical concepts related to cognitive load. Learners have a limited…
Descriptors: Prior Learning, Memory, Cognitive Structures, Instructional Design
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
