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Angra, Aakanksha; Gardner, Stephanie M. – CBE - Life Sciences Education, 2017
Undergraduate biology education reform aims to engage students in scientific practices such as experimental design, experimentation, and data analysis and communication. Graphs are ubiquitous in the biological sciences, and creating effective graphical representations involves quantitative and disciplinary concepts and skills. Past studies…
Descriptors: Graphs, Biology, Science Instruction, College Science
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Frischemeier, Daniel; Biehler, Rolf – Statistics Education Research Journal, 2018
Group comparisons offer students opportunities to reason about many fundamental statistical concepts like center, variation, or distribution. When doing such activities using large, real datasets, technology becomes an essential tool for exploring the data. With its large variety of features and its user-friendly handling, TinkerPlots™--as a…
Descriptors: Graphs, Teaching Methods, Educational Technology, Technology Uses in Education
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Chini, Jacquelyn J.; Straub, Carrie L.; Thomas, Kevin H. – Physical Review Physics Education Research, 2016
Undergraduate students are increasingly being used to support course transformations that incorporate research-based instructional strategies. While such students are typically selected based on strong content knowledge and possible interest in teaching, they often do not have previous pedagogical training. The current training models make use of…
Descriptors: Undergraduate Students, College Science, Physics, Science Process Skills
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Hill, Matthew; Sharma, Manjula Devi – EURASIA Journal of Mathematics, Science & Technology Education, 2015
To succeed within scientific disciplines, using representations, including those based on words, graphs, equations, and diagrams, is important. Research indicates that the use of discipline specific representations (sometimes referred to as expert generated representations), as well as multi-representational use, is critical for problem solving…
Descriptors: Case Studies, Graduate Students, Qualitative Research, Coding
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Carruthers, Sarah; Masson, Michael E. J.; Stege, Ulrike – Journal of Problem Solving, 2012
Recent studies on a computationally hard visual optimization problem, the Traveling Salesperson Problem (TSP), indicate that humans are capable of finding close to optimal solutions in near-linear time. The current study is a preliminary step in investigating human performance on another hard problem, the Minimum Vertex Cover Problem, in which…
Descriptors: Performance, Problem Solving, Graphs, Mathematics
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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
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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