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Eshach, Haim; Kukliansky, Ida – International Journal of Science and Mathematics Education, 2018
The present study uses the intuitive rules theory as a framework to examine whether some of the difficulties in dealing with errors and uncertainties observed among students in the university physics laboratory can stem from their use of intuitive rules. The study also examines the relationship between the use of intuitive rules and laboratory…
Descriptors: Physics, Engineering Education, Error of Measurement, Error Patterns
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Melloy, Patricia G. – Biochemistry and Molecular Biology Education, 2015
A two-part laboratory exercise was developed to enhance classroom instruction on the significance of p53 mutations in cancer development. Students were asked to mine key information from an international database of p53 genetic changes related to cancer, the IARC TP53 database. Using this database, students designed several data mining activities…
Descriptors: College Science, Undergraduate Study, Science Laboratories, Cancer
Bumbacher, Engin; Salehi, Shima; Wierzchula, Miriam; Blikstein, Paulo – International Educational Data Mining Society, 2015
Studies comparing virtual and physical manipulative environments (VME and PME) in inquiry-based science learning have mostly focused on students' learning outcomes but not on the actual processes they engage in during the learning activities. In this paper, we examined experimentation strategies in an inquiry activity and their relation to…
Descriptors: Physics, Science Instruction, College Students, Predictor Variables
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies