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Emily K. Toutkoushian; Kihyun Ryoo – Measurement: Interdisciplinary Research and Perspectives, 2024
The Next Generation Science Standards (NGSS) delineate three interrelated dimensions that describe what students should know and how they should engage in science learning. These present significant challenges for assessment because traditional assessments may not be able to capture the ways in which students engage with content. Science…
Descriptors: Middle School Students, Academic Standards, Science Education, Learner Engagement
Sao Pedro, Michael; Jiang, Yang; Paquette, Luc; Baker, Ryan S.; Gobert, Janice – Grantee Submission, 2014
Students conducted inquiry using simulations within a rich learning environment for 4 science topics. By applying educational data mining to students' log data, assessment metrics were generated for two key inquiry skills, testing stated hypotheses and designing controlled experiments. Three models were then developed to analyze the transfer of…
Descriptors: Simulation, Transfer of Training, Bayesian Statistics, Inquiry
Gobert, Janice Darlene; Sao Pedro, Michael A.; Baker, Ryan S. – Grantee Submission, 2012
In this paper we explored whether engaging in two inquiry skills associated with data collection, designing controlled experiments and testing stated hypotheses, within microworlds for one physical science domain (density) impacted the acquisition of inquiry skills in another domain (phase change). To do so, we leveraged educational data mining…
Descriptors: Data Collection, Learning Analytics, Inquiry, Science Process Skills
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