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Download full textPérez-Lemonche, Ángel; Drury, Byron Coffin; Pritchard, David – International Educational Data Mining Society, 2018
We analyze results from paired pre- and post-instruction administration of the Mechanics Baseline Test to 2238 students in introductory mechanics classes. We investigate pairs of specific wrong answers given with unusual frequency by students on the pretest. We also identify transitions between pre- and post-test answers on the same question which…
Descriptors: Data Collection, Knowledge Level, Misconceptions, Pretests Posttests
Direct linkPawl, Andrew; Teodorescu, Raluca E.; Peterson, Joseph D. – Physical Review Special Topics - Physics Education Research, 2013
We have developed simple data-mining algorithms to assess the consistency and the randomness of student responses to problems consisting of multiple true or false statements. In this paper we describe the algorithms and use them to analyze data from introductory physics courses. We investigate statements that emerge as outliers because the class…
Descriptors: Data Collection, Test Reliability, Physics, Introductory Courses
Santoyo, Christina; Zhang, Shaoan – Teacher Education Quarterly, 2016
Teacher candidates (TCs) use clinical experiences to enact concepts taught in their university courses; therefore field experiences may be the most important component of teacher preparation (Hammerness et al., 2005). TCs require support and guidance as they learn to adapt curriculum materials for effective use in the classroom (Davis, 2006). They…
Descriptors: Preservice Teachers, Student Teachers, Lesson Plans, Field Experience Programs
Bailey, Janelle M.; Sanchez, Roxanne; Coble, Kim; Larrieu, Donna; Cochran, Geraldine; Cominsky, Lynn R. – Astronomy Education Review, 2012
In order to improve instruction in introductory astronomy, we are investigating students' preinstructional ideas about a number of cosmology topics. This article describes one aspect of this large research study in which 1270 students responded to a subset of three questions each from a larger set of questions about the following areas: definition…
Descriptors: College Instruction, Astronomy, Introductory Courses, Instructional Improvement
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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
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
