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Aguilar, Stephen J. – Journal of Research on Technology in Education, 2018
This qualitative study focuses on capturing students' understanding two visualizations often utilized by learning analytics-based educational technologies: bar graphs, and line graphs. It is framed by Achievement Goal Theory--a prominent theory of students' academic motivation--and utilizes interviews (n = 60) to investigate how students at risk…
Descriptors: Comparative Analysis, Visualization, At Risk Students, College Students
Wagner, Dana L.; Hammerschmidt-Snidarich, Stephanie M.; Espin, Christine A.; Seifert, Kathleen; McMaster, Kristen L. – Learning Disabilities Research & Practice, 2017
Teachers must be proficient at using data to evaluate the effects of instructional strategies and interventions, and must be able to make, describe, justify, and validate their data-based instructional decisions to parents, students, and educational colleagues. An important related skill is the ability to accurately read and interpret…
Descriptors: Preservice Teachers, Progress Monitoring, Curriculum Based Assessment, Teacher Competencies
Kim, Myung-Hoon; Kim, Michelle S. – Journal of Chemical Education, 2016
A visual regression analysis using the least absolutes method (LAB) was developed, utilizing an interactive approach of visually minimizing the sum of the absolute deviations (SAB) using a bar graph in Excel; the results agree very well with those obtained from nonvisual LAB using a numerical Solver in Excel. These LAB results were compared with…
Descriptors: Least Squares Statistics, Regression (Statistics), Graphs, Courseware

Hopkins, Kenneth D.; Chappell, David – Educational and Psychological Measurement, 1994
Quick power estimates for detecting a difference in two population proportions are expedient during early stages of research planning. Such estimates are tabled and graphed in this article. They are shown to be conservative but accurate for most research situations when proportions fall in the range of 0.25 to 0.75. (SLD)
Descriptors: Comparative Analysis, Data Collection, Estimation (Mathematics), Graphs
Benson, Peter; McMillen, Marilyn Miles – 1991
A statistical portrait is provided of private schools in the United States, using the best national data available to the National Center for Education Statistics (NCES). Previously published work is used to give an overview of private schools from 1980-81 through 1985-86. Following an introductory examination of private schools in the United…
Descriptors: Catholic Schools, Comparative Analysis, Data Collection, Educational Trends

White, Cynthia – System, 1995
Examines results from a comparative study of the strategies of distance and classroom foreign language learners (French, German, Japanese, and Chinese) enrolled in a dual-mode institution. Data on strategy use was collected through a questionnaire and the yoked subject technique. Results indicate that mode of study is the predominant influence on…
Descriptors: Chinese, Comparative Analysis, Data Collection, Distance Education
Bernstein, Allison – Library Talk, 1999
Describes projects in a fifth grade classroom that used data collection and graph making activities as part of a collaborative project between the teacher and the library media specialist. Discusses the use of Excel spreadsheets, comparing the effectiveness of different types of graphs, and project planning. (LRW)
Descriptors: Comparative Analysis, Computer Assisted Instruction, Computer Graphics, Computer Software
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