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Wise, Alyssa Friend; Shaffer, David Williamson – Journal of Learning Analytics, 2015
It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…
Descriptors: Learning Theories, Predictor Variables, Data, Data Analysis
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Seixas, T. M.; da Silva, M. A. Salgueiro – Physics Teacher, 2015
When conducting experiments involving the measurement of physically related quantities, choosing an appropriate spacing for the experimental independent variable is a crucial procedure whose consequences may go beyond data graphical visualization. This is particularly true if the measured quantities are nonlinearly related and experimental errors…
Descriptors: Measurement, Data, Error of Measurement, Intervals
Lee, Katelyn; Therriault, Susan – College and Career Readiness and Success Center, 2016
This brief examines strategies for leveraging State longitudinal data systems (SLDS) to promote college and career readiness (CCR) goals. The examples provided are based on current state efforts to use their state longitudinal data systems to achieve their CCR vision and goals. The following information outlines the basic purpose and elements of…
Descriptors: Longitudinal Studies, Career Readiness, College Readiness, Elementary Secondary Education
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Sole, Marla A. – Mathematics Teacher, 2016
Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…
Descriptors: Statistics, Mathematics Instruction, Data Collection, Teaching Methods
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Lei, Wu; Qing, Fang; Zhou, Jin – International Journal of Distance Education Technologies, 2016
There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…
Descriptors: Causal Models, Attribution Theory, Correlation, Evaluation Methods
Chatterjee, Samprit; Hadi, Ali S. – John Wiley & Sons, Inc, 2012
Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…
Descriptors: Regression (Statistics), Data Analysis, Statistical Analysis, Models
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Lewis, Timothy J.; Scott, Terrance M.; Wehby, Joseph H.; Wills, Howard P. – Behavioral Disorders, 2014
Across the modern history of the field of special education and emotional/behavioral disorders (EBD), direct observation of student and educator behavior has been an essential component of the diagnostic process, student progress monitoring, and establishing functional and statistical relationships within research. This article provides an…
Descriptors: Student Behavior, Teacher Behavior, Observation, Educational Environment
Foy, Pierre, Ed.; Drucker, Kathleen T., Ed. – International Association for the Evaluation of Educational Achievement, 2013
This supplement contains documentation on all the derived variables contained in the PIRLS and prePIRLS 2011 data files that are based on background questionnaire variables. These variables were used to report background data in the PIRLS 2011 International Results in Reading report, and are made available as part of this database to be used in…
Descriptors: Databases, Data, Student Surveys, Teacher Surveys
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Chen, Chen-Su; Sable, Jennifer; Mitchell, Lindsey; Liu, Fei – National Center for Education Statistics, 2012
The Common Core of Data (CCD) nonfiscal surveys consist of data submitted annually to the National Center for Education Statistics (NCES) by state education agencies (SEAs) in the 50 states, the District of Columbia, Puerto Rico, the four U.S. Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin…
Descriptors: School Surveys, Documentation, State Surveys, Annual Reports
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Gleason, Sonia Caus – Journal of Staff Development, 2010
Consistent, excellent teaching is the single greatest factor in improving student achievement over time. School leadership is the second. Excellent teaching and strong leadership require deliberate, ongoing professional learning. In working with high-poverty school systems over time, the following basics emerge: (1) time; (2) content; (3)…
Descriptors: Teacher Effectiveness, Instructional Leadership, Predictor Variables, Academic Achievement