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Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
Conzemius, Anne – Journal of Staff Development, 2012
This article discusses five generally accepted reasons to use data as a part of an educator's ongoing professional practice. Of course, there are many other more specific reasons one might look at data, but these five cover the overarching need in an educational setting. The five major purposes for using data are: (1) To enhance understanding and…
Descriptors: Data Analysis, Teaching (Occupation), Educational Practices, Perspective Taking
Sam, Sonn – ProQuest LLC, 2011
The purpose of this quantitative study was to investigate how Rhode Island high school principals rate success in implementing 21st century skills in their schools. Secondly, this study investigated how high school principals rate the influence of implementing of 21st century skills in curriculum and instruction in their schools. The high…
Descriptors: Principals, Critical Thinking, Thinking Skills, Problem Solving
Guo, Zhen – ProQuest LLC, 2010
A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…
Descriptors: Artificial Intelligence, Man Machine Systems, Probability, Data
Corwin, Rebecca B.; Russell, Susan Jo – 1990
A unit of study that introduces measuring as a way of collecting data is presented. Suitable for students in grades 3 and 4, it provides a foundation for further work in statistics and data analysis. The investigations may extend from one to four class sessions and are grouped into three parts: "Introduction to Measurement"; "Using Standard…
Descriptors: Calculators, Computer Assisted Instruction, Cooperative Learning, Data Analysis

Young, Sharon L. – Arithmetic Teacher, 1991
Presented are activities that focus on gathering, using, and interpreting data about fingerprints as a basis for integrating mathematics and science. Patterns, classification, logical reasoning, and mathematical relationships are explored by making graphs, classifying fingerprints, and matching identical fingerprints. A parent-involvement activity…
Descriptors: Classification, Data Analysis, Elementary Education, Elementary School Mathematics
Burton, Grace; And Others – 1992
The 1989 document, "Curriculum and Evaluation Standards for School Mathematics," provides a vision and a framework for revising and strengthening the K-12 mathematics curriculum in North American schools and for evaluating both the mathematics curriculum and students' progress. This book, one in a series designed to interpret and…
Descriptors: Computer Assisted Instruction, Curriculum Enrichment, Data Analysis, Discovery Learning
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers