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Dorans, Neil J.; Moses, Tim P.; Eignor, Daniel R. – Educational Testing Service, 2010
Score equating is essential for any testing program that continually produces new editions of a test and for which the expectation is that scores from these editions have the same meaning over time. Particularly in testing programs that help make high-stakes decisions, it is extremely important that test equating be done carefully and accurately.…
Descriptors: Equated Scores, Methods, Data Collection, Data Processing
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Rees, Malcolm – Journal of Institutional Research, 2014
This paper reports on progress to date with a project underway in New Zealand involving the extraction of data from multiple government agencies that is then combined into one comprehensive longitudinal integrated dataset and made available to trial participants in a way never previously thought possible. The dataset includes school leaver…
Descriptors: Foreign Countries, Data Collection, Data Analysis, Data Processing
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Gee, Kevin A. – American Journal of Evaluation, 2014
The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…
Descriptors: Longitudinal Studies, Data Analysis, Statistical Studies, Program Evaluation
Wei, Weiqi – ProQuest LLC, 2012
Subject selection is essential and has become the rate-limiting step for harvesting knowledge to advance healthcare through clinical research. Present manual approaches inhibit researchers from conducting deep and broad studies and drawing confident conclusions. High-throughput clinical phenotyping (HTCP), a recently proposed approach, leverages…
Descriptors: Health Services, Records (Forms), Medical Evaluation, Electronic Publishing
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Valsamidis, Stavros; Kontogiannis, Sotirios; Kazanidis, Ioannis; Theodosiou, Theodosios; Karakos, Alexandros – Educational Technology & Society, 2012
Learning Management Systems (LMS) collect large amounts of data. Data mining techniques can be applied to analyse their web data log files. The instructors may use this data for assessing and measuring their courses. In this respect, we have proposed a methodology for analysing LMS courses and students' activity. This methodology uses a Markov…
Descriptors: Foreign Countries, Electronic Learning, College Mathematics, Integrated Learning Systems
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Rodriguez, Sheila M.; Estacion, Angela – Regional Educational Laboratory Northeast & Islands, 2014
As the name indicates, the College Readiness Data Catalog Tool focuses on identifying data that can indicate a student's college readiness. While college readiness indicators may also signal career readiness, many states, districts, and other entities, including the U.S. Virgin Islands (USVI), do not systematically collect career readiness…
Descriptors: College Readiness, Data, Educational Indicators, Data Collection
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Nord, C.; Hicks, L.; Hoover, K.; Jones, M.; Lin, A.; Lyons, M.; Perkins, R.; Roey, S.; Rust, K.; Sickles, D. – National Center for Education Statistics, 2011
This user's guide documents the procedures used to collect, process, and summarize data from the 2009 High School Transcript Study (HSTS 2009). Chapters detail the sampling of schools and graduates (chapters 2 and 3), data collection procedures (chapter 4), data processing procedures (chapter 5), and weighting procedures (chapter 6). Chapter 7…
Descriptors: High School Graduates, Academic Records, National Competency Tests, Questionnaires
Koh, Byungwan – ProQuest LLC, 2011
The advent of information technology has enabled firms to collect significant amounts of data about individuals and mine the data for developing their strategies. Profiling of individuals is one common use of data collected about them. It refers to using known or inferred information to categorize the type of an individual and to tailor specific…
Descriptors: Screening Tests, Program Effectiveness, Information Technology, Data Collection
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Sangasubana, Nisaratana – Qualitative Report, 2011
The purpose of this paper is to describe the process of conducting ethnographic research. Methodology definition and key characteristics are given. The stages of the research process are described including preparation, data gathering and recording, and analysis. Important issues such as reliability and validity are also discussed.
Descriptors: Student Research, Ethnography, Research Methodology, Data Analysis
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Levy, Sharona T.; Wilensky, Uri – Computers & Education, 2011
This study lies at an intersection between advancing educational data mining methods for detecting students' knowledge-in-action and the broader question of how conceptual and mathematical forms of knowing interact in exploring complex chemical systems. More specifically, it investigates students' inquiry actions in three computer-based models of…
Descriptors: Test Content, Mathematical Models, Prior Learning, Data Processing
Zhu, Zutao – ProQuest LLC, 2010
In recent years, the concerns about the privacy for the electronic data collected by government agencies, organizations, and industries are increasing. They include individual privacy and knowledge privacy. Privacy-preserving data publishing is a research branch that preserves the privacy while, at the same time, withholding useful information in…
Descriptors: Public Agencies, Models, Data Collection, Vignettes
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Loh, Christian Sebastian – International Journal of Virtual and Personal Learning Environments, 2013
Today's economic situation demands that learning organizations become more diligent in their business dealings to reduce cost and increase bottom line for survival. While there are many champions and proponents claiming that game-based learning (GBL) is sure to improve learning, researchers have, thus far, been unable to (re)produce concrete,…
Descriptors: Investment, Outcomes of Education, Educational Games, Instructional Improvement
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Koyama, Jill P. – Journal of Education Policy, 2011
This article ethnographically examines the ways in which No Child Left Behind (NCLB) links local practices to the centralized processing of data through its narrowing of procedures and measurements aimed at accountability. Framed by actor-network theory, it draws upon data consistently collected between June 2005 and October 2008, and then…
Descriptors: Federal Legislation, Ethnography, Accountability, Data Collection
Welker, Josh – Computers in Libraries, 2012
Any librarian who has managed electronic resources has experienced the--for want of words--"joy" of gathering and analyzing usage statistics. Such statistics are important for evaluating the effectiveness of resources and for making important budgeting decisions. Unfortunately, the data are usually tedious to collect, inconsistently organized, of…
Descriptors: Library Services, Databases, Academic Libraries, Electronic Libraries
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Mathies, Charles; Valimaa, Jussi – Tertiary Education and Management, 2013
Recent changes in European higher education have accompanied a strong desire and need by national ministries to have comparable data across institutions and a growing recognition from campus leaders that effective planning and decision-making requires reliable institutional data and analyses. This has induced changes and restructuring of duties…
Descriptors: Higher Education, Institutional Evaluation, Governance, Data Analysis
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