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Frank Lee; Alex Algarra – Information Systems Education Journal, 2024
Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that…
Descriptors: Visual Aids, Data Use, Data Collection, Naming
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Knipe, Sally – Educational Practice and Theory, 2022
This article presents a descriptive, critical analysis of the comparability of information concerning students, teachers, and school resources gathered by organisations within government jurisdiction, and the pitfalls for the unwary researcher using government data banks. Differences in the method of compiling information about citizens, and…
Descriptors: Educational Research, Educational Researchers, Data Collection, Data Analysis
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Loy, Adam; Kuiper, Shonda; Chihara, Laura – Journal of Statistics Education, 2019
This article describes a collaborative project across three institutions to develop, implement, and evaluate a series of tutorials and case studies that highlight fundamental tools of data science--such as visualization, data manipulation, and database usage--that instructors at a wide-range of institutions can incorporate into existing statistics…
Descriptors: Undergraduate Study, Data Collection, Data Analysis, Statistics
Sinani, Sara; Edora, Fred – Center for the Integration of IDEA Data, 2018
High-quality data is essential when looking at student-level data, including data specifically focused on students with disabilities. For state education agencies (SEAs), it is critical to have a solid foundation for how data is collected and stored to achieve high-quality data. The process of integrating the Individuals with Disabilities…
Descriptors: State Departments of Education, Databases, Information Systems, Educational Legislation
DeBaun, Bill; Cook, Kendall E. – National College Access Network, 2017
National College Access Network (NCAN) has heard repeatedly and consistently over the years that one of the best aspects of network membership is the ability to collaborate with and learn from other members. In an effort to further the transfer of ideas, in the summer of 2016 NCAN hosted a series of four Idea Incubators across the country, which…
Descriptors: Databases, Information Storage, Data Collection, Student Records
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Bonnéry, Daniel; Feng, Yi; Henneberger, Angela K.; Johnson, Tessa L.; Lachowicz, Mark; Rose, Bess A.; Shaw, Terry; Stapleton, Laura M.; Woolley, Michael E.; Zheng, Yating – Journal of Research on Educational Effectiveness, 2019
There is demand among policy-makers for the use of state education longitudinal data systems, yet laws and policies regulating data disclosure limit access to such data, and security concerns and risks remain high. Well-developed synthetic datasets that statistically mimic the relations among the variables in the data from which they were derived,…
Descriptors: Data Collection, Access to Information, Privacy, Information Dissemination
Fraillon, Julian, Ed.; Ainley, John, Ed.; Schulz, Wolfram, Ed.; Friedman, Tim, Ed.; Duckworth, Daniel, Ed. – International Association for the Evaluation of Educational Achievement, 2020
IEA's International Computer and Information Literacy Study (ICILS) 2018 investigated how well students are prepared for study, work, and life in a digital world. ICILS 2018 measured international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and communicate at…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Assisted Testing
Gosa, Kathy; Huennekens, Bill – Center for the Integration of IDEA Data, 2015
This brief provides a definition of an integrated data system, identifies who would benefit from the information provided by an integrated data system, and examines the challenges and costs associated with data integration, as well as potential benefits to creating an integrated data system. [The Center for the Integration of IDEA Data (CIID) is…
Descriptors: Information Management, Database Management Systems, Databases, Decision Making
Jabour, Abdulrahman M. – ProQuest LLC, 2016
Introduction: Cancer registries collect tumor-related data to monitor incident rates and support population-based research. A common concern with using population-based registry data for research is reporting timeliness. Data timeliness have been recognized as an important data characteristic by both the Centers for Disease Control and Prevention…
Descriptors: Cancer, Data Collection, Information Management, Databases
Perry, Angela – Project on Student Debt, 2019
California has long been a national and global leader in developing and maintaining quality higher education options, as well as in providing financial aid and consumer protections for Californians who access that education. However, although California's colleges and the state government do collect, receive, and report a great deal of data, these…
Descriptors: Education Work Relationship, Access to Information, Wages, Data Collection
Lang, Leah; Pirani, Judith A. – EDUCAUSE, 2014
This Spotlight focuses on data from the 2013 Core Data Service [CDS] to better understand how higher education institutions approach business intelligence (BI) reporting and data warehouse systems (see the Sidebar for definitions). Information provided for this Spotlight was derived from Module 8 of CDS, which contains several questions regarding…
Descriptors: Colleges, Business, Information Systems, Interviews
Spielberger, Julie; Axelrod, Jennifer; Dasgupta, Denali; Cerven, Christine; Spain, Angeline; Kohm, Amelia; Mader, Nicholas – Chapin Hall at the University of Chicago, 2016
To support the effectiveness of afterschool programs in fostering skills youth need to succeed in school and life, a growing number of cities have invested in afterschool systems to coordinate disparate programs and funding streams. A primary function of most afterschool systems is to develop and maintain a data system to collect, analyze, and…
Descriptors: After School Programs, Youth Programs, Skill Development, Data Collection
Spielberger, Julie; Axelrod, Jennifer; Dasgupta, Denali; Cerven, Christine; Spain, Angeline; Kohm, Amelia; Mader, Nicholas – Chapin Hall at the University of Chicago, 2016
To support the effectiveness of afterschool programs in fostering skills youth need to succeed in school and life, a growing number of cities have invested in afterschool systems to coordinate disparate programs and funding streams. A primary function of most afterschool systems is to develop and maintain a data system to collect, analyze, and…
Descriptors: After School Programs, Youth Programs, Skill Development, Data Collection
Martha, VenkataSwamy – ProQuest LLC, 2013
Networks, such as social networks, are a universal solution for modeling complex problems in real time, especially in the Big Data community. While previous studies have attempted to enhance network processing algorithms, none have paved a path for the development of a persistent storage system. The proposed solution, GraphStore, provides an…
Descriptors: Networks, Information Storage, Graphs, Statistical Data
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Penuel, William R.; Means, Barbara – American Journal of Evaluation, 2011
Major advances in the number, capabilities, and quality of state, national, and transnational databases have opened up new opportunities for evaluators. Both large-scale data sets collected for administrative purposes and those collected by other researchers can provide data for a variety of evaluation-related activities. These include (a)…
Descriptors: Data Collection, Data Analysis, Program Evaluation, Evaluators
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