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Victoria Reyes; Elizabeth Bogumil; Levin Elias Welch – Sociological Methods & Research, 2024
Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we've collected. Although there are a few exceptions, less focus is on transparency regarding…
Descriptors: Qualitative Research, Data Analysis, Guides, Databases
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Sneed, Stacey; Nguyen, Chau H. P.; Eubank, Chrissy L. – International Journal of Adult Education and Technology, 2020
Case study has been one of the most often used qualitative research methodologies in the field of education at all levels -- from preschool to adult. Yet the number of available resources for case study researchers--be they emerging or experienced--is still limited. This paper will review the definition of the case study method as well as some of…
Descriptors: Case Studies, Research Methodology, Qualitative Research, Educational Research
Smith, Brent; Milham, Laura – Advanced Distributed Learning Initiative, 2021
Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…
Descriptors: Learning Analytics, Computer Software, Metadata, Learning Activities
Maldonado, Monica; Mugglestone, Konrad; Roberson, Amanda Janice – Institute for Higher Education Policy, 2021
Data-informed decision-making has always been -- and always will be -- a smart approach to policy, including at institutions of higher education. Just over one year since the COVID-19 pandemic radically and abruptly shifted every aspect of higher education, states and institutions are tackling the same student success goals as before, but with…
Descriptors: Data Analysis, Learning Analytics, Decision Making, Higher Education
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Makela, Carole J. – Journal of Family and Consumer Sciences, 2016
"Big data" prompts a whole lexicon of terms--data flow; analytics; data mining; data science; smart you name it (cars, houses, cities, wearables, etc.); algorithms; learning analytics; predictive analytics; data aggregation; data dashboards; digital tracks; and big data brokers. New terms are being coined frequently. Are we paying…
Descriptors: Data Analysis, Information Utilization, Data Collection, Consumer Science
Lohrer, Johannes-Y.; Kaltenthaler, Daniel; Kröger, Peer – International Association for Development of the Information Society, 2016
In this paper, we describe a framework for data analysis that can be embedded into a base application. Since it is important to analyze the data directly inside the application where the data is entered, a tool that allows the scientists to easily work with their data, supports and motivates the execution of further analysis of their data, which…
Descriptors: Data Analysis, Expertise, Models, Evaluation Methods
Data Quality Campaign, 2014
Regular attendance is essential to succeeding in school, and chronic absence--missing excessive amounts of school for any reason--can cause students to be off track academically. Developed in partnership with Attendance Works, this fact sheet analyzes data from the "Data for Action 2013" survey to discuss how states use data to monitor…
Descriptors: Attendance, Success, Academic Achievement, State Action
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Dynarski, Mark; Kisker, Ellen – National Center for Education Evaluation and Regional Assistance (NCEE), 2014
Communicating complex concepts to practitioners, policymakers, and other nontechnical readers is a challenge that all policy researchers face. Research in education uses many concepts from methodology and statistics. If researchers want to communicate their findings to an audience of other researchers, they can safely assume that their audience is…
Descriptors: Research Reports, Concept Formation, Information Dissemination, Language Usage
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Pence, Harry E. – Journal of Educational Technology Systems, 2014
Big Data Analytics is a topic fraught with both positive and negative potential. Big Data is defined not just by the amount of information involved but also its variety and complexity, as well as the speed with which it must be analyzed or delivered. The amount of data being produced is already incredibly great, and current developments suggest…
Descriptors: Data Analysis, Data Collection, Privacy, Definitions
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Watson, Jane M. – Australian Mathematics Teacher, 2012
This article compares the definition of "box plot" as used in the "Australian Curriculum: Mathematics" with other definitions used in the education community; describes the difficulties students experience when dealing with box plots; and discusses the elaboration that is necessary to enable teachers to develop the knowledge…
Descriptors: Foreign Countries, Probability, Data Analysis, Mathematics Curriculum
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Little, Mary E. – Educational Forum, 2012
The purpose of this article is to define and clarify the process of instructional problem-solving using assessment data within action research (AR) and Response to Intervention (RtI). Similarities between AR and RtI are defined and compared. Lastly, specific resources and examples of the instructional problem-solving process of AR within…
Descriptors: Intervention, Action Research, Problem Solving, Data Analysis
Picciano, Anthony G. – Journal of Asynchronous Learning Networks, 2012
Data-driven decision making, popularized in the 1980s and 1990s, is evolving into a vastly more sophisticated concept known as big data that relies on software approaches generally referred to as analytics. Big data and analytics for instructional applications are in their infancy and will take a few years to mature, although their presence is…
Descriptors: Higher Education, Decision Making, Data, Data Analysis
Stuart-Cassel, Victoria; Terzian, Mary; Bradshaw, Catherine – National Center on Safe Supportive Learning Environments, 2013
Bullying is considered one of the most prevalent and potentially damaging forms of school violence. Each year, more than a quarter of middle and high school students are subjected to some form of bullying in their school environments. Research has identified potentially harmful immediate and long-term consequences for bullying-involved youth and…
Descriptors: Bullying, Aggression, Definitions, Educational Environment
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Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2013
The 2012 edition of the "Digest of Education Statistics" is the 48th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: School Statistics, Definitions, Tables (Data), Longitudinal Studies
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Snyder, Thomas D.; Dillow, Sally A. – National Center for Education Statistics, 2012
The 2011 edition of the "Digest of Education Statistics" is the 47th in a series of publications initiated in 1962. The "Digest" has been issued annually except for combined editions for the years 1977-78, 1983-84, and 1985-86. Its primary purpose is to provide a compilation of statistical information covering the broad field…
Descriptors: Educational Research, Data Collection, Data Analysis, Error Patterns
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