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Jamelia Harris – Field Methods, 2024
Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…
Descriptors: Foreign Countries, Sample Size, Surveys, Computation
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Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2022
The authors discuss the use of surveys for collecting data from a population sample and emphasise the importance of being careful with the language of data collection. [For "The Data Files 5: Graphs for Exploring Relationships," see EJ1355504.]
Descriptors: Surveys, Data Collection, Statistics Education, Foreign Countries
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Beth Chance; Andrew Kerr; Jett Palmer – Journal of Statistics and Data Science Education, 2024
While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…
Descriptors: Publications, Public Opinion, Surveys, Bias
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Matthew J. Mayhew; Christa E. Winkler – Journal of Postsecondary Student Success, 2024
Higher education professionals often are tasked with providing evidence to stakeholders that programs, services, and practices implemented on their campuses contribute to student success. Furthermore, in the absence of a solid base of evidence related to effective practices, higher education researchers and practitioners are left questioning what…
Descriptors: Higher Education, Educational Practices, Evidence Based Practice, Program Evaluation
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Shen, Ting; Konstantopoulos, Spyros – Practical Assessment, Research & Evaluation, 2022
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…
Descriptors: Sampling, Weighted Scores, Hierarchical Linear Modeling, Educational Research
Katrina Boone; Ebony Lambert – National Comprehensive Center, 2020
CCNetwork, in many cases, begins their work by assessing client needs--speaking with clients, examining current evidence and data, reviewing documents, and identifying patterns across those. Needs-sensing methods are important inputs to helping shape and prioritize what CCNetwork does. Landscape scans take these efforts a bit further by helping to…
Descriptors: Networks, Needs Assessment, Planning, Data Collection
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Link, Michael – Quality Assurance in Education: An International Perspective, 2018
Purpose: Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches -- in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and…
Descriptors: Sampling, Data Collection, Trend Analysis, Data
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Hustedt, Beth; Franklin, Jeff; Tate, Nicole – New Directions for Institutional Research, 2019
We discuss methods that can improve response rates in large-scale cross-sectional and longitudinal studies. Regardless of the specific study topic, sample member population, or method of contact, data collections should be designed with certain core principles in mind: legitimizing the study to prospective participants; presenting study…
Descriptors: Data Collection, Longitudinal Studies, Surveys, Response Rates (Questionnaires)
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Fellers, Pamela S.; Kuiper, Shonda – Journal of Statistics Education, 2020
Increasingly students, particularly those in the social sciences, work with survey data collected through a more complex sampling method than a simple random sample. Failing to understand how to properly approach survey data can lead to inaccurate results. In this article, we describe a series of online data visualization applications and…
Descriptors: Statistics, Introductory Courses, Teaching Methods, Concept Formation
European Commission, 2019
The 2nd Survey of Schools: ICT in Education has two objectives: 1) Objective 1: Benchmark progress in ICT in Schools - to provide detailed and up-to-date information related to access, use and attitudes towards the use of technology in education by surveying head teachers, teachers, students and parents covering the EU28, Norway, Iceland and…
Descriptors: Information Technology, Computer Uses in Education, Technology Integration, Access to Computers
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Hazel, Cynthia E.; Newman, Daniel S.; Barrett, Courtenay A. – Journal of Educational & Psychological Consultation, 2016
The evidence base for school-based consultation practice and training is limited by a small number of studies, possibly due to unique challenges in researching consultation. For example, there are myriad variables to measure and idiosyncratic cultural and contextual factors to account for when investigating what works, for whom, and in what…
Descriptors: Consultation Programs, Surveys, Research, School Activities
Bernstein, Sara; Dang, Myley; Li, Ann; Klein, Ashley Kopack; Reid, Natalie; Blesson, Elizabeth; Cannon, Judy; Harrington, Jeff; Larson, Addison; Aikens, Nikki; Tarullo, Louisa; Malone, Lizabeth – Administration for Children & Families, 2021
Since 1997, the Head Start Family and Child Experiences Survey (FACES) has been a major source of information on the Head Start program and the preschool children ages 3 to 5 who attend the program. As part of its management of Head Start, the federal government divides Head Start programs into 12 regions. Regions XI and XII are not based on…
Descriptors: Preschool Education, Disadvantaged Youth, Surveys, Preschool Children
Dang, Myley; Bernstein, Sara; Doran, Elizabeth; Li, Ann; Klein, Ashley Kopack; Reid, Natalie; Scott, Myah; Rakibullah, Sharika; Cannon, Judy; Harrington, Jeff; Larson, Addison; Aikens, Nikki; Tarullo, Louisa; Malone, Lizabeth – Administration for Children & Families, 2021
Since 1997, the Head Start Family and Child Experiences Survey (FACES) has been a major source of information on the Head Start program and the preschool children ages 3 to 5 who attend the program. As part of its management of Head Start, the federal government divides Head Start programs into 12 regions. Regions XI and XII are not based on…
Descriptors: Preschool Education, Disadvantaged Youth, Surveys, Preschool Children
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Quinn, Anne; Larson, Karen – Mathematics Teacher, 2016
Consistent with the Common Core State Standards for Mathematics (CCSSI 2010), the authors write that they have asked students to do statistics projects with real data. To obtain real data, their students use the free Web-based app, Census at School, created by the American Statistical Association (ASA) to help promote civic awareness among school…
Descriptors: Statistical Analysis, Technology Uses in Education, Mathematics Instruction, Statistics
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Olpak, Yusuf Ziya; Yagci, Mustafa; Basarmak, Ugur – Educational Research and Reviews, 2016
Community of inquiry (CoI) is the conceptual framework which describes critical prerequisite factors for deep and meaningful learning in online learning environments. Based on the literature concerning the CoI framework, it can be observed that studies in which three factors in the model (cognitive, social and teaching presence) were investigated…
Descriptors: Foreign Countries, Electronic Learning, Data Collection, Surveys
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