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Aruguete, Mara S.; Huynh, Ho; Browne, Blaine L.; Jurs, Bethany; Flint, Emilia; McCutcheon, Lynn E. – International Journal of Social Research Methodology, 2019
This study compared the quality of survey data collected from Mechanical Turk (MTurk) workers and college students. Three groups of participants completed the same survey. "MTurk" respondents completed the survey as paid workers using the Mechanical Turk crowdsourcing platform. "Student Online" respondents also completed the…
Descriptors: Data Collection, Research Methodology, Sampling, College Students
Misato Hiraga – ProQuest LLC, 2024
This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…
Descriptors: Japanese, Computational Linguistics, Form Classes (Languages), Error Analysis (Language)
Ellison, George T. H. – Journal of Statistics and Data Science Education, 2021
Temporality-driven covariate classification had limited impact on: the specification of directed acyclic graphs (DAGs) by 85 novice analysts (medical undergraduates); or the risk of bias in DAG-informed multivariable models designed to generate causal inference from observational data. Only 71 students (83.5%) managed to complete the…
Descriptors: Statistics Education, Medical Education, Undergraduate Students, Graphs
Arzumanyan, George; Halcoussis, Dennis; Phillips, G. Michael – American Journal of Business Education, 2015
This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small…
Descriptors: Business Administration Education, Error of Measurement, Error Patterns, Intervals
Liu, Qin – Association for Institutional Research, 2012
This discussion constructs a survey data quality strategy for institutional researchers in higher education in light of total survey error theory. It starts with describing the characteristics of institutional research and identifying the gaps in literature regarding survey data quality issues in institutional research and then introduces the…
Descriptors: Institutional Research, Higher Education, Quality Control, Researchers
Karadag, Engin – Education, 2010
In this research, the level of quality of the qualitative research design used and the analytic mistakes made in the doctorate dissertations carried out in the field of education science in Turkey have been tried to be identified. Case study design has been applied in the study in which qualitative research techniques have been used. The universe…
Descriptors: Foreign Countries, Research Design, Qualitative Research, Educational Research
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
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
Yu, Lei; Moses, Tim; Puhan, Gautam; Dorans, Neil – ETS Research Report Series, 2008
All differential item functioning (DIF) methods require at least a moderate sample size for effective DIF detection. Samples that are less than 200 pose a challenge for DIF analysis. Smoothing can improve upon the estimation of the population distribution by preserving major features of an observed frequency distribution while eliminating the…
Descriptors: Test Bias, Item Response Theory, Sample Size, Evaluation Criteria