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Yaosheng Lou; Kimberly F. Colvin – Discover Education, 2025
Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…
Descriptors: Educational Research, Data Collection, Performance, Prediction
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Shiyu Zhang; James Wagner – Sociological Methods & Research, 2024
Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the…
Descriptors: Surveys, Research Design, Response Rates (Questionnaires), Demography
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Hussain, Sadiq; Gaftandzhieva, Silvia; Maniruzzaman, Md.; Doneva, Rositsa; Muhsin, Zahraa Fadhil – Education and Information Technologies, 2021
Educational data mining helps the educational institutions to perform effectively and efficiently by exploiting the data related to all its stakeholders. It can help the at-risk students, develop recommendation systems and alert the students at different levels. It is beneficial to the students, educators and authorities as a whole. Deep learning…
Descriptors: Regression (Statistics), Academic Achievement, Learning Analytics, Models
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Melissa Dan Wang – Large-scale Assessments in Education, 2025
Although self-report surveys are widely used for data collection, data quality can vary across populations because certain groups are more likely to engage in insufficient effort responding (IER). Our study examined how different levels of the educational system--student groups, schools, and cultural contexts--affect data quality due to IER, using…
Descriptors: Responses, Response Style (Tests), Questionnaires, Surveys
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Doleck, Tenzin; Lemay, David John; Basnet, Ram B.; Bazelais, Paul – Education and Information Technologies, 2020
Large swaths of data are readily available in various fields, and education is no exception. In tandem, the impetus to derive meaningful insights from data gains urgency. Recent advances in deep learning, particularly in the area of voice and image recognition and so-called complete knowledge games like chess, go, and StarCraft, have resulted in a…
Descriptors: Learning Analytics, Prediction, Information Retrieval, Accuracy
Daugherty, Lindsay; Anderson, Drew M. – RAND Corporation, 2021
This appendix supplements the report "Stackable Credential Pipelines in Ohio: Evidence on Programs and Earnings Outcomes" (ED613593). In the appendix, the authors provide more details about the data and empirical approach, additional information about the samples, and some alternative results from analyses related to those that appear in…
Descriptors: Credentials, Postsecondary Education, Research Methodology, Data Collection
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Anderson, Joe S.; Williams, Susan K. – Decision Sciences Journal of Innovative Education, 2019
In this project, students asked and attempted to answer questions about themselves by collecting and analyzing data. With the prevalence of big data and business analytics, managers have data and quantitative information available more immediately than ever. However, managers need to understand how to use this information. In this project,…
Descriptors: Data Collection, Data Analysis, Student Projects, Experiential Learning
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Kastberg, David; Murray, Gordon; Ferraro, David; Arieira, Carlos; Roey, Shep; Mamedova, Saida; Liao, Yuqi – National Center for Education Statistics, 2021
The Program for International Student Assessment Young Adult Follow-up Study (PISA YAFS) is a follow-up study with students who participated in PISA 2012 in the United States. The study is designed to measure how performance on PISA 2012 relates to subsequent measures of outcomes and skills of young adults on an online assessment, Education and…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, Young Adults
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Aksu, Gokhan; Reyhanlioglu Keceoglu, Cigdem – Eurasian Journal of Educational Research, 2019
Purpose: In this study, Logistic Regression (LR), CHAID (Chi-squared Automatic Interaction Detection) analysis and data mining methods are used to investigate the variables that predict the mathematics success of the students. Research Methods: In this study, a quantitative research design was employed during the data collection and the analysis…
Descriptors: Regression (Statistics), Data Collection, Information Retrieval, Predictor Variables
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Sinharay, Sandip – Educational Measurement: Issues and Practice, 2016
Data mining methods for classification and regression are becoming increasingly popular in various scientific fields. However, these methods have not been explored much in educational measurement. This module first provides a review, which should be accessible to a wide audience in education measurement, of some of these methods. The module then…
Descriptors: Data Collection, Information Retrieval, Classification, Regression (Statistics)
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Khan, Alamgir; Khan, Salahuddin; Zia-Ul-Islam, Syed; Khan, Manzoor – Journal of Education and Practice, 2017
Basically the current study sought to assess the perception of students regarding the role of teacher communication skills in their academics success. Comprehensive questionnaire carrying information including social economic and demographic aspects of the study was designed by the researcher to achieve the set objectives. All those universities…
Descriptors: Foreign Countries, Physical Education Teachers, Communication Skills, College Faculty
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Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
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Myers, Carrie B.; Myers, Scott M. – Research & Practice in Assessment, 2017
Previous studies have found that freshmen who enter college with dual enrollment credits earned during high school have higher 6-year graduation rates. Yet, we do not know if institutional graduation rates benefit in the aggregate from their practice of accepting dual enrollment credits among incoming freshman cohorts. In this study, we used…
Descriptors: Undergraduate Students, College Graduates, Graduation Rate, Dual Enrollment
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Hughes, John; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2016
The high rate of students taking developmental education courses suggests that many students graduate from high school unready to meet college expectations. A college readiness screener can help colleges and school districts better identify students who are not ready for college credit courses. The primary audience for this guide is leaders and…
Descriptors: College Readiness, Screening Tests, Test Construction, Predictor Variables
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Buelens, Bart; van den Brakel, Jan A. – Sociological Methods & Research, 2015
Mixed-mode surveys are known to be susceptible to mode-dependent selection and measurement effects, collectively referred to as mode effects. The use of different data collection modes within the same survey may reduce selectivity of the overall response but is characterized by measurement errors differing across modes. Inference in sample surveys…
Descriptors: Error of Measurement, Surveys, Crime, Victims
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