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Polak, Julia; Cook, Dianne – Journal of Statistics and Data Science Education, 2021
Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…
Descriptors: Artificial Intelligence, Data Analysis, Models, Competition
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Schwab-McCoy, Aimee; Baker, Catherine M.; Gasper, Rebecca E. – Journal of Statistics and Data Science Education, 2021
In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…
Descriptors: Statistics Education, Higher Education, College Students, Teaching Methods
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Gibson, Patrick; Robles, Ashley – Center for Learner Equity, 2021
This technical brief is part of an ongoing series the Center for Learner Equity (CLE) launched in 2015 that examines the enrollment and experiences of students with disabilities in different school settings. Using the 2017-2018 Civil Rights Data Collection (CRDC) data released earlier this year, this brief focuses on the number and percentages of…
Descriptors: Students with Disabilities, Charter Schools, Public Schools, Data Analysis
Clifford, Richard M.; Yazejian, Noreen; Jang, Wonkyung; Jigjidsuren, Dari – Teachers College Press, 2021
Early childhood is a crucial stage in a child's life, and aspects of the environment in the physical, social-emotional, cognitive, and health and safety domains all play important roles in shaping children's development during these early years. Having a valid and reliable measure of the quality of these aspects of children's care settings is…
Descriptors: Early Childhood Education, Data Analysis, Data Interpretation, Educational Quality
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Windeyer, Richard C. – Research in Drama Education, 2019
As information literacy and data-driven program evaluations have become growing obsessions within academic institutions, how might liberal arts and humanities programmes engage students in both critical and creative explorations of contemporary human-data relations? Inspired by the variety of metaphors that currently shape human-data relations and…
Descriptors: Information Literacy, Theater Arts, Liberal Arts, Humanities
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Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2019
Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of…
Descriptors: Reliability, Longitudinal Studies, Growth Models, Structural Equation Models
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Lougheed, Jessica P.; Benson, Lizbeth; Cole, Pamela M.; Ram, Nilam – Developmental Psychology, 2019
The timing of events (e.g., how long it takes a child to exhibit a particular behavior) is often of interest in developmental science. Multilevel survival analysis (MSA) is useful for examining behavioral timing in observational studies (i.e., video recordings) of children's behavior. We illustrate how MSA can be used to answer 2 types of research…
Descriptors: Time, Child Behavior, Psychological Patterns, Data Analysis
Public School Forum of North Carolina, 2019
Each year, policymakers, educators, and the general public engage in debates around the statewide average teacher pay figure that the North Carolina Department of Public Instruction (DPI) publishes on its website and reports to the National Education Association. These debates take up the important consideration of whether or not teachers are…
Descriptors: Teacher Salaries, Data Analysis, School Districts, Poverty
Fesler, Lily; Dee, Thomas; Baker, Rachel; Evans, Brent – Stanford Center for Education Policy Analysis, 2019
Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this paper, we review the recent automated text methods relevant to educational…
Descriptors: Educational Research, Data Analysis, Automation, Methods
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Kayleigh K. Hyde; Marlena N. Novack; Nicholas LaHaye; Chelsea Parlett-Pelleriti; Raymond Anden; Dennis R. Dixon; Erik Linstead – Review Journal of Autism and Developmental Disorders, 2019
Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Clinical Diagnosis, Intervention
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Kardes, Servet – International Journal of Progressive Education, 2020
The purpose of this study is to examine the abstracts in 6th International Preschool Education Congress abstract book in terms of research subject, method, model, sample type, data collection tools, data analysis techniques, validity and reliability. This study is a qualitative study and was conducted using document analysis, which is one of the…
Descriptors: Preschool Education, Educational Research, Research Methodology, Data Collection
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Walters, Courtney E.; Nitin, Rachana; Margulis, Katherine; Boorom, Olivia; Gustavson, Daniel E.; Bush, Catherine T.; Davis, Lea K.; Below, Jennifer E.; Cox, Nancy J.; Camarata, Stephen M.; Gordon, Reyna L. – Journal of Speech, Language, and Hearing Research, 2020
Purpose: Data mining algorithms using electronic health records (EHRs) are useful in large-scale population-wide studies to classify etiology and comorbidities (Casey et al., 2016). Here, we apply this approach to developmental language disorder (DLD), a prevalent communication disorder whose risk factors and epidemiology remain largely…
Descriptors: Language Impairments, Developmental Disabilities, Automation, Disability Identification
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Larkan-Skinner, Kara; Shedd, Jessica M. – New Directions for Institutional Research, 2020
As institutions seek to shift into more advanced analytics and data-based decision-support, many institutional research offices face the challenge of meeting the office's current demands while taking on more intricate and specialized work to support decision-making. Given the great need organizations have for information that supports real-time…
Descriptors: Data, Data Analysis, Prediction, Data Use
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Adnan, Muhamad Hariz Muhamad; Ariffin, Shamsul Arrieya; Hanafi, Hafizul Fahri; Husain, Mohd Shahid; Panessai, Ismail Yusuf – Asian Journal of University Education, 2020
Recently, the promotion of science, technology, engineering and mathematics (STEM) education has become the highlight due to the shortage in the STEM workforce. Surprisingly, the enrolment rates in STEM degrees are still low in many countries. Social media has been identified as one of the main platforms that can help to increase prospective…
Descriptors: Social Media, College Bound Students, STEM Education, Vocational Education
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Yildiz, Muhammed Berke; Börekci, Caner – Journal of Educational Technology and Online Learning, 2020
Education systems produce a large number of valuable data for all stakeholders. The processing of these educational data and making studies on the future of education based on the data reveal highly meaningful results. In this study, an insight was tried to be developed on the educational data collected from ninth-grade students by using data…
Descriptors: Grade Prediction, Academic Achievement, Artificial Intelligence, Grade 9
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