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West Virginia Department of Education, 2024
The purpose of this Executive Summary and the full report is to summarize the results and technical analyses performed with the Spring 2024 "Artificial Intelligence in Education: West Virginia Stakeholder Survey", which was used to collect stakeholder feedback related to perceptions of using artificial intelligence (AI) in education. The…
Descriptors: Artificial Intelligence, Technology Uses in Education, Stakeholders, Public Education
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Autenrieth, Maximilian; Levine, Richard A.; Fan, Juanjuan; Guarcello, Maureen A. – Journal of Educational Data Mining, 2021
Propensity score methods account for selection bias in observational studies. However, the consistency of the propensity score estimators strongly depends on a correct specification of the propensity score model. Logistic regression and, with increasing popularity, machine learning tools are used to estimate propensity scores. We introduce a…
Descriptors: Probability, Artificial Intelligence, Educational Research, Statistical Bias
Holly Kurtz; Sterling Lloyd; Alex Harwin; Rachel Gong; Taylor Nichols – Editorial Projects in Education, 2024
In today's world, technology is ubiquitous and rapidly evolving. As it evolves and new challenges emerge, educators will be tasked with teaching students about healthy and responsible management of their online lives. From late December 2023 to early January 2024, the EdWeek Research Center conducted a survey of teachers, school leaders, and…
Descriptors: Student Welfare, Technology, Influence of Technology, Social Media
Kurtz, Holly; Lloyd, Sterling; Harwin, Alex; Daniels, Ashlee; Cheseldine, Sarah – Editorial Projects in Education, 2023
In a trend buoyed by new technology purchased to accommodate the remote learning necessitated by the coronavirus pandemic, educators are increasingly using devices and apps to teach core subjects, including math. This report examines perceptions and experiences of teachers, principals, and district leaders around the use of such tools for math…
Descriptors: Educational Technology, Technology Uses in Education, Mathematics Instruction, Teacher Attitudes
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Sarsa, Sami; Leinonen, Juho; Hellas, Arto – Journal of Educational Data Mining, 2022
New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Memory
Greene Nolan, Hillary; Vang, Mai Chou – Digital Promise, 2023
Providing feedback to students in a sustainable way represents a perennial challenge for secondary teachers of writing. Employing artificial intelligence (AI) tools to give students personalized and immediate feedback holds great promise. Project Topeka offered middle school teachers pre-curated teaching materials, foundational texts and videos,…
Descriptors: Middle School Students, Grade 7, Grade 8, Predictor Variables
Kopack Klein, Ashley; Aikens, Nikki; Li, Ann; Bernstein, Sara; Reid, Natalie; Dang, Myley; Blesson, Elizabeth; Rakibullah, Sharikah; Scott, Myah; Cannon, Judy; Harrington, Jeff; Larson, Addison; Malone, Lizabeth; Tarullo, Louisa – Administration for Children & Families, 2021
Head Start is a national program that helps young children from families with low income get ready to succeed in school. The Head Start Family and Child Experiences Survey (FACES) is the premier source of national information about Head Start programs and participants. For more than two decades, FACES has been advancing the knowledge base about…
Descriptors: Children, Early Intervention, Preschool Education, Surveys
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
Schleicher, Andreas; Achiron, Marilyn; Burns, Tracey; Davis, Cassandra; Tessier, Rebecca; Chambers, Nick – OECD Publishing, 2019
This report, the product of a collaboration between the Organisation for Economic Co-operation and Development (OECD) and the UK-based charity, Education and Employers, offers a glimpse of how children see their future, and the forces that, if properly understood and harnessed, will drive them forward to realise their dreams. Through concerted…
Descriptors: Educational Trends, Trend Analysis, Computer Uses in Education, Artificial Intelligence
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Kehoe, Margaret; Poulin-Dubois, Diane; Friend, Margaret – Journal of Speech, Language, and Hearing Research, 2021
Purpose: This study investigated within-language and between-language associations between phonological memory, vocabulary, and grammar in French-English (n = 43) and Spanish-English (n = 25) bilingual children at 30, 36, and 48 months. It was predicted that phonological memory would display both within-language and between-language relations to…
Descriptors: Bilingualism, Preschool Children, Foreign Countries, Longitudinal Studies
Li, Weilin; Duncan, Greg J.; Magnuson, Katherine; Schindler, Holly S.; Yoshikawa, Hirokazu; Leak, Jimmy – Annenberg Institute for School Reform at Brown University, 2020
This paper uses meta-analytic techniques to estimate the separate effects of the starting age, program duration, and persistence of impacts of early childhood education programs on children's cognitive and achievement outcomes. It concentrates on studies published before the wide scale penetration of state-pre-K programs. Specifically, data are…
Descriptors: Early Childhood Education, School Entrance Age, Time, Program Effectiveness
Graziano, Paulo A.; Ros, Rosmary; Haas, Sarah; Hart, Katie; Slavec, Janine; Waschbusch, Daniel; Garcia, Alexis – Grantee Submission, 2016
The goal of this study was to examine the extent to which preschoolers with externalizing behavior problems (EBP) can identify behaviors indicative of callous-unemotional (CU) traits among their peers. Participants for this study included 86 preschool children (69% boys; M[subscript age] = 5.07 years) with at-risk or clinically elevated levels of…
Descriptors: Preschool Children, Child Behavior, Behavior Problems, At Risk Students
Yettick, Holly; Lloyd, Sterling; Harwin, Alexandra; Riemer, Andrew; Swanson, Christopher B. – Editorial Projects in Education, 2016
The concept of growth mindset--the belief that intelligence can be developed through effort--has gained considerable attention in K-12 education in recent years. To learn more about educators' experiences and views regarding growth mindset, the Education Week Research Center developed an original survey and administered it to a national sample of…
Descriptors: Teacher Attitudes, Elementary School Teachers, Secondary School Teachers, National Surveys
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Muhombe, Joseph Andrew; Rop, Naftali K.; Ogola, Fredrick O.; Wesonga, Justus Nyongesa – Journal of Education and Practice, 2015
This study sought to examine influence of Special Needs Education Policy on access to secondary school education by learners with hearing impairments in Nandi County, Kenya. The study was informed by the Multiple Intelligences theory and the Dewey theory of Progressivism. The findings showed that majority of the respondents were aware of the…
Descriptors: Foreign Countries, Special Education, Secondary Education, Secondary Schools
Foorman, Barbara R.; Petscher, Yaacov; Schatschneider, Chris – Florida Center for Reading Research, 2015
The Florida Center for Reading Research (FCRR) Reading Assessment (FRA) consists of computer-adaptive reading comprehension and oral language screening tasks that provide measures to track growth over time, as well as a Probability of Literacy Success (PLS) linked to grade-level performance (i.e., the 50th percentile) on the reading comprehension…
Descriptors: Elementary School Students, Middle School Students, High School Students, Written Language
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