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Cara Giacomini; Deborah Trumble; Divya Krishnaswamy; Jacqueline King – Council for Advancement and Support of Education, 2024
How, and to what extent, are advancement professionals integrating artificial intelligence (AI) into their work? What do they view as the primary opportunities presented by this new technology, and what are their concerns regarding its use? To answer these questions, the Council for Advancement and Support of Education (CASE) and GiveCampus…
Descriptors: Institutional Advancement, Artificial Intelligence, Nonprofit Organizations, Schools
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
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
Reyes, Erifer Fernandez; Popof, Evo – State Educational Technology Directors Association, 2023
This report captures state leaders' perspectives on various issues relating to education technology at this unique moment in time. To be more precise, the report provides an analysis of the feedback collected from state leaders through surveys administered in April and May 2023. It seeks to catalog the ways in which state education agencies are…
Descriptors: Educational Technology, Trend Analysis, Technology Uses in Education, Information Security
Sallie Mae Bank, 2025
This report examines how enrolled undergraduate students and parents of undergraduates view higher education and how they pay for it. The report considers education funding sources--from parent and student income and savings to scholarships, grants, and borrowed funds--and evaluates trends in payment strategies over time. This 18th edition builds…
Descriptors: Paying for College, Undergraduate Students, Parents, Student Financial Aid
EdChoice, 2023
This poll was conducted between December 11-15, 2023 among a sample of 2,260 Adults. The interviews were conducted online and the data were weighted to approximate a target sample of Adults based on gender, educational attainment, age, race, and region. This report highlights: (1) views on K-12 education; (2) schooling and experiences; (3) K-12…
Descriptors: Adults, Parents, Public Opinion, Student Mobility
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
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
Andrew Walker, Contributor; Katherine Bao, Contributor; Kun Yuan, Contributor; Sabrina White, Contributor – Graduate Management Admission Council, 2024
The annual Application Trends Survey from the Graduate Management Admission Council (GMAC) provides the world's graduate business schools with data and insights to understand current trends in applications sent to graduate management education (GME) programs. This year's report begins with information from new survey questions about artificial…
Descriptors: College Applicants, Business Education, Graduate Study, Masters Programs
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
Anjali Adukia; Emileigh Harrison – Annenberg Institute for School Reform at Brown University, 2025
Curricula impart knowledge, instill values, and shape collective memory. Despite growing public funding for religious schools through U.S. school choice programs, little is known about what they teach. We examine textbooks from public schools, religious private schools, and home schools, applying computational methods -- including the use of…
Descriptors: State Church Separation, Public Schools, Private Schools, Curriculum Evaluation
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
EdChoice, 2024
This poll was conducted between February 2-5, 2024 among a sample of 2,252 Adults. The interviews were conducted online and the data were weighted to approximate a target sample of Adults based on gender, educational attainment, age, race, and region. Results based on the full survey have a measure of precision of plus or minus 2.41 percentage…
Descriptors: Public Opinion, Parents, Parent Attitudes, Elementary Secondary Education
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