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Doran, Elizabeth; Reid, Natalie; Bernstein, Sara; Nguyen, Tutrang; Dang, Myley; Li, Ann; Kopack Klein, Ashley; Rakibullah, Sharika; Scott, Myah; Cannon, Judy; Harrington, Jeff; Larson, Addison; Tarullo, Louisa; Malone, Lizabeth – Office of Planning, Research and Evaluation, 2022
Head Start is a national program that helps young children from families with low income get ready to succeed in school. It does this by working to promote their early learning and health and their families' well-being. The Head Start Family and Child Experiences Survey (FACES) provides national information about Head Start programs and…
Descriptors: Federal Programs, Low Income Students, Social Services, Children
Egan, Laura; Tang, Judy H.; Ferraro, David; Erberber, Ebru; Tsokodayi, Yemurai; Stearns, Pat – National Center for Education Statistics, 2022
Trends in International Mathematics and Science Study (TIMSS) is an international comparative study designed to measure trends in mathematics and science achievement at grades 4 and 8, as well as to collect information about educational contexts (such as students' schools, teachers, and homes) that may be related to student achievement. TIMSS has…
Descriptors: Achievement Tests, Mathematics Achievement, International Assessment, Foreign Countries
Arnold, Karen D.; Owen, Laura; Lewis, Jonathan – Journal of College Access, 2020
Making college access and success more equitable at a national scale requires alternatives to intensive in-person modes of pre-college advising. Text-message advising campaigns are a promising intervention model for delivering college application and financial aid assistance affordably to large populations of college-intending, low-income…
Descriptors: Academic Advising, Telecommunications, Handheld Devices, College Bound Students
Bezerra, Luis Naito Mendes; Silva, Márcia Terra – International Journal of Distance Education Technologies, 2020
In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…
Descriptors: Learning Analytics, Data Collection, Class Size, Online Courses
Edelstein, Jeffrey; Abbott, Jordan; Kimball, Ezekiel – Journal of Postsecondary Education and Disability, 2020
Disability-as-diagnosis, disability-as-identity, and disability-as-experience as pressing measurement issues in learning outcomes assessment are described in this paper. Disability represents a critically important latent variable in many learning outcomes assessment plans unless it is a formalized part of analytic plans. Noting the potential for…
Descriptors: Disabilities, Clinical Diagnosis, Identification (Psychology), Experience
Gage, Nicholas A.; Beahm, Lydia; Kaplan, Rachel; MacSuga-Gage, Ashley S.; Lee, Ahhyun – Beyond Behavior, 2020
The Positive Behavioral Interventions and Supports (PBIS) framework is currently implemented in more than 25,000 schools across the globe. Its implementation has demonstrated positive impacts on a number of behavioral and academic outcomes. A growing evidence base has found that PBIS has been particularly effective at reducing both in- and…
Descriptors: Student Behavior, Behavior Problems, Positive Behavior Supports, Intervention
Parker, John N.; Cardenas, Edgar; Dorr, Alexander N.; Hackett, Edward J. – Sociological Methods & Research, 2020
New technologies transform research specialties and potentiate new fields. Sociometers--wearable electronic sensors collecting quantitative, dynamic data about embodied social interactions at hyperfine scales--represent such a possibility for small group research. This article introduces this new method and its distinctive qualities and…
Descriptors: Measurement Equipment, Data Collection, Group Structure, Group Dynamics
Kwet, Michael; Prinsloo, Paul – Teaching in Higher Education, 2020
This article examines developments in the 'smart classroom' as a new frontier for the university. It provides a conceptual map of the scope and limitations of smart classrooms, contextualized to smart university initiatives. First, it introduces the notion of 'smart' technology in cities, campuses, and classrooms. Next, it examines how the smart…
Descriptors: Educational Technology, Classroom Environment, Educational Equipment, College Environment
Wallace-Spurgin, Mekca – International Journal of Technology in Education, 2020
In an effort provide access to devices and prepare students for the future, a small rural high school committed to becoming a high-tech school. However, data collected using the IPI-T process suggested teachers were typically the users of the technology, students were often disengaged, and teachers were asking students to participate in…
Descriptors: Technology Integration, Learner Engagement, Cognitive Processes, High School Students
Hodges, Jaret – Journal of Advanced Academics, 2020
State databases offer researchers the opportunity to conduct research using data collected by states. These databases contain financial, demographic, and accountability data. Accessing and acquiring data from these repositories, though, can offer challenges to scholars interested in conducting research. This brief describes the type of data…
Descriptors: Data Collection, Data Use, Educational Research, Gifted Education
Viano, Samantha; Baker, Dominique J. – Review of Research in Education, 2020
Measuring race and ethnicity for administrative data sets and then analyzing these data to understand racial/ethnic disparities present many logistical and theoretical challenges. In this chapter, we conduct a synthetic review of studies on how to effectively measure race/ethnicity for administrative data purposes and then utilize these measures…
Descriptors: Data Collection, Data Analysis, Racial Identification, Ethnicity
Hansen, David M. – Strategic Enrollment Management Quarterly, 2020
In recent years we have developed a data analytics pipeline using artificial neural networks to predict prospective student matriculation for university admissions using very limited demographic data. Predictions are generated at the earliest stages of the admissions process and successfully inform recruiting and admissions staff about the…
Descriptors: Artificial Intelligence, Data Analysis, College Admission, Enrollment Management
Harvey, Annelie J.; Keyes, Helen – Innovations in Education and Teaching International, 2020
Learning Dashboards display analytics pertaining to student performance and attainment, often alongside scores for the class cohort average. Little research has considered the effects of this social comparison information on students' well-being, motivation, and engagement. The current study presented participants with hypothetical data that…
Descriptors: Self Esteem, College Students, Student Motivation, Information Management
Kittelman, Angus; Storie, Sloan; Horner, Robert H.; Machalicek, Wendy – Center on Positive Behavioral Interventions and Supports, 2020
Young students starting school for the first time (e.g., kindergarteners) often benefit from more than typical intensity of behavioral support. Learning new social expectations, routines, and interaction patterns can be daunting. This is an important concern for schools implementing positive behavioral interventions and supports (PBIS). Learning a…
Descriptors: Behavior Modification, Positive Behavior Supports, Intervention, Kindergarten
Bhatanagar, Sameer; Zouaq, Amal; Desmarais, Michel C.; Charles, Elizabeth – International Educational Data Mining Society, 2020
Online "Peer Instruction" has become prevalent in many "flipped classroom" settings, yet little work has been done to examine the content students generate in such a learning environment. This study characterizes a dataset generated by an open-source, web-based homework system that prompts students to first answer questions,…
Descriptors: Peer Teaching, Electronic Learning, Educational Technology, Web Based Instruction

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