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Brian Holzman; Horace Duffy – Annenberg Institute for School Reform at Brown University, 2024
As states incorporate measures of college readiness into their accountability systems, school and district leaders need effective strategies to identify and support students at risk of not enrolling in college. Although there is an abundant literature on early warning indicators for high school dropout, fewer studies focus on indicators for…
Descriptors: College Enrollment, College Readiness, Educational Indicators, Predictor Variables
Jake Meads; Daniel Shepherd; Jason Landon; Sonja Goedeke – Journal of Autism and Developmental Disorders, 2024
The current study was a secondary analysis of cross-sectional data collected in New Zealand. Parents (n = 291) of an autistic child completed an online survey that included temporal/demographic questions relating to the parent and child, and parent ratings of the child's core ASD symptoms, their parenting stress, and psychological well-being.…
Descriptors: Child Rearing, Autism Spectrum Disorders, Symptoms (Individual Disorders), Stress Variables
Dante D. Dixson; Leah Jansen; Ersie-Anastasia Gentzis; Frank C. Worrell – High Ability Studies, 2024
In this study, the relationship between clusters of hope and a psychosocial profile of academic talent development is examined in a sample of 466 academically gifted adolescents. First, cluster analysis is leveraged to examine whether interpretable three- and four-cluster hope solutions can be found in the sample. Second, differences among a group…
Descriptors: Academically Gifted, Adolescents, Predictor Variables, Student Characteristics
Md Sazzad Hossain; Debora Wenger – Journalism and Mass Communication Educator, 2024
Journalism is a highly technology-dependent profession, and students, educators, and professionals must develop specific digital skills. This study uses the theory of disruptive innovation to examine how journalism educators adapt their programs in response to changing media environments. A survey of accredited journalism and mass communication…
Descriptors: Journalism Education, Educational Change, Educational Technology, Technology Uses in Education
Steven R. Frechette – ProQuest LLC, 2024
This study investigates student perceptions of artificial intelligence (AI). The study analyzed four independent variables -- age, gender, school, and employment -- to predict students' level of readiness to adopt AI within an educational setting. Using an instrument with two constructs, data was collected from a diverse, multicultural group of…
Descriptors: Community College Students, Community Colleges, Student Attitudes, Artificial Intelligence
Francisco Arturo Santelli; Jason A. Grissom – AERA Open, 2024
Research suggests that longer commute times may increase employee turnover probabilities by increasing stress and reducing job attachment and embeddedness. Using administrative data from a midsized urban school district, we test whether teachers with longer commute times are more likely to transfer schools or exit the district. Both descriptively…
Descriptors: Travel, Transportation, Time, Proximity
Matthew E. Foster; Jacqueline M. Caemmerer; Briana Hennessy; Sara A. Smith; Lisa M. López; Trina D. Spencer – Elementary School Journal, 2024
Using the Early Childhood Longitudinal Study Kindergarten Cohort (2010-2011), this study is the first to investigate predictors of kindergarten science achievement and growth across elementary school--English language proficiency (ELP), executive functioning, math and reading achievement, parent-engaged science and math activities, and classroom…
Descriptors: Predictor Variables, Kindergarten, Young Children, Science Achievement
Bantigegn Tegegne; Habtamu Wondimu – Cogent Education, 2024
Retaining a talented workforce is a crucial concern for any organization. This study aimed to examine the level and predictors of organizational commitment among Ethiopian public university instructors. The objectives were to measure the levels of emotional intelligence, effective communication, and organizational commitment; test the…
Descriptors: Emotional Intelligence, Universities, Communication Skills, Predictor Variables
Kristin Hadfield; Mays Al-Hamad; Rinad Bakhti; Rana Dajani; Amal El Kharouf; Julia Michalek; Joana Mukunzi; Lina Qtaishat; Tanvi Sethi; Sophie von Stumm; Isabelle Mareschal – International Journal of Early Childhood, 2024
Refugee children often face disruptions to their education before and during displacement. However, little is known about either levels or predictors of refugee children's literacy or about their attitudes toward reading in low- or middle-income countries. To address this, we conducted in-home literacy assessments using the Holistic Assessment of…
Descriptors: Refugees, Predictor Variables, Literacy, Young Children
Trevor T. Tuma; Erin L. Dolan – CBE - Life Sciences Education, 2024
Quality mentoring promotes graduate student success. Despite an abundance of practical advice, empirical evidence regarding how to match mentees and mentors to form quality mentoring relationships is lacking. Here, we examine the influence of variables theorized to predict mentorship support and quality in a national sample of 565 science doctoral…
Descriptors: Mentors, Predictor Variables, Doctoral Students, Universities
Lisa Kittinger; Victor Law – Journal of Information Technology Education: Research, 2024
Aim/Purpose: The purpose of this systematic literature review is to evaluate the application of UTAUT and UTAUT2 frameworks in K-12 education. Background: This study included an analysis of peer-reviewed empirical studies that use the UTAUT and UTAUT2 frameworks to understand the factors that influence technology adoption among K-12 educators. New…
Descriptors: Elementary Secondary Education, Educational Technology, Technology Uses in Education, Technology Integration
Angelos Rodafinos; Vassilis Barkoukis; Katerina Tzafilkou; Despoina Ourda; Anastasios A. Economides; Maria Perifanou – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This study aims to examine the influence of digital competences, technology acceptance, and individual factors (gender and educational level) on academic achievement in Physical Education and Sports Science (PESS). Background: Prior research has established a positive correlation between digital competences and performance, but the…
Descriptors: Technological Literacy, Academic Achievement, Physical Education, Athletics
Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
Jessica Wise Younger; Zoe D'Esposito; Irene S. Geng; Stephanie L. Haft; Project iLEAD Consortium; Melina R. Uncapher – Social Psychology of Education: An International Journal, 2024
Growth mindset has been shown to predict academic achievement in a variety of student populations, though the strength of the relationship can vary depending on the characteristics of the students examined. Using a large-scale sample of middle school students from a diverse district in the United States, we examine how multiple facets of students'…
Descriptors: Self Efficacy, Beliefs, Middle School Students, At Risk Students
Jiye Kim – International Journal of Child Care and Education Policy, 2024
Kindergarten is emphasized as a critical first entry into the education system, as politicians and pundits believe kindergartners' success can lead to later academic achievement. Therefore, a comprehensive understanding of kindergarten school readiness data should consider how it is measured and how that affects learning. Using the Early Childhood…
Descriptors: Kindergarten, School Readiness, Teacher Attitudes, Cognitive Style

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