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Julia Martini; Mark Wade; Heather Prime; Jennifer Jenkins – Social Development, 2024
In the current paper, we examined the dimensional structure of parenting using a bifactor model of observed parenting domains during infancy. We validated our parenting dimensions by examining correlations with indicators of family well-being and child development. Data come from a longitudinal cohort that recruited a diverse sample of mothers…
Descriptors: Child Rearing, Parenting Styles, Infants, Family Environment
Yuan Fang; Lijuan Wang – Grantee Submission, 2024
Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…
Descriptors: Structural Equation Models, Research Problems, Longitudinal Studies, Simulation
Lisa DaVia Rubenstein; Sydney Katherine Johnson; Allison Southworth; Gerardo Ramirez – Phi Delta Kappan, 2024
Leadership is often conceptualized and taught through famous, world-changing individuals; however, leadership spans levels of influence, from small-group projects to global initiatives. While student leaders are present at every level, existing leadership research and programs center adults. Within this article, Lisa DaVia Rubenstein, Sydney…
Descriptors: Leadership, Student Leadership, Models, Definitions
Lena Geuer; Alena Otteny; Dennis Wagner; Steffen Menne; Sergey Mukametov; Roland Ulber – Journal of Chemical Education, 2024
Lateral flow immunoassays have become part of our daily lives as a consequence of the coronavirus pandemic, but what is actually the story behind these red lines? Scientific findings, often described as a scientific black box, create continuous global changes in our living conditions and must be made accessible to society in a comprehensible way.…
Descriptors: Science Instruction, Science Laboratories, COVID-19, Models
Ankita Bhattashali; Zachary A. McCall – Exceptional Children, 2026
In this conceptual paper, we introduce intersectional field analysis as a theoretical framework for understanding how power operates in the special education field broadly and how it affects immigrant families in their efforts to influence special education decisions for their children. We apply the framework, which merges key insights from…
Descriptors: Special Education, Power Structure, Immigrants, Decision Making
Ben Oliver D. Tutor; Emerson R. Rico – Journal of Academic Ethics, 2026
The integration of technology into education, though beneficial, has also raised concerns about academic dishonesty. Digital tools and platforms provide new opportunities for students to engage in behaviors that could undermine academic integrity. Understanding why students commit these acts is crucial for designing effective policies to mitigate…
Descriptors: Technology Uses in Education, Artificial Intelligence, Natural Language Processing, Cheating
Renee M. Penalver; C. Mazariegos; Kyle Parker; Jennifer Dyer-Seymour – Teaching of Psychology, 2026
Background: The American Psychological Association (APA)'s Guidelines for the Undergraduate Psychology Major, 3.0 includes communication as one of the five learning goals. We examined to what extent psychology majors communicated their ideas in an APA-style research paper. Objective: This study aimed to provide data about students' written…
Descriptors: State Universities, Undergraduate Students, Psychology, Majors (Students)
Polikoff, Morgan – Policy Analysis for California Education, PACE, 2019
California is one of just two states (with Kansas) that does not use a student-level growth model to measure school performance. This brief lays out a number of common beliefs about growth models and provides evidence that these beliefs are inaccurate or unsupported. In so doing, the brief makes a positive case that the state should adopt such a…
Descriptors: Growth Models, School Effectiveness, Accountability, Misconceptions
Bellarhmouch, Youssra; Jeghal, Adil; Tairi, Hamid; Benjelloun, Nadia – Education and Information Technologies, 2023
Nowadays, the need for e-learning is amplified, especially after the COVID-19 pandemic. E-learning platforms present a solution for the continuity of the learning process. Learners are using different platforms and tools for learning. For this, it is necessary to model the learner for the personalization of the learning environment according to…
Descriptors: Electronic Learning, Educational Environment, Models, Individualized Instruction
Jiang, Shiyan; Qian, Yingxiao; Tang, Hengtao; Yalcinkaya, Rabia; Rosé, Carolyn P.; Chao, Jie; Finzer, William – Education and Information Technologies, 2023
As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Artificial Intelligence
Casillas, Marisa – Child Development Perspectives, 2023
In this article, I advocate for an enriched view of children's linguistic input, with the aim of building sustainable and tangible links between theoretical models of language development and families' everyday experiences. Children's language experiences constrain theoretical models in ways that may illuminate universal learning biases. However,…
Descriptors: Child Language, Linguistic Input, Language Acquisition, Context Effect
Khan, Eijaz Ahmed; Cram, Andrew; Wang, Xiaoxia; Tran, Khanh; Cavaleri, Michelle; Rahman, Md Jahidur – International Journal of Educational Management, 2023
Purpose: Critically, to improve and manage online learning quality (OLQUAL), higher education providers need to regularly measure OLQUAL. Hence, a reliable measure of OLQUAL in higher education from the students' perspective is indispensable. Further, as a pioneer in examining OLQUAL outcomes in the online education context, we assert that…
Descriptors: Electronic Learning, Educational Quality, Student Satisfaction, Trust (Psychology)
Zitter, Ashley; Rinn, Hezekiah; Szapuova, Zofia; Avila-Pons, Vanessa M.; Coulter, Kirsty L.; Stahmer, Aubyn C.; Robins, Diana L.; Vivanti, Giacomo – Journal of Autism and Developmental Disorders, 2023
There is increasing evidence supporting the effectiveness of the Early Start Denver Model (ESDM) for children on the autism spectrum. However, substantial variability in response to the ESDM has been reported across participants. We examined the plausible yet untested hypothesis that variations in the fidelity level of therapists delivering the…
Descriptors: Fidelity, Early Intervention, Models, Skill Development
Haensel, Maria; Schmitt, Thomas M.; Bogenreuther, Jakob – Journal of Science Education and Technology, 2023
Agent-based modeling is a promising tool for familiarizing students with complex systems as well as programming skills. Human-environment systems, for instance, entail complex interdependencies that need to be considered when modeling these systems. This complexity is often neglected in teaching modeling approaches. For a heterogeneous group of…
Descriptors: Graduate Students, Foreign Countries, Programming, Models
Bellone, Katherine M.; Elliott, Stephen C.; Hynan, Linda S.; Warren, Beth; Jarrett, Robin B. – Journal of Autism and Developmental Disorders, 2023
We conducted an open-trial proof of concept study to determine the safety, acceptability, and feasibility of Mindful Self-Care for Caregivers (MSCC) for parents of children with Autism Spectrum Disorders (ASD) (N = 13). The intervention was offered as a co-located care model in a pediatric specialty center where the participants' children received…
Descriptors: Child Caregivers, Autism Spectrum Disorders, Metacognition, Self Management

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