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Rescorla, Leslie A.; Adams, Allison; Ivanova, Masha Y. – Journal of Autism and Developmental Disorders, 2020
Previous research supports the CBCL/1½--5's "DSM"-ASD scale (and its precursor, the "DSM"-PDP scale) as a Level 1 ASD screener. Confirmatory factor analyses (CFAs) with data from population samples in 24 societies (N = 19,850) indicated good measurement invariance across societies, especially for configural and metric…
Descriptors: Child Behavior, Check Lists, Clinical Diagnosis, Screening Tests
Taggart, Jessica; Becker, Ian; Rauen, Julia; Al Kallas, Hala; Lillard, Angeline S. – Journal of Cognition and Development, 2020
Pretend play is common in childhood. Yet by age 4, children shown pretend and real activities in a book said they would choose to do the real activity over the pretend one. The present studies extended this research, examining children's actual behavior in laboratory and school settings (Study 1, n = 32, M = 59.32 months; and Study 2, n = 16, M…
Descriptors: Preschool Children, Childrens Attitudes, Parent Attitudes, Play
Gonzalez, Sandy L.; Campbell, Julie M.; Marcinowski, Emily C.; Michel, George F.; Coxe, Stefany; Nelson, Eliza L. – Developmental Psychology, 2020
Prior work has found links between consistency in toddler handedness for the fine motor skill role-differentiated bimanual manipulation (RDBM), and language development at 2 and 3 years of age. The current study investigated whether consistency in handedness from 18 to 24 months (N = 90) for RDBM predicts receptive and expressive language…
Descriptors: Preschool Children, Toddlers, Handedness, Psychomotor Skills
Palos, Ramona – Educational Studies, 2020
Three main categories of variables which impact the approach to learning were synthesised, and they are linked to the learning context, the way that students perceive this context and the students' characteristics. Despite the research which emphasised the influence of these variables on approaches to learning in different areas, only a few…
Descriptors: Goal Orientation, Nursing Education, Mastery Learning, Student Attitudes
Hughes, Robert W.; Marsh, John E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
Two experiments critically examined a predictive-coding based account of the vulnerability of short-term memory (STM) to auditory distraction, particularly the disruptive effect of changing-state sound on verbal serial recall. Experiment 1 showed that providing participants with the opportunity to predict the contents of an imminent spoken…
Descriptors: Auditory Stimuli, Short Term Memory, Prediction, Acoustics
Geng, Lina; Zheng, Qiao; Zhong, Xiaoyu; Li, Lingyan – Asia-Pacific Education Researcher, 2020
The purpose of this study was to examine the reciprocal relationships between students' engagement and their relationships with teachers and peers in the context of Chinese educational reform. The participants were 628 7th-grade students from a public secondary school in Beijing. All of the students completed self-reported student engagement,…
Descriptors: Learner Engagement, Peer Relationship, Teacher Student Relationship, Educational Change
Cui, Ying; Chen, Fu; Shiri, Ali – Information and Learning Sciences, 2020
Purpose: This study aims to investigate the feasibility of developing general predictive models for using the learning management system (LMS) data to predict student performances in various courses. The authors focused on examining three practical but important questions: are there a common set of student activity variables that predict student…
Descriptors: Foreign Countries, Identification, At Risk Students, Prediction
Slater, Stefan; Baker, Ryan S.; Wang, Yeyu – International Educational Data Mining Society, 2020
Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…
Descriptors: Data Analysis, Engineering, Classification, Models
Shafee Mohammed – ProQuest LLC, 2020
Predicting learning and human behavior in general is a challenging endeavor. Machine learning driven predictive modeling have been an increasingly popular means to understand disparities in student performance. With more than a handful of approaches to predictive modeling, the current literature of predicting learning is plagued with issues such…
Descriptors: Prediction, Short Term Memory, Blended Learning, Student Behavior
Forsblom, Lara; Pekrun, Reinhard; Loderer, Kristina; Peixoto, Francisco – Journal of Educational Psychology, 2022
Based on control-value theory (CVT), we examined longitudinal relations between students' control and value appraisals, three activity-related achievement emotions (enjoyment, anger, and boredom), and math achievement (N = 1,716 fifth and seventh grade students). We assessed appraisals and emotions with self-report measures of perceived competence…
Descriptors: Cognitive Processes, Coping, Psychological Patterns, Mathematics Achievement
Chen, Xieling; Zou, Di; Xie, Haoran; Cheng, Gary; Liu, Caixia – Educational Technology & Society, 2022
With the increasing use of Artificial Intelligence (AI) technologies in education, the number of published studies in the field has increased. However, no large-scale reviews have been conducted to comprehensively investigate the various aspects of this field. Based on 4,519 publications from 2000 to 2019, we attempt to fill this gap and identify…
Descriptors: Artificial Intelligence, Educational Trends, Educational Technology, Bibliometrics
Mann, Bryan A.; Bruno, Paul – Educational Policy, 2022
We analyze a natural experiment in which policymakers in Pennsylvania first implemented, and later removed, reimbursements to districts for students exiting to brick and mortar and cyber charter schools. Generalized difference-in-difference models show that larger shares of students enrolling in charter schools predict decrements in spending,…
Descriptors: Charter Schools, Enrollment Trends, Declining Enrollment, Prediction
Arslan, Aysel – International Journal of Curriculum and Instruction, 2022
The aim of this study; is to examine the critical thinking dispositions and achievement goal orientations of university students in terms of various variables, and to determine the predictive level of students' critical thinking dispositions on their achievement goal orientations. The sample of the research consists of 785 (333 female, 452 male)…
Descriptors: Prediction, Critical Thinking, Goal Orientation, Academic Achievement
Zhan, Ying; Lee, John Chi-Kin; Wan, Zhi Hong – Language Testing in Asia, 2022
Students can only benefit from teacher feedback if they recognise its value for learning. However, there is still a lack of research to investigate the factors influencing students' perceptions of the value of teacher feedback in the context of learning English as a foreign language. This study investigated the impacts of two significant…
Descriptors: Feedback (Response), Language Teachers, Second Language Instruction, Self Concept
Schiller, Lauren K.; Fan, Ao; Siegler, Robert S. – Journal of Numerical Cognition, 2022
The number one plays a special role in mathematics because it is the identity element in multiplication and division. The present findings, however, indicate that many middle school students do not demonstrate mathematical flexibility representing one as a fraction. Despite possessing explicit knowledge of fraction forms of one (e.g., 95% of…
Descriptors: Numbers, Mathematics Instruction, Multiplication, Division

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