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Divya Sadana; Rajnish Kumar Gupta; Sanjeev Jain; S. S. Kumaran; Jamuna Rajeswaran – Gifted and Talented International, 2024
The present study aimed to explore the association between creativity, intelligence, and personality. The study recruited sixty healthy volunteers in the age range of 20-40 years from Bengaluru city (formerly Bangalore), South India, and administered tests for fluid intelligence (Raven's Standard Progressive Matrices), personality (Big Five…
Descriptors: Creativity, Personality, Intelligence, Correlation
Segundo Salatiel Malca-Peralta; Rosa Marilú Velarde Ruiz; Hilda Raquel Alarcón Lescano – Electronic Journal of Research in Educational Psychology, 2024
Introduction: The objective of the present study was to determine if emotional intelligence and family stress are predictors of satisfaction with studies in university students. Method: Cross-sectional predictive study with a quantitative approach. The population was made up of 414 university students of both sexes who applied the TMMS-24…
Descriptors: Emotional Intelligence, College Students, Stress Variables, Predictor Variables
Matthew D. Blanchard; Eugene Aidman; Lazar Stankov; Sabina Kleitman – Cognitive Research: Principles and Implications, 2025
A collective intelligence factor (CI) was introduced by prior research to characterise the cognitive ability of groups. Surprisingly, individual intelligence did not predict CI. Instead, it correlated with individual social sensitivity, the equality of conversational turn-taking, and the proportion of females in a group. However, these findings…
Descriptors: Intelligence, Cooperative Learning, Participative Decision Making, Metacognition
Sinead Rhodes; Josephine N. Booth; Emily McDougal; Jessica Oldridge; Karim Rivera-Lares; Alexia Revueltas Roux; Tracy M. Stewart – Journal of Autism and Developmental Disorders, 2025
We examined whether cognitive profiles or diagnostic outcomes are better predictors of literacy performance for children being considered for an ADHD diagnosis. Fifty-five drug naïve children (M[subscript age] = 103.13 months, SD = 18.65; 29.09% girls) were recruited from an ADHD clinical referral waiting list. Children underwent assessment of IQ,…
Descriptors: Executive Function, Predictor Variables, Profiles, Literacy
Lucy Shiels; Peter Carew; Dani Tomlin; Gary Rance – npj Science of Learning, 2025
This study investigated the impact of soundfield amplification (SFA) on reading fluency in normal-hearing students (n = 84) aged 8-10 years. Twenty-three grade 3 and 4 classes participated across three academic terms, alternating between SFA-On and SFA-Off conditions. Reading fluency was assessed using the Wheldall Assessment of Reading Passages.…
Descriptors: Classroom Environment, Acoustics, Reading Fluency, Hearing (Physiology)
Rianne Suelmann; Eric Blaauw – Journal of Intellectual & Developmental Disability, 2025
Background: Addiction medicine still largely neglects the topic of mild and borderline intellectual disabilities (MBID), although patients with MBID are considered a risk group for substance-related problems and offending behaviour. This study aimed to explore the cognitive and adaptive impairments of inpatients in forensic addiction mental health…
Descriptors: Substance Abuse, Mild Intellectual Disability, At Risk Persons, Mental Health
Robison, Matthew K.; Brewer, Gene A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
The present study examined individual differences in 3 cognitive abilities: attention control (AC), working memory capacity (WMC), and fluid intelligence (gF) as they relate the tendency to experience task-unrelated thoughts (TUTs) and the regulation of arousal. Cognitive abilities were measured with a battery of 9 laboratory tasks, TUTs were…
Descriptors: Individual Differences, Short Term Memory, Attention Control, Intelligence
Józsa, Krisztián; Amukune, Stephen; Zentai, Gabriella; Barrett, Karen Caplovitz – Journal of Intelligence, 2022
Research has shown that the development of cognitive and social skills in preschool predicts school readiness in kindergarten. However, most longitudinal studies are short-term, tracking children's development only through the early elementary school years. This study aims to investigate the long-term impact of preschool predictors, intelligence,…
Descriptors: Foreign Countries, School Readiness, Intelligence Tests, Preschool Children
Igor Esnaola; Sara Martínez-Gregorio; Lorea Azpiazu; Iratxe Antonio-Agirre; Amparo Oliver – Psychology in the Schools, 2025
The main goal of this study was to analyze a longitudinal model which reviews the relationships between parent trust, trait emotional intelligence (EI) and self-concept. The sample was composed of 484 Spanish adolescents (226 boys, 258 girls) who completed the questionnaires "Parent Trust and Understanding Scale, Emotional Quotient Inventory:…
Descriptors: Parent Attitudes, Trust (Psychology), Emotional Intelligence, Self Concept
Michael Generalo Albino; Femia Solomon Albino; John Mark R. Asio; Ediric D. Gadia – International Journal of Technology in Education, 2025
Technology has contributed so much to the development and innovation of humankind. Artificial Intelligence (AI) is an off-shoot of such. This article explored the influence of AI anxiety on AI self-efficacy among college students. The investigators used a cross-sectional research design for 695 purposively chosen college students in one higher…
Descriptors: Anxiety, Artificial Intelligence, Self Efficacy, College Students
Haowen Zheng; Siwei Cheng – Sociological Methods & Research, 2025
How well can individuals' parental background and previous life experiences predict their mid-life socioeconomic status (SES) attainment? This question is central to stratification research, as a strong power of earlier experiences in predicting later-life outcomes signals substantial intra- or intergenerational status persistence, or put simply,…
Descriptors: Socioeconomic Status, Adults, Parent Background, Social Stratification
Michael L. Chrzan; Francis A. Pearman; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2025
The increasing rate of permanent school closures in U.S. public school districts presents unprecedented challenges for administrators and communities alike. This study develops an early-warning indicator model to predict mass closure events -- defined as a district closing at least 10% of its schools -- five years in advance. Leveraging…
Descriptors: Artificial Intelligence, Electronic Learning, School Districts, School Closing
Danaci, Miray Özözen; Dümenci, Sirma Seda Bapoglu – South African Journal of Education, 2022
The study reported on here was conducted to examine the consistency of the views of children and teachers in predicting the multiple intelligence areas of children at the end of the education programme provided in an enriched class based on multiple intelligence practices in a pre-school education institution. Using the…
Descriptors: Preschool Children, Intelligence, Multiple Intelligences, Preferences
Junxian Shen; Hongfeng Zhang; Jiansong Zheng – Psychology in the Schools, 2024
Online learning is becoming more and more common, so how to maintain learners' online learning engagement is very important. This study aims to explore the impact of future self-continuity on college students' online learning engagement and its underlying mechanism of action. We utilized the Future Self-Continuity Questionnaire, the Learning…
Descriptors: College Students, Learner Engagement, Electronic Learning, Predictor Variables
Nwosu, Kingsley Chinaza; Wahl, Williem Petrus; Anyanwu, Adeline Nne; Ezenwosu, Ngozi Elizabeth; Okwuduba, Emmanuel Nkemakolam – Journal of Research in Special Educational Needs, 2023
Our study determined the impact of emotional intelligence (EI) on teachers' attitudes, concerns and sentiments about inclusive education while controlling for teachers' professional-related factors. This is predicated on the increasing influence of EI on teacher effectiveness. The sample size consisted of 508 regular classroom teachers. Using…
Descriptors: Teacher Characteristics, Emotional Intelligence, Predictor Variables, Teacher Attitudes

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