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Showing 1 to 15 of 23 results Save | Export
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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
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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
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Yongtian Cheng; K. V. Petrides – Educational and Psychological Measurement, 2025
Psychologists are emphasizing the importance of predictive conclusions. Machine learning methods, such as supervised neural networks, have been used in psychological studies as they naturally fit prediction tasks. However, we are concerned about whether neural networks fitted with random datasets (i.e., datasets where there is no relationship…
Descriptors: Psychological Studies, Artificial Intelligence, Cognitive Processes, Predictive Validity
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Sarab Tej Singh; Satish Kumar; Vishal Singh – Journal of Education and Learning (EduLearn), 2025
The current research is the study of academic buoyancy in relation to emotional intelligence and parenting styles. Academic buoyancy is a strength in a student's life to deal with the routine problems in classroom study like low grades, negative feedback by teachers, and difficulties in understanding of concepts. For the studying the relationship…
Descriptors: Parenting Styles, Emotional Intelligence, Predictor Variables, Academic Achievement
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Yoon Lee; Gosia Migut; Marcus Specht – British Journal of Educational Technology, 2025
Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constrained by the subjective nature of human evaluation and the challenges of maintaining consistency and scalability. The recent widespread AI…
Descriptors: Artificial Intelligence, Cognitive Processes, Student Behavior, Cues
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Samantha M. van Rens; Cristina Lemelin; Patricia H. Kloosterman; Laura J. Summerfeldt; James D. A. Parker – Canadian Journal of School Psychology, 2025
Although previous research has found trait emotional intelligence (TEI) to be a moderate predictor of bullying behaviors in adolescents, this work has limited generalizability. The current study is the first to use a multidimensional approach to both TEI and bullying behaviors when looking at their relationship in high school students. The study…
Descriptors: Bullying, High School Students, Emotional Intelligence, Predictor Variables
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Kevser Hava; Özgür Babayigit – Education and Information Technologies, 2025
In recent years, there has been a growing emphasis on integrating Artificial Intelligence (AI) applications in educational settings. As a result, it is essential to assess teachers' competencies in Technological, Pedagogical, and Content Knowledge (TPACK) as it pertains to AI and examine the factors that influence these competencies. This study…
Descriptors: Technological Literacy, Pedagogical Content Knowledge, Artificial Intelligence, Technology Integration
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Afef Saihi; Mohamed Ben-Daya; Moncer Hariga – Education and Information Technologies, 2025
The integration of AI-chatbots into higher education offers the potential to enhance learning practices. This research aims to explore the factors influencing AI-chatbots adoption within higher education, with a focus on the moderating roles of technological proficiency and academic discipline. Utilizing a survey-based approach and advanced…
Descriptors: Technology Uses in Education, Artificial Intelligence, Higher Education, Technology Integration
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Kheira Ouassif; Benameur Ziani – Education and Information Technologies, 2025
The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…
Descriptors: Predictor Variables, College Students, Majors (Students), Decision Making
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Wenyi Lu; Joseph Griffin; Troy D. Sadler; James Laffey; Sean P. Goggins – Journal of Learning Analytics, 2025
Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…
Descriptors: Game Based Learning, Predictor Variables, Evaluation Methods, Educational Games
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Elizeth Mayrene Flores Hinostroza; Derling Jose Mendoza; Mercedes Navarro Cejas; Edinson Patricio Palacios Trujillo – International Electronic Journal of Mathematics Education, 2025
This study builds on the increasing relevance of technology integration in higher education, specifically in artificial intelligence (AI) usage in educational contexts. Background research highlights the limited exploration of AI training in educational programs, particularly within Latin America. AI has become increasingly pivotal in educational…
Descriptors: Science Instruction, Artificial Intelligence, Technology Integration, Technology Uses in Education
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Layes Smail; Gharaibeh Mahmoud; Djeribiai Adel – Reading Psychology, 2025
This study examined the independent contribution of morphological awareness and orthographic awareness in reading comprehension, controlling for working memory and reading fluency in Arabic-speaking children. Participants (N = 244) from grades four and five, were classified into typical comprehenders (n = 207) and poor comprehenders (n = 37). All…
Descriptors: Morphology (Languages), Orthographic Symbols, Reading Comprehension, Arabic
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Liang Zhang; Jionghao Lin; John Sabatini; Conrad Borchers; Daniel Weitekamp; Meng Cao; John Hollander; Xiangen Hu; Arthur C. Graesser – IEEE Transactions on Learning Technologies, 2025
Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…
Descriptors: Artificial Intelligence, Academic Achievement, Data, Evaluation Methods
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Carey Bernini Dowling; C. Veronica Smith; Yue Yin; Jeffrey M. Williams – Journal of the Scholarship of Teaching and Learning, 2025
People view many attributes, including intelligence, through implicit theories (or mindsets). Entity mindsets position the attribute as unchangeable or static, whereas incremental mindsets see the attribute as malleable or capable of being changed/improved (Dweck & Leggett, 1988). The present studies examined a new questionnaire designed to…
Descriptors: Grade Point Average, Undergraduate Students, Study Habits, Intelligence
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Weiqing Shi; Xin Jiang – Reading and Writing: An Interdisciplinary Journal, 2025
This study explores the effectiveness of machine learning and eye movement features in predicting Chinese reading proficiency. Unlike previous research, which focused on one or two specific levels of eye movement features, this study integrates passage-, sentence- and word-level eye movement features to predict reading proficiency. By analyzing…
Descriptors: Foreign Countries, Undergraduate Students, Predictor Variables, Reading Achievement
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