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Jiayi Zhang; Conrad Borchers; Vincent Aleven; Ryan S. Baker – International Educational Data Mining Society, 2024
Think-aloud protocols are a common method to study self-regulated learning (SRL) during learning by problem-solving. Previous studies have manually transcribed and coded students' verbalizations, labeling the presence or absence of SRL strategies and then examined these SRL codes in relation to learning. However, the coding process is difficult to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Protocol Analysis, Self Management
Moran P. Lee; Abubakir Siedahmed; Neil T. Heffernan – Grantee Submission, 2024
Contextual multi-armed bandits have previously been used to personalize student support messages given to learners by supplying a model with relevant context about the user, problem, and available student supports. In this work, we propose using careful feature selection with relevant domain knowledge to improve the quality of student support…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Reinforcement
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T. Philip Nichols – National Education Policy Center, 2024
In September 2024, Bellwether released a three-part report, entitled "Learning Systems," on artificial intelligence (AI) in K-12 education. The report's stated purpose is to provide a holistic picture of the opportunities and risks that AI presents for education stakeholders, and it offers recommendations for policymakers and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Elementary Secondary Education
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Hollocks, Matthew J.; Charman, Tony; Baird, Gillian; Lord, Catherine; Pickles, Andrew; Simonoff, Emily – Autism: The International Journal of Research and Practice, 2022
Autistic young people experience high levels of co-occurring mental health difficulties, including anxiety, depression and behavioural difficulties, across their lifespan. Understanding the neuropsychological mechanisms which underlie these difficulties is vital in developing personalised supports and interventions. Cognitive inflexibility is one…
Descriptors: Adolescents, Young Adults, Autism Spectrum Disorders, Cognitive Processes
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Colbert, Dylan; Tyndall, Ian; Roche, Bryan; Cassidy, Sarah – Journal of Behavioral Education, 2018
A burgeoning research stream supports the efficacy of a novel behavior-analytic intervention, known as SMART training, in raising general intelligence by training a set of crucial cognitive skills, referred to as relational skills. A sample of Irish secondary school students (n = 26) was divided into two IQ matched groups, with the experimental…
Descriptors: Foreign Countries, Intelligence, Behavior Modification, Intervention
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Mujeeb Rahman, K. K.; Monica Subashini, M. – Journal of Autism and Developmental Disorders, 2022
Autism spectrum disorder (ASD) is an abnormal condition of brain development characterized by impaired cognitive ability, speech and human interactions, in addition to a set of repetitive and stereotyped patterns of behaviours. Although no cure for autism exists, early medical intervention can improve the associated symptoms and quality of life.…
Descriptors: Screening Tests, Autism, Pervasive Developmental Disorders, Artificial Intelligence
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Bokedal, Tomas; Reindal, Solveig Magnus; Rise, Svein; Wivestad, Stein M. – Journal of Philosophy of Education, 2022
Innovations in genetics, nanotechnology and artificial intelligence involve the possibility of enhancement of human attributes and capacities--offering humans innumerable opportunities for diverse, unprecedented experiences and developments both physically and cognitively. These new innovations, frequently associated with theoretical frameworks…
Descriptors: Technological Advancement, Ethics, Teaching Methods, Educational Philosophy
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Takarae, Yukari; Zanesco, Anthony; Keehn, Brandon; Chukoskie, Leanne; Müller, Ralph-Axel; Townsend, Jeanne – Developmental Science, 2022
EEG microstates represent transient electrocortical events that reflect synchronized activities of large-scale networks, which allows investigations of brain dynamics with sub-second resolution. We recorded resting EEG from 38 children and adolescents with Autism Spectrum Development (ASD) and 48 age, IQ, sex, and handedness-matched typically…
Descriptors: Autism, Pervasive Developmental Disorders, Children, Adolescents
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Kalender, Z. Yasemin; Marshman, Emily; Schunn, Christian D.; Nokes-Malach, Timothy J.; Singh, Chandralekha – Physical Review Physics Education Research, 2022
Physics is a science, technology, engineering, and mathematics discipline in which women are severely underrepresented. Prior work has identified motivation-based explanations for low participation and retention rates of women in physics. Among various motivational factors, intelligence mindsets (i.e., having fixed or growth mindsets) have been…
Descriptors: Student Attitudes, Physics, Gender Differences, Student Motivation
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Zhao, Anping; Yu, Yu – IEEE Transactions on Learning Technologies, 2022
To provide insight into online learners' interests in various knowledge from course discussion texts, modeling learners' sentiments and interests at different granularities are of great importance. In this article, the proposed framework combines a deep convolutional neural network and a hierarchical topic model to discover the hidden structure of…
Descriptors: Online Courses, Student Attitudes, Knowledge Level, Networks
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Vaiouli, Potheini; Luminet, Olivier; Panayiotou, Georgia – Autism: The International Journal of Research and Practice, 2022
Research evidence suggests that heterogeneity in emotion processing difficulties in autistic individuals may reflect co-occurring alexithymia. Elevated levels of alexithymia is a robust finding in the adult autistic population but there is a relative poverty regarding the corresponding research in younger populations. The aim of this review is to…
Descriptors: Autism, Pervasive Developmental Disorders, Children, Adolescents
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Akhrif, Ouidad; Benfaress, Chaymae; EL Jai, Mostapha; El Bouzekri El Idrissi, Youness; Hmina, Nabil – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this paper is to reveal the smart collaborative learning service. This concept aims to build teams of learners based on the complementarity of their skills, allowing flexible participation and offering interdisciplinary collaboration opportunities for all the learners. The success of this environment is related to predict…
Descriptors: Artificial Intelligence, Cooperative Learning, Interdisciplinary Approach, Universities
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Karakus, Sena; Evin Akbay, Sinem – Participatory Educational Research, 2022
Within the scope of this study, the relationships among alexithymia, psychological flexibility, authenticity and life satisfaction of individuals were investigated. In addition, the possible meditating role of psychological flexibility on the relationships among alexithymia, authenticity and life satisfaction were investigated. The research model…
Descriptors: Psychological Patterns, Life Satisfaction, Emotional Intelligence, Self Expression
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McGrew, Kevin S. – Canadian Journal of School Psychology, 2022
The "Cognitive-Affective-Motivation Model of Learning" (CAMML) is a proposed framework for integrating contemporary motivation, affective (Big 5 personality) and cognitive (CHC theory) constructs in the practice of school psychologists (SPs). The central tenet of this article is that SPs need to integrate motivation alongside affective…
Descriptors: Personality Traits, School Psychology, Student Motivation, Cognitive Ability
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Namanloo, Alireza A.; Thorpe, Julie; Salehi-Abari, Amirali – International Educational Data Mining Society, 2022
Peer assessment systems are emerging in many settings, such as peer grading in large (online) classes, peer review in conferences, peer art evaluation, etc. However, peer assessments might not be as accurate as expert evaluations, thus rendering these systems unreliable. The reliability of peer assessment systems is influenced by various factors…
Descriptors: Peer Evaluation, Graphs, Models, Self Evaluation (Individuals)
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