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Liang, Zibo; Mu, Lan; Chen, Jie; Xie, Qing – Education and Information Technologies, 2023
In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…
Descriptors: MOOCs, Artificial Intelligence, Graphs, Educational Resources
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Dimov, Cvetomir M.; Anderson, John R.; Betts, Shawn A.; Bothell, Dan – Cognitive Science, 2023
We studied collaborative skill acquisition in a dynamic setting with the game Co-op Space Fortress. While gaining expertise, the majority of subjects became increasingly consistent in the role they adopted without being able to communicate. Moreover, they acted in anticipation of the future task state. We constructed a collaborative skill…
Descriptors: Cooperation, Skill Development, Expertise, Role Playing
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Chapman, Jared R.; Kohler, Tanner B.; Gedeborg, Sam – Journal of Educational Computing Research, 2023
Research on gamification's effects in educational environments has been a growing domain in recent years. As research has demonstrated the power of gamified systems to effectively motivate learners in educational settings, it has also become clear that not all individuals are motivated in the same way, or to the same extent, by the same gamified…
Descriptors: Educational Technology, Gamification, Student Motivation, Student Attitudes
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Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
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Jesús Pérez; Eladio Dapena; Jose Aguilar – Education and Information Technologies, 2024
In tutoring systems, a pedagogical policy, which decides the next action for the tutor to take, is important because it determines how well students will learn. An effective pedagogical policy must adapt its actions according to the student's features, such as knowledge, error patterns, and emotions. For adapting difficulty, it is common to…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Reinforcement, Difficulty Level
Cipani, Ennio – Communique, 2019
This article discusses a three-phase model aimed at obtaining vocal speech with students who display selective mutism at school. The three phases discussed include: (1) establishing reinforcer influence; (2) enhancing motivation to speak; and (3) generalize to nontherapy settings. The utilization of this approach to get speech to occur and…
Descriptors: Therapy, Anxiety Disorders, Speech, Models
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Yao, Zhuojun; Enright, Robert – Early Child Development and Care, 2020
The current study investigated the effect of moral stories in promoting kindergarteners' sharing behaviour. One hundred eight children were randomly assigned to one of three conditions: two experimental conditions (a moral story with a sharing model and good consequences and a moral story with a selfish model and bad consequences) and a control…
Descriptors: Moral Values, Kindergarten, Young Children, Sharing Behavior
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Li, Xiao; Xu, Hanchen; Zhang, Jinming; Chang, Hua-hua – Journal of Educational and Behavioral Statistics, 2023
The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…
Descriptors: Learning Processes, Models, Algorithms, Individualized Instruction
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Liu, Xinyang; Ardakani, Saeid Pourroostaei – Education and Information Technologies, 2022
The purpose of this study is to propose an e-learning system model for learning content personalisation based on students' emotions. The proposed system collects learners' brainwaves using a portable Electroencephalogram and processes them via a supervised machine learning algorithm, named K-nearest neighbours (KNN), to recognise real-time…
Descriptors: Foreign Countries, Undergraduate Students, Electronic Learning, Artificial Intelligence
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Kausik, Neel Harit; Hussain, Dilwar – Child Care in Practice, 2020
This paper presents a conceptual framework to understand the Nurtured Heart Approach (NHA) through the perspective of Self-Determination Theory (SDT). The Nurtured Heart Approach and the Self-Determination Theory are discussed and the parallels are drawn between the two, to provide a theoretical foundation to NHA and support for its effectiveness,…
Descriptors: Self Determination, Models, Intervention, Behavior Problems
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LaBrot, Zachary C.; DeFouw, Emily; Eldridge, Morgan – Education and Treatment of Children, 2021
Several strategies (e.g., performance feedback, video models, tactile prompting) have been found to be effective for improving preservice teachers' use of foundational behavior management skills. However, there is limited research examining these training strategies for promoting preservice clinicians' use of evidence-based behavior management…
Descriptors: School Psychology, Graduate Students, Program Effectiveness, Positive Reinforcement
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King-Sears, Margaret E.; Garwood, Justin D. – Clearing House: A Journal of Educational Strategies, Issues and Ideas, 2020
The effectiveness of behavioral interventions can be dependent on the fidelity with which practitioners design and implement those methods. Fidelity refers to the degree to which interventions are implemented as intended. Interventions implemented with low fidelity do not achieve anticipated results with students, whereas high-fidelity…
Descriptors: Fidelity, Program Implementation, Intervention, Behavior Modification
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Gevarter, Cindy; Horan, Keri – Journal of Behavioral Education, 2019
This study examined a behavioral intervention package to promote the use of target vocalizations alongside speech-generating device (SGD) mands. Six minimally verbal children with autism spectrum disorder participated, including three with no prior SGD experience. During baseline, SGD responses resulted in access to a preferred item and there was…
Descriptors: Autism, Speech Communication, Audio Equipment, Children
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Aidonopoulou-Read, Tereza – British Journal of Special Education, 2020
The popularity of formative assessment has increased since the publication of work by Black and Wiliam in 1998. Even though it is a useful teaching tool, in most cases it has only been possible to use it for students with high levels of cognitive and communicative ability. The aim of this article is to propose a modified, personalisable model of…
Descriptors: Formative Evaluation, Models, Students with Disabilities, Autism
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Topping, Keith – Education Sciences, 2021
The present paper offers a definition of peer assessment and then reviews the major syntheses on its effectiveness. However, the main part of this paper is preoccupied with how to do PA successfully. A typology of 44 elements explains the differences between the many types of peer assessment. Then a theoretical model outlines some of the processes…
Descriptors: Peer Evaluation, Definitions, Program Effectiveness, Models
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