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Gulnoza Yakubova; Briella Baer Chen; Melissa A. Defayette – Review Journal of Autism and Developmental Disorders, 2024
In this systematic review, we examined the use of technology-based interventions to teach science, technology, engineering, and mathematics (STEM) skills to K-12 autistic students. Twenty peer-reviewed articles with 59 autistic participants, ages 5-21 and published between 2012 and 2021 were included. Studies used a variety of technology-based…
Descriptors: STEM Education, Intervention, Kindergarten, Elementary Secondary Education
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Mako Kato; M. Nutsa Kobakhidze – Asia Pacific Education Review, 2024
Japan has a longstanding history of shadow education, which has evolved, transformed, and extended beyond its borders. Japanese shadow education institutions, known as "juku," have expanded worldwide, including in Asia, the US, and Europe, offering offline and online tutoring services mainly for Japanese expatriates. This study examines…
Descriptors: Tutoring, Private Education, Computer Assisted Instruction, Role
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Noemi Mauro; Liliana Ardissono; Federica Cena; Livio Scarpinati; Gianluca Torta – International Journal of Artificial Intelligence in Education, 2024
Field trips enrich learning programs with out-of-school activities that can bring gains in students' academic content knowledge and personal growth. However, they are a source of anxiety for teachers because of the bureaucracy, pedagogy, etc., risks they imply. To address this issue, we propose FieldTripOrganizer, a field trip planner based on the…
Descriptors: Foreign Countries, Field Trips, Computer Assisted Instruction, Educational Planning
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Yong Jik Lee; Robert O. Davis – Contemporary Educational Technology, 2024
This research investigated the effects of generative AI on affective factors (motivation, interest, and confidence) of English as a foreign language (EFL) learners enrolled in Korean university-level general English courses. During the Spring 2024 semester, this study involved 89 participants exposed to a generative AI-based instruction model.…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Artificial Intelligence
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Akbar Bahari; Parviz Alavinia; Mohammad Mohammadi – Journal of Computer Assisted Learning, 2024
Background: This study investigates the effects of higher and lower-level text processing strategies on both higher and lower-level processing skills and cognitive load using the computer-assisted interactive reading model (CAIRM) as the educational intervention framework. Objectives: The objectives of this study are to examine the effects of the…
Descriptors: Computer Assisted Instruction, Experiential Learning, Reading, Cognitive Processes
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Chen, Binbin; Bao, Lina; Zhang, Rui; Zhang, Jingyu; Liu, Feng; Wang, Shuai; Li, Mingjiang – Journal of Educational Computing Research, 2024
Language learning has increasingly benefited from Computer-Assisted Language Learning (CALL) technologies, especially with Artificial Intelligence involved in recent years. CALL in writing learning acknowledged as the core of language learning is being realized by technologies like Automated Writing Evaluation (AWE), and Automated Essay Scoring…
Descriptors: Computer Assisted Instruction, English (Second Language), Second Language Learning, Writing Instruction
Chante Glick – ProQuest LLC, 2024
There are currently approximately 180,000 Registered Behavior Technicians® (RBT®s) (Behavior Analyst Certification Board, n.d.) To become an RBT, one must complete 40 hours of training and pass a competency assessment and an exam. The initial training is frequently conducted though asynchronous online platforms. To our knowledge, there has been…
Descriptors: Electronic Learning, Asynchronous Communication, Computer Assisted Instruction, Allied Health Personnel
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Pankaj Chejara; Luis P. Prieto; Yannis Dimitriadis; Maria Jesus Rodriguez-Triana; Adolfo Ruiz-Calleja; Reet Kasepalu; Shashi Kant Shankar – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…
Descriptors: Learning Analytics, Attribution Theory, Acoustics, Artificial Intelligence
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Micah Watanabe; Megan Imundo; Katerina Christhilf; Tracy Arner; Danielle S. McNamara – Grantee Submission, 2024
Reading comprehension is essential for students' ability to build knowledge. Students' comprehension abilities can be enhanced by providing students with deliberate practice and formative feedback on reading comprehension strategies. iSTART is an Intelligent Tutoring System (ITS) that is designed to provide instruction in reading strategies with…
Descriptors: Reading Comprehension, Reading Strategies, Intelligent Tutoring Systems, Reading Instruction
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Ulfia Rahmi; Bayu Ramadhani Fajri; Azrul Azrul – Journal of Learning for Development, 2024
The end of the pandemic era has brought new changes and challenges to lectures held in a blended learning environment, one of which is the use of interactive content. The objective of this study was to analyse, develop and evaluate the presentation of content using H5P in blended learning, its relevance to lecture topics, activities to achieve…
Descriptors: Learning Management Systems, Blended Learning, Educational Technology, Computer Assisted Instruction
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Vysakh Kani Kolil; Krishnashree Achuthan – Education and Information Technologies, 2024
The integration of Virtual Laboratories (VLs) into blended learning environments in science education offers a multifaceted educational experience that bridges the gap between theoretical knowledge and practical application. This approach provides dynamic, interactive learning opportunities that can be customized to meet various educational needs…
Descriptors: Computer Assisted Instruction, Electronic Learning, Laboratory Experiments, Chemistry
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Rebekah M. Chiasson; Alan K. Goodboy; Megan A. Vendemia; Nathaniel Beer; Gracyn C. Meisz; Laken Cooper; Alyssa Arnold; Austin Lincoski; William George; Cole Zuckerman; Jessica Schrout – Communication Education, 2024
Three within-subject experiments were conducted by providing students with answers to content questions across different subject matters (a definition, explanation, and example) offered by a human professor (subject-matter expert) versus generative artificial intelligence (ChatGPT). In a randomized order, students read both the expert and…
Descriptors: College Faculty, Expertise, Artificial Intelligence, Man Machine Systems
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Charlotte Beal; Rolf Steier – International Journal of Computer-Supported Collaborative Learning, 2024
In this study, we investigate how pre-service teachers' group dialogues emerged and intersected across time and space as students collaboratively constructed a video-based mind map to prepare for oral exams in a pedagogy course. The study was conducted as part of a design-based research project investigating the ways that video-based mind maps can…
Descriptors: Video Technology, Technology Uses in Education, Cooperative Learning, Concept Mapping
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Asma Almusharraf; Hassan Saleh Mahdi; Haifa Al-Nofaie; Amal Aljasser – Journal of Computer Assisted Learning, 2024
Background study: Computer-assisted pronunciation training (CAPT) has emerged as an important resource for second language (L2) pronunciation learning. CAPT offers diverse opportunities for learners to master L2 pronunciation with the help of authentic learning activities in multiple contexts. Objectives: This study presents a comprehensive…
Descriptors: Computer Assisted Instruction, Pronunciation Instruction, Second Language Learning, Second Language Instruction
Navjot Singh – ProQuest LLC, 2024
The rapid growth of edge computing, 5G, and IoT technologies has led to a significant increase in distributed data, creating both opportunities and challenges for machine learning. Federated learning has emerged as a promising approach to enable collaborative model training across decentralized devices while not sharing user data. However,…
Descriptors: Artificial Intelligence, Cooperative Learning, Communications, Efficiency
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