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Showing all 8 results Save | Export
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Andrew Kwok-Fai Lui; Sin-Chun Ng; Stella Wing-Nga Cheung – Interactive Learning Environments, 2024
The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…
Descriptors: Grading, Computer Uses in Education, Educational Technology, Artificial Intelligence
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Bambang Sulistio; Arief Ramadhan; Edi Abdurachman; Muhammad Zarlis; Agung Trisetyarso – Education and Information Technologies, 2024
Computer science development, especially machine learning, is a thriving innovation essential for education. It makes the process of teaching and learning more accessible and manageable and also promotes equality. The positive influence of machine learning can also be felt in Islamic studies, particularly in Hadith studies. This literature review…
Descriptors: Electronic Learning, Artificial Intelligence, Computer Uses in Education, Islam
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Farrow, Robert – Learning, Media and Technology, 2023
Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term.…
Descriptors: Artificial Intelligence, Algorithms, Computer Uses in Education, Language Usage
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Jian-hui Wu – Journal of Educational Computing Research, 2025
The objective of this research is to investigate how AI-improved dynamic physical education materials impact middle school education in physical settings. Utilizing a randomized controlled crossover approach, a 16-week study involved 120 students aged 12 to 18 to evaluate the impact of AI-enhanced physical education courses against traditional…
Descriptors: Artificial Intelligence, Physical Education, Instructional Materials, Middle School Students
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Siu-Cheung Kong; Wei Shen – Interactive Learning Environments, 2024
Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…
Descriptors: Student Characteristics, Predictor Variables, Comprehension, Computation
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Lonneke Boels; Enrique Garcia Moreno-Esteva; Arthur Bakker; Paul Drijvers – International Journal of Artificial Intelligence in Education, 2024
As a first step toward automatic feedback based on students' strategies for solving histogram tasks we investigated how strategy recognition can be automated based on students' gazes. A previous study showed how students' task-specific strategies can be inferred from their gazes. The research question addressed in the present article is how data…
Descriptors: Eye Movements, Learning Strategies, Problem Solving, Automation
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Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
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Mena-Guacas, Andres F.; Urueña Rodríguez, Jairo Alonso; Santana Trujillo, David Mauricio; Gómez-Galán, José; López-Meneses, Eloy – Contemporary Educational Technology, 2023
The diversity of topics in education makes it difficult for artificial intelligence (AI) to address them all in depth. Therefore, guiding to focus efforts on specific issues is essential. The analysis of competency development by fostering collaboration should be one of them because competencies are the way to validate that the educational…
Descriptors: Cooperative Learning, Skill Development, Artificial Intelligence, Educational Development