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Showing 1 to 15 of 65 results Save | Export
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Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Matti Tedre – IEEE Transactions on Learning Technologies, 2025
The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer Science Education, Grade 4
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Ayse Alkan; Ezgi Pelin Yildiz – International Journal of Research in Education and Science, 2024
The main goal of this study is to reveal special talented primary school students' perceptions of artificial intelligence, one of the popular concepts of recent times, through metaphors. In this study, the phenomenological design, which is within the scope of qualitative research, was used. In this study, Türkiye Science and Art Center included…
Descriptors: Foreign Countries, Gifted, Elementary School Students, Middle School Students
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Yannik Fleischer; Susanne Podworny; Rolf Biehler – Statistics Education Research Journal, 2024
This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…
Descriptors: Decision Making, Data Use, Cognitive Processes, Artificial Intelligence
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Helen Zhang; Anthony Perry; Irene Lee – International Journal of Artificial Intelligence in Education, 2025
The rapid expansion of Artificial Intelligence (AI) in our society makes it urgent and necessary to develop young students' AI literacy so that they can become informed citizens and critical consumers of AI technology. Over the past decade many efforts have focused on developing curricular materials that make AI concepts accessible and engaging to…
Descriptors: Test Construction, Test Validity, Measures (Individuals), Artificial Intelligence
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Okan Bulut; Tarid Wongvorachan; Surina He; Soo Lee – Discover Education, 2024
Despite its proven success in various fields such as engineering, business, and healthcare, human-machine collaboration in education remains relatively unexplored. This study aims to highlight the advantages of human-machine collaboration for improving the efficiency and accuracy of decision-making processes in educational settings. High school…
Descriptors: High School Students, Dropouts, Identification, Man Machine Systems
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Seda Göktepe Körpeoglu; Sevda Göktepe Yildiz – International Journal of Science Education, 2024
Numerous artificial intelligence methods have lately been applied in education. This study proposes an Adaptive Neural-network-based Fuzzy Logic (ANFIS) model combining fuzzy logic and artificial neural networks for predicting students' STEM attitudes. The inputs of the research were determined as grade levels and academic achievement scores, and…
Descriptors: Foreign Countries, Middle School Students, STEM Education, Student Attitudes
John Ross – Region 8 Comprehensive Center, 2024
Artificial intelligence (AI) has been making considerable inroads into everyday lives, and AI applications and resources can be found in homes, businesses, entertainment venues, and--of course--in schools. The rapid rate at which AI is being integrated into education and placed in the hands of students, teachers, and other staff has prompted a…
Descriptors: Artificial Intelligence, Elementary Schools, Middle Schools, High Schools
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Woongbin Park; Hyuksoo Kwon – International Journal of Technology and Design Education, 2024
The purpose of this study is multifold: First, to develop an educational program using artificial intelligence (AI) in middle school free semester system of South Korea. Second, to verify the program's effectiveness, the study clarified the definition of AI and AI education and considered their meaning in technology education. This study used…
Descriptors: Foreign Countries, Middle Schools, Artificial Intelligence, Program Effectiveness
Scott Cameron; Carmel Mesiti – Mathematics Education Research Group of Australasia, 2024
In their daily work teachers are responsible for several complex tasks; might AI be harnessed to support teachers in the challenging work of planning lessons? In this paper we investigate the use of an AI tool, namely ChatGPT, to generate a lesson plan that may be of use to teachers in their planning. A carefully worded prompt, informed by…
Descriptors: Artificial Intelligence, Mathematics Education, Lesson Plans, Computer Assisted Instruction
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Kyosuke Takami; Brendan Flanagan; Yiling Dai; Hiroaki Ogata – International Journal of Distance Education Technologies, 2024
Explainable recommendation, which provides an explanation about why a quiz is recommended, helps to improve transparency, persuasiveness, and trustworthiness. However, little research examined the effectiveness of the explainable recommender, especially on academic performance. To survey its effectiveness, the authors evaluate the math academic…
Descriptors: Bayesian Statistics, Epistemology, Mathematics Achievement, Artificial Intelligence
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Marcelo Fernando Rauber; Christiane Gresse von Wangenheim; Pedro Alberto Barbetta; Adriano Ferreti Borgatto; Ramon Mayor Martins; Jean Carlo Rossa Hauck – Informatics in Education, 2024
The insertion of Machine Learning (ML) in everyday life demonstrates the importance of popularizing an understanding of ML already in school. Accompanying this trend arises the need to assess the students' learning. Yet, so far, few assessments have been proposed, most lacking an evaluation. Therefore, we evaluate the reliability and validity of…
Descriptors: Artificial Intelligence, Measures (Individuals), Test Reliability, Test Validity
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Anna Trifonova; Mariela Destéfano; Mario Barajas – Digital Education Review, 2024
This article proposes a comprehensive AI curriculum tailored for young learners aged 11 to 14, emphasizing a humanistic approach. We review other AI curricula proposals for children and young people and underline that they focus primarily on AI's technological benefits and on learning coding and logic. Our curriculum explores human cognition that…
Descriptors: Artificial Intelligence, Cognitive Processes, Children, Constructivism (Learning)
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Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
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Gülçin Kurkan; Münevver Çetin – International Journal of Contemporary Educational Research, 2024
Artificial intelligence technologies are used in many fields and have become a part of our lives. The field of artificial intelligence, which has an important place, especially in the field of education and digital leadership, is constantly developing and is expected to create even greater impacts in the future. The main purpose of this research…
Descriptors: Administrator Attitudes, Artificial Intelligence, Technology Uses in Education, Instructional Leadership
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Ramon Mayor Martins; Christiane G. Von Wangenheim; Marcelo F. Rauber; Adriano F. Borgatto; Jean C. R. Hauck – ACM Transactions on Computing Education, 2024
As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…
Descriptors: Artificial Intelligence, Computer Science Education, Socioeconomic Status, Correlation
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