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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
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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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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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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Kason Ka Ching Cheung; Jack K. H. Pun; Wangyin Li – Research in Science Education, 2024
ChatGPT becomes a prominent tool for students' learning of science when students "read" its scientific texts. Students read to learn about climate change misinformation using ChatGPT, while they develop critical awareness of the content, linguistic features as well as nature of AI and science to comprehend these texts. In this…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Secondary School Students
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Seow Yongzhi – IAFOR Journal of Education, 2024
Humanities education in Singapore at the secondary level emphasises the inquiry-based learning pedagogical approach to engage students, inculcate critical thinking skills, and achieve the necessary knowledge and skills outcomes stipulated by the national curriculum. Inquiry-based learning is structured by a Humanities inquiry cycle involving four…
Descriptors: Debate, Teaching Methods, Artificial Intelligence, Humanities Instruction
de Vera, Shaun P. – ProQuest LLC, 2023
Contributing to a growing body of research on broadening participation in computing for historically underrepresented racial communities (e.g., Black and Latinx), this qualitative study describes the knowledge (content and sources) six antiracist Computer Science (CS) teachers have about examples (and counterexamples) of modern techno-racism, a…
Descriptors: Racism, Computer Science Education, Middle School Teachers, High School Teachers
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Asselman, Amal; Khaldi, Mohamed; Aammou, Souhaib – Interactive Learning Environments, 2023
Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by…
Descriptors: Algorithms, Artificial Intelligence, Factor Analysis, Student Behavior
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Ramon Mayor Martins; Christiane Gresse Von Wangenheim; Marcelo Fernando Rauber; Jean Carlo Rossa Hauck; Melissa Figueiredo Silvestre – Informatics in Education, 2024
Knowledge about Machine Learning (ML) is becoming essential, yet it remains a restricted privilege that may not be available to students from a low socio-economic status background. Thus, in order to provide equal opportunities, we taught ML concepts and applications to 158 middle and high school students from a low socio-economic background in…
Descriptors: Middle School Students, High School Students, Low Income Students, Socioeconomic Status
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Xia, Qi; Chiu, Thomas K. F.; Chai, Ching Sing – Education and Information Technologies, 2023
Artificial intelligence (AI) has the potential to support self-regulated learning (SRL) because of its strong anthropomorphic characteristics. However, most studies of AI in education have focused on cognitive outcomes in higher education, and little research has examined how psychological needs affect SRL with AI in the K-12 setting. SRL is a…
Descriptors: Artificial Intelligence, Grade 9, Student Needs, Gender Differences
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Ramon Mayor Martins; Christiane Gresse von Wangenheim; Marcelo Fernando Rauber; Jean Carlo Hauck – International Journal of Artificial Intelligence in Education, 2024
Although Machine Learning (ML) is found practically everywhere, few understand the technology behind it. This presents new challenges to extend computing education by including ML concepts in order to help students to understand its potential and limits and empowering them to become creators of intelligent solutions. Therefore, we developed an…
Descriptors: Artificial Intelligence, Information Technology, Technology Uses in Education, Computer Software
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Xia, Qi; Chiu, Thomas K. F.; Chai, Ching Sing; Xie, Kui – British Journal of Educational Technology, 2023
The anthropomorphic characteristics of artificial intelligence (AI) can provide a positive environment for self-regulated learning (SRL). The factors affecting adolescents' SRL through AI technologies remain unclear. Limited AI and disciplinary knowledge may affect the students' motivations, as explained by self-determination theory (SDT). In this…
Descriptors: Secondary School Students, Grade 9, Needs, Satisfaction
Kurtz, Holly; Lloyd, Sterling; Harwin, Alex; Daniels, Ashlee; Cheseldine, Sarah – Editorial Projects in Education, 2023
In a trend buoyed by new technology purchased to accommodate the remote learning necessitated by the coronavirus pandemic, educators are increasingly using devices and apps to teach core subjects, including math. This report examines perceptions and experiences of teachers, principals, and district leaders around the use of such tools for math…
Descriptors: Educational Technology, Technology Uses in Education, Mathematics Instruction, Teacher Attitudes
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Xiaofang Liao; Xuedi Zhang; Zhifeng Wang; Heng Luo – British Journal of Educational Technology, 2024
Formative assessment is essential for improving teaching and learning, and AI and visualization techniques provide great potential for its design and delivery. Using NLP, cognitive diagnostic and visualization techniques designed to analyse and present students' monthly exam data, we developed an AI-enabled visual report tool comprising six…
Descriptors: Artificial Intelligence, Design, Program Implementation, Formative Evaluation
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Vladislav Slavov; Kamelia Yotovska; Asya Asenova – International Association for Development of the Information Society, 2023
Artificial intelligence (AI) technology is already challenging a variety of societal areas, including education. It is transforming education to data driven. AI-enhanced technologies in education (abbreviated AIinED) will have a significant role in changing the teaching and learning methods, as well as impacting the behavior and organization of…
Descriptors: Artificial Intelligence, High School Students, Student Attitudes, Technology Uses in Education
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