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Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
Barana, Alice; Marchisio, Marina; Roman, Fabio – International Association for Development of the Information Society, 2023
The spread of Artificial Intelligence (AI) has been recently generating worries among teachers and educators about the validity of assessment when students make use of AI tools to solve tasks. To tackle this issue, we propose mathematical problem solving activities to be carried out with the aid of ChatGPT, showing how problem solving and critical…
Descriptors: Artificial Intelligence, Mathematics Instruction, Problem Solving, Critical Thinking
Betty Exintaris; Nilushi Karunaratne; Elizabeth Yuriev – Journal of Chemical Education, 2023
Successful problem solving is a complex process that requires content knowledge, process skills, developed critical thinking, metacognitive awareness, and deep conceptual reasoning. Teaching approaches to support students developing problem-solving skills include worked examples, metacognitive and instructional scaffolding, and variations of these…
Descriptors: College Bound Students, Problem Solving, Metacognition, Scaffolding (Teaching Technique)
Clayton Cohn; Caitlin Snyder; Joyce Horn Fonteles; Ashwin T. S.; Justin Montenegro; Gautam Biswas – British Journal of Educational Technology, 2025
Recent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open-ended environments. AI…
Descriptors: Cooperation, Researchers, Artificial Intelligence, STEM Education
Tristan Kumor; Lida Uribe-Flórez; Jesús Trespalacios; Dazhi Yang – TechTrends: Linking Research and Practice to Improve Learning, 2024
There has been a limited amount of research that has attempted to determine teaching strategies using adaptive learning systems. Most studies have attempted to measure success of the use of these technologies based on improvements in students' test scores but have lacked to provide any information regarding the pedagogy implemented while using the…
Descriptors: High School Teachers, Mathematics Teachers, Teacher Attitudes, Teaching Methods
Akmanchi, Suchitra; Bird, Kelli A.; Castleman, Benjamin L. – Annenberg Institute for School Reform at Brown University, 2023
Prediction algorithms are used across public policy domains to aid in the identification of at-risk individuals and guide service provision or resource allocation. While growing research has investigated concerns of algorithmic bias, much less research has compared algorithmically-driven targeting to the counterfactual: human prediction. We…
Descriptors: Academic Advising, Artificial Intelligence, Algorithms, Prediction
Takami, Kyosuke; Flanagan, Brendan; Dai, Yiling; Ogata, Hiroaki – Smart Learning Environments, 2023
In the age of artificial intelligence (AI), trust in AI systems is becoming more important. Explainable recommenders, which explain why an item is recommended, have recently been proposed in the field of learning technology to improve transparency, persuasiveness, and trustworthiness. However, the methods for generating explanations are limited…
Descriptors: Artificial Intelligence, Personality, Cognitive Processes, Public Health
Sintha Wahjusaputri; Tashia Indah Nastiti; Bunyamin; Wati Sukmawati – Journal of Education and Learning (EduLearn), 2024
The objective of this study is to examine and assess the progress of utilizing artificial intelligence (AI) in teaching factory learning to enhance the digital skills of vocational high school (SMK) students in the province of Central Java. This study employed a qualitative approach utilizing meta-ethnography, as well as a quantitative approach…
Descriptors: Artificial Intelligence, Vocational High Schools, Foreign Countries, Digital Literacy
HeeWon Hong; YeonKyoung Kim – Education and Information Technologies, 2024
Career education for students with disabilities during their transition to adulthood is of utmost importance for their career planning and preparation. To implement effective career education for students with disabilities, it is necessary to use technology that provides new learning experiences. This study investigates the impact of an artificial…
Descriptors: Artificial Intelligence, Career Education, Students with Disabilities, Educational Technology
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
Shashi Kant Shankar; Gayathri Pothancheri; Deepu Sasi; Shitanshu Mishra – International Journal of Artificial Intelligence in Education, 2025
In education, the utilization of EdTech tools diverges notably between developed and developing nations, a dichotomy attributed to multiple factors like Technological Infrastructure, Digital Literacy, Digital Pedagogy, Tools, and Content. Recent research studies highlight that Generative AI's potential use and integration might exacerbate this…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Educational Technology
Wang, Yi; King, Ronnel; Haw, Joseph; Leung, Shing on – Journal for the Study of Education and Development, 2023
Although Macau students have consistently been recognized as top performers in international assessments, little research has been conducted to explore the various factors that are associated with their achievement. This paper aimed to identify factors that could best predict Macau students' reading achievement using PISA 2018 data provided by…
Descriptors: Foreign Countries, High School Students, Reading Achievement, Predictor Variables
Nicole Vargas – ProQuest LLC, 2023
Artificial intelligence in education (AIED) is an exigent topic of concern across educational settings. While artificial intelligence (AI) is not new, integrating it into K-12 schools has created a mix of positive and negative perceptions regarding how to do so effectively. The purpose of this phenomenological study was to examine teachers'…
Descriptors: High School Teachers, Teacher Attitudes, Artificial Intelligence, Instructional Materials
Lahoud, Christine; Moussa, Sherin; Obeid, Charbel; El Khoury, Hicham; Champin, Pierre-Antoine – Education and Information Technologies, 2023
Academic advising is inhibited at most of the high schools to help students identify appropriate academic pathways. The choice of a career domain is significantly influenced by the complexity of life and the volatility of the labor market. Thus, high school students feel confused during the shift period from high school to university, especially…
Descriptors: Academic Advising, Artificial Intelligence, Majors (Students), Career Guidance
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