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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)
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
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
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
Zachary Opps – ProQuest LLC, 2024
As the use of artificial intelligence (AI), especially machine learning (ML), has dramatically increased, K-12 schools have begun to deliver AI education; however, little is known about teachers' views on the field. This qualitative study investigated how U.S. high school computer science (CS) teachers conceptualize AI, the role of AI in their CS…
Descriptors: Artificial Intelligence, High School Teachers, Computer Science Education, Teacher Education
Muhamad Taufik Hidayat – Journal of Learning for Development, 2024
The ability to comprehend reading material is a crucial skill for academic and professional success, yet many students struggle with it, negatively impacting their academic performance. This study aimed to assess the effectiveness of AI-based personalised reading platforms in improving reading comprehension among senior high school students. The…
Descriptors: Artificial Intelligence, Reading Comprehension, Academic Achievement, High School Students
Hunkoog Jho; Minsu Ha – Journal of Baltic Science Education, 2024
This study aimed at examining the performance of generative artificial intelligence to extract argumentation elements from text. Thus, the researchers developed a web-based framework to provide automated assessment and feedback relying on a large language model, ChatGPT. The results produced by ChatGPT were compared to human experts across…
Descriptors: Feedback (Response), Artificial Intelligence, Persuasive Discourse, Models
Xiaodong Huang; Chengche Qiao – Science & Education, 2024
Artificial intelligence is the unification of philosophy, cognitive science, mathematics, neurophysiology, psychology, computer science, information theory, cybernetics, and uncertainty theory. Therefore, it is feasible and necessary to utilize STEAM (Science, Technology, Engineering, Liberal Arts, and Mathematics) education to learn artificial…
Descriptors: Thinking Skills, Artificial Intelligence, STEM Education, Art Education
Georgios A. Bazoukis; Spyros T. Halkidis; Evangelos Pepes; Pantelis Venardos – European Journal of Science and Mathematics Education, 2024
The problem behind our research that was investigated was the evaluation of an artificial intelligence in education tool, namely ASSISTments by seventy one science and technology students in a small city. The objective was to find to what extent the students assimilate this tool. The data collection and instrumentation were done by the tool…
Descriptors: Ethics, Mathematics Instruction, Science Education, Technology Education
Jiseung Yoo; Jisun Park; Minsu Ha; Chelcea Mae Lagmay Darang – SAGE Open, 2024
In the context of formative assessment in classrooms, the incorporation of automated evaluation (AE) systems and teachers' interactions with them hold significant importance. This study aimed to investigate the cognitive processes of pre-service teachers as they engaged with an AE system. We developed an unsupervised learning-based AE system, the…
Descriptors: Preservice Teachers, Cognitive Processes, Automation, Supervision
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
Lin Zhang; Qiang Jiang; Weiyan Xiong; Wei Zhao – Journal of Educational Computing Research, 2025
This study seeks to deepen the understanding of the direct and indirect effects of human-computer dialogic interaction programming activities, facilitated by ChatGPT, on student engagement. Data were collected from 109 Chinese high school students who engaged in programming tasks using either ChatGPT-driven dialogic interaction or traditional pair…
Descriptors: Artificial Intelligence, Computer Software, Computer Science Education, Programming
Wei Li; Jia-Wei Ji; Judy C. R. Tseng; Cheng-Ye Liu; Ji-Yi Huang; Hai-Ying Liu; Mo Zhou – Educational Technology & Society, 2025
Education is an important way to achieve global Sustainable Development Goals (SDGs), while classroom engagement and collective efficacy are key factors that influence SDG learning outcomes. However, students' in-depth thinking could be limited when they apply to search engines such as Google to support their learning of SDG-related topics. Large…
Descriptors: Learner Engagement, Self Efficacy, Critical Thinking, Artificial Intelligence
Eran Hadas; Arnon Hershkovitz – Journal of Learning Analytics, 2025
Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…
Descriptors: Creativity, Evaluation Methods, Computer Assisted Testing, Artificial Intelligence
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