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Ali, Farhan; Choy, Doris; Divaharan, Shanti; Tay, Hui Yong; Chen, Wenli – Learning: Research and Practice, 2023
Self-directed learning and self-assessment require student responsibility over learning needs, goals, processes, and outcomes. However, this student-led learning can be challenging to achieve in a classroom limited by a one-to-many teacher-led instruction. We, thus, have designed and prototyped a generative artificial intelligence chatbot…
Descriptors: Independent Study, Self Evaluation (Individuals), Artificial Intelligence, Man Machine Systems
Christopher H. Clark, Editor; Cathryn van Kessel, Editor – Teachers College Press, 2025
Whether skeptical or enthusiastic about AI, every social studies educator will find something useful for their practice in this book. The introduction of widely available generative AI tools has caused a frenzy of both positive and negative reactions. Between utopian visions and apocalyptic predictions of AI's impact on education, there is a need…
Descriptors: Social Studies, Artificial Intelligence, Technology Uses in Education, Computer Software
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Dai, Zilin; McReynolds, Andrew; Whitehill, Jacob – International Educational Data Mining Society, 2023
We explore multi-modal machine learning-based approaches (facial expression recognition, auditory emotion recognition, and text sentiment analysis) to identify "negative moments" of teacher-student interaction during classroom teaching. Our analyses on a large (957 videos, each 20min) dataset of classroom observations suggest that: (1)…
Descriptors: Teacher Behavior, Negative Attitudes, Nonverbal Communication, Teacher Student Relationship
UK Department for Education, 2024
This report sets out the findings of the technical development work completed as part of the Use Cases for Generative AI in Education project, commissioned by the Department for Education (DfE) in September 2023. It has been published alongside the User Research Report, which sets out the findings from the ongoing user engagement activity…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Computational Linguistics
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Gadanidis, George – International Journal of Information and Learning Technology, 2017
Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…
Descriptors: Artificial Intelligence, Computation, Mathematics Education, Elementary School Mathematics
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Utecht, Jeff; Keller, Doreen – Critical Questions in Education, 2019
This paper will examine the eight principles of Connectivism Learning Theory and provide examples of how institutions of learning--K-12 and higher education--may think about applying them. Engaging in such work will allow institutions to take advantage of technological platforms as they exist today and into the future. While the Internet has…
Descriptors: Learning Theories, Elementary Schools, Secondary Schools, Critical Thinking
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Lenat, Douglas B.; Durlach, Paula J. – International Journal of Artificial Intelligence in Education, 2014
We often understand something only after we've had to teach or explain it to someone else. Learning-by-teaching (LBT) systems exploit this phenomenon by playing the role of "tutee." BELLA, our sixth-grade mathematics LBT systems, departs from other LTB systems in several ways: (1) It was built not from scratch but by very slightly…
Descriptors: Artificial Intelligence, Knowledge Level, Mathematics Instruction, Teaching Methods
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Yang, Chih-Wei; Kuo, Bor-Chen; Liao, Chen-Huei – Turkish Online Journal of Educational Technology - TOJET, 2011
The aim of the present study was to develop an on-line assessment system with constructed response items in the context of elementary mathematics curriculum. The system recorded the problem solving process of constructed response items and transfered the process to response codes for further analyses. An inference mechanism based on artificial…
Descriptors: Foreign Countries, Mathematics Curriculum, Test Items, Problem Solving
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Pavlekovic, Margita; Zekic-Susac, Marijana; Djurdjevic, Ivana – Computers & Education, 2009
This paper compares the efficiency of two intelligent methods: expert systems and neural networks, in detecting children's mathematical gift at the fourth grade of elementary school. The input space for the expert system and the neural network model consisted of 60 variables describing five basic components of a child's mathematical gift…
Descriptors: Gifted, Psychological Evaluation, Artificial Intelligence, Grade 4
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Huang, Chenn-Jung; Wang, Yu-Wu; Huang, Tz-Hau; Chen, Ying-Chen; Chen, Heng-Ming; Chang, Shun-Chih – Computers & Education, 2011
Recent research indicated that students' ability to construct evidence-based explanations in classrooms through scientific inquiry is critical to successful science education. Structured argumentation support environments have been built and used in scientific discourse in the literature. To the best of our knowledge, no research work in the…
Descriptors: Electronic Learning, Feedback (Response), Persuasive Discourse, Teaching Load