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Steven Van Zost – Journal of Teaching and Learning, 2025
Artificial intelligence (AI) transforms the ethical and moral subjectivity of teachers, positioning them to navigate the complex convergence of technological advancement, intellectual autonomy, and teacher identity. The purpose of this paper is to offer a conceptual model for how teachers' identities are constituted through AI prompt engineering.…
Descriptors: Artificial Intelligence, Professional Identity, Teachers, Computer Uses in Education
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Khalida Parveen; Abdulelah A. Alghamdi; Nagwan Abdel Samee; Muhammad Shafiq – Journal of Educational Computing Research, 2025
As technology rapidly evolves, generative AI tools are increasingly integrated across various fields, including education. ChatGPT, a well-known language model developed by OpenAI, has gained significant importance in educational settings. This study employed a quantitative, cross-sectional survey design and employed the Unified Theory of…
Descriptors: Artificial Intelligence, Computer Uses in Education, College Students, Foreign Countries
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Ekaterina Tour; Artem Zadorozhnyy – Journal of Adolescent & Adult Literacy, 2025
Recent developments in Generative Artificial Intelligence (GenAI) technologies have had significant implications for English language education worldwide, opening up new opportunities and challenges. Both researchers and practitioners are increasingly exploring the necessary capabilities that English language learners should possess in relation to…
Descriptors: English (Second Language), Second Language Learning, Artificial Intelligence, Computer Uses in Education
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Denis Shchepakin; Sreecharan Sankaranarayanan; Dawn Zimmaro – International Educational Data Mining Society, 2024
Bayesian Knowledge Tracing (BKT) is a probabilistic model of a learner's state of mastery for a knowledge component. The learner's state is a "hidden" binary variable updated based on the correctness of the learner's responses to questions corresponding to that knowledge component. The parameters used for this update are inferred/learned…
Descriptors: Algorithms, Bayesian Statistics, Probability, Artificial Intelligence
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Suliman Zakaria Suliman Abdalla; Amal Khalfan Rashid AlSalti – Educational Process: International Journal, 2025
Background/purpose: This study examines the behavioral factors influencing the adoption of AI-powered generative technologies in higher education and their impact on students' cognitive engagement--a crucial element of sustainable, inclusive, and high-quality learning, as envisioned by UNESCO's Sustainable Development Goal 4 (SDG4). The study…
Descriptors: Artificial Intelligence, Cognitive Development, College Students, Computer Uses in Education
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Zhang, Lishan; Huang, Yuwei; Yang, Xi; Yu, Shengquan; Zhuang, Fuzhen – Interactive Learning Environments, 2022
Automatic short-answer grading has been studied for more than a decade. The technique has been used for implementing auto assessment as well as building the assessor module for intelligent tutoring systems. Many early works automatically grade mainly based on the similarity between a student answer and the reference answer to the question. This…
Descriptors: Automation, Grading, Models, Artificial Intelligence
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Tingting Li; Kevin Haudek; Joseph Krajcik – Journal of Science Education and Technology, 2025
Scientific modeling is a vital educational practice that helps students apply scientific knowledge to real-world phenomena. Despite advances in AI, challenges in accurately assessing such models persist, primarily due to the complexity of cognitive constructs and data imbalances in educational settings. This study addresses these challenges by…
Descriptors: Artificial Intelligence, Scientific Concepts, Models, Automation
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Te Hu; Zongmin Fu; Niya Wang; Jinbin Gui; Qinghe Song; Xiaofan Qian – Education and Information Technologies, 2025
Digital image processing is an integral part of the computer vision field. However, traditional digital image processing teaching methods mainly focus on theoretical knowledge, lacking practical teaching content. To address this issue, this article proposes a project-based learning (PBL) model that consists of four key stages: project proposal,…
Descriptors: Student Projects, Active Learning, Models, Computer Uses in Education
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Sense, Florian; Krusmark, Michael; Fiechter, Joshua; Collins, Michael G.; Sanderson, Lauren; Onia, Joshua; Jastrzembski, Tiffany – International Educational Data Mining Society, 2021
Cardiopulmonary resuscitation (CPR) is a foundational lifesaving skill for which medical personnel are expected to be proficient. Frequent refresher training is needed to prevent the involved skills from decaying. Regular low-dose, high-frequency training for staff at fixed intervals has proven successful at maintaining CPR competence but does not…
Descriptors: First Aid, Training, Artificial Intelligence, Prediction
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Zhai, Xiaoming; He, Peng; Krajcik, Joseph – Journal of Research in Science Teaching, 2022
Involving students in scientific modeling practice is one of the most effective approaches to achieving the next generation science education learning goals. Given the complexity and multirepresentational features of scientific models, scoring student-developed models is time- and cost-intensive, remaining one of the most challenging assessment…
Descriptors: Artificial Intelligence, Science Education, Models, Middle School Students
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Wang, Chunpai; Zhao, Siqian; Sahebi, Shaghayegh – International Educational Data Mining Society, 2021
The state of the art knowledge tracing approaches mostly model student knowledge using their performance in assessed learning resource types, such as quizzes, assignments, and exercises, and ignore the non-assessed learning resources. However, many student activities are non-assessed, such as watching video lectures, participating in a discussion…
Descriptors: Models, Knowledge Level, Artificial Intelligence, Computer Uses in Education
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Jia, Qinjin; Cui, Jialin; Xiao, Yunkai; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2021
Peer assessment has been widely applied across diverse academic fields over the last few decades, and has demonstrated its effectiveness. However, the advantages of peer assessment can only be achieved with high-quality peer reviews. Previous studies have found that high-quality review comments usually comprise several features (e.g., contain…
Descriptors: Peer Evaluation, Models, Artificial Intelligence, Evaluation Methods
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Lajoie, Susanne P. – International Journal of Artificial Intelligence in Education, 2021
I first met Jim Greer at the NATO Advanced Study Institute on Syntheses of Instructional Sciences and Computing Science for Effective Instructional Computing Systems in 1990 in Calgary, Canada. It was during this meeting that I came to realize that Jim was one of those rare individuals that could help "translate" computer science…
Descriptors: Models, Student Characteristics, Artificial Intelligence, Computer Uses in Education
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Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2018
This paper summarizes key stages in development of the Structural Learning Theory (SLT) and explains how and why it is now possible to model human tutors in a highly efficient manner. The paper focuses on evolution of the SLT, a deterministic theory of teaching and learning, on which AuthorIT authoring and TutorIT delivery systems have been built.…
Descriptors: Artificial Intelligence, Models, Tutors, Learning Theories
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Giannakos, Michail, Ed. – Lecture Notes in Educational Technology, 2020
This book introduces the reader to evidence-based non-formal and informal science learning considerations (including technological and pedagogical innovations) that have emerged in and empowered the information and communications technology (ICT) era. The contributions come from diverse countries and contexts (such as hackerspaces, museums,…
Descriptors: Nonformal Education, Informal Education, Science Education, Computer Uses in Education
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