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Fletcher Wadsworth; Josh Blaney; Matthew Springsteen; Bruce Coburn; Nischal Khanal; Tessa Rodgers; Chase Livingston; Suresh Muknahallipatna – International Journal of Technology in Education and Science, 2024
Artificial Intelligence (AI) and, more specifically, Machine Learning (ML) methodologies have successfully tailored commercial applications for decades. However, the recent profound success of large language models like ChatGPT and the enormous subsequent funding from governments and investors have positioned ML to emerge as a paradigm-shifting…
Descriptors: Secondary School Students, Artificial Intelligence, High School Teachers, College Faculty
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Jacqueline Corcoran; Malitta Engstrom; Kate Ledwith; Gerard Jefferies; Tamara J. Cadet – Journal of Teaching in Social Work, 2025
Competency-based education in social work (CSWE, 2022) demands active learning methods that demonstrate professional competencies and practice behaviors. Role-plays and simulations are methods that link learning in the classroom with practice. This article explores role-play and simulation variants: basic role-play, real play, student-scripted…
Descriptors: Role Playing, Simulation, Social Work, Competency Based Education
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Pin-Hui Li; Hsin-Yu Lee; Chia-Ju Lin; Wei-Sheng Wang; Yueh-Min Huang – Journal of Educational Computing Research, 2025
The core purpose of integrating inquiry-based learning strategies into STEM activities is to create a challenging learning environment that stimulates students' active learning, thereby effectively enhancing their interest in learning, thinking skills, and practical application abilities. To achieve these goals, developing more technology-assisted…
Descriptors: Computer Software, Artificial Intelligence, Synchronous Communication, Active Learning
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Boutilier, Justin J.; Chan, Timothy C. Y. – INFORMS Transactions on Education, 2023
Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning…
Descriptors: Artificial Intelligence, Operations Research, Undergraduate Students, Engineering Education
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Hui-Tzu Chang; Chia-Yu Lin – IEEE Transactions on Education, 2024
Contribution: This study incorporates competition-based learning (CBL) into machine learning courses. By engaging students in innovative problem-solving challenges within information competitions, revealing that students' participation in online problem-solving competitions can improve their information technology, and showcase competitions can…
Descriptors: Competition, Artificial Intelligence, Curriculum, Problem Solving
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Qing Wang; Xizhen Cai – Journal of Statistics and Data Science Education, 2024
Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…
Descriptors: Active Learning, Class Activities, Classification, Artificial Intelligence
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Ting-Ting Wu; Hsin-Yu Lee; Pei-Hua Chen; Chia-Ju Lin; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Science, Technology, Engineering, and Mathematics (STEM) education in Asian universities struggles to integrate Knowledge, Skills, and Attitudes (KSA) due to large classes and student reluctance. While ChatGPT offers solutions, its conventional use may hinder independent critical thinking. Objectives: This study introduces PA-GPT,…
Descriptors: Peer Evaluation, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Rim Gouia-Zarrad; Cindy Gunn – International Electronic Journal of Mathematics Education, 2024
This research paper explores the integration of ChatGPT as a tool for interactive learning of numerical methods in a differential equations (DEs) course. DE course is crucial for engineering students to model real-world phenomena. However, many DE courses focus only on analytical solutions and neglect important numerical solutions. To overcome…
Descriptors: Learning Experience, Teaching Methods, Artificial Intelligence, Computer Software
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Viktoriia V. Sydorenko; Inna O. Akhnovska; Sergiy V. Smirnov; Igor A. Verbovskyi; Olha V. Melnychuk – Journal of Education and Learning (EduLearn), 2024
The research is focused on a comprehensive analysis of digitalization as a prerequisite for higher education modernization. The authors of this article consider the digital divide as a component of information inequality, which has a technological nature and presupposes unequal opportunities for access, use, and production of information and…
Descriptors: Educational Improvement, Higher Education, Digital Literacy, Technology Uses in Education
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Steven Michels – Journal of Political Science Education, 2024
The advent of artificial intelligence and concerns over academic integrity have put instructors from every discipline on notice regarding the kinds of coursework we are assigning. But this is also a moment to deliver content in a manner that is clearer and more dynamic, use more active forms of learning, and improve the academic and professional…
Descriptors: Political Science, Artificial Intelligence, Computer Software, Teaching Methods
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Voss, Julia; Shaghaghi, Navid; Calle, Andres Mauricio; Lee, Kristin; Abbate, Liam – Across the Disciplines, 2022
Although Writing Across the Curriculum (WAC) has long focused on incorporating writing and related literacy activities into STEM education, the extent to which these pedagogies are widely used in STEM teaching remains unclear, as does their impact on student course performance, especially for underrepresented and marginalized student groups. Using…
Descriptors: Photography, Artificial Intelligence, STEM Education, Teaching Methods
Staci Freeworth – ProQuest LLC, 2021
The purpose of this study was to explore faculty members' lived experiences with student resistance in a gateway STEM classroom. A comparative investigation was done of the case study population to evaluate differences in experiences in active learning classes that use LAs (LAF) and classes that use more passive methods without LAs (NLA). The…
Descriptors: College Faculty, College Students, STEM Education, Introductory Courses
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Michelle Allgood; Paul Musgrave – Journal of Public Affairs Education, 2024
The potential benefits and challenges of AI in the workplace are documented with public service facing a particular choice to leverage this tool to better communities. This article explores the use of generative artificial intelligence (AI) tools in public service education. As students prepare to enter public service, they need to gain the skills…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Human Resources
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Ching-Yi Chang; Patcharin Panjaburee; Shao-Chen Chang – Interactive Learning Environments, 2024
Educators have recognized the importance of providing a realistic learning environment which helps learners to not only comprehend learning content, but also to link the content to practical problems. Such an environment can hence foster problem-solving skills in nursing training. However, when learners interact in a virtual environment with rich…
Descriptors: Artificial Intelligence, Context Effect, Nursing Education, Technology Integration
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Ariya Azamatova; Nuraisha Bekeyeva; Kulyay Zhaxylikova; Arailym Sarbassova; Nagima Ilyassova – International Journal of Education in Mathematics, Science and Technology, 2023
The aim of this study is to determine the effect of digital tools and artificial intelligence applications on the achievement, motivation and retention of university students on the basis of project-based teaching approach in foreign language course. Pre-test post-test experimental design with control group was used as the method in the study. A…
Descriptors: Artificial Intelligence, Academic Achievement, Student Motivation, Active Learning
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