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Adeolu Tolu Ebenezer Oyebode – ProQuest LLC, 2024
The COVID-19 pandemic led to an increase in Online learning. With this increase comes several challenges for instructors and students such as connectivity issues and student engagement. Organizations are spending millions of dollars developing emerging technologies such as emotion AI and other AI applications without taking cognizance of users'…
Descriptors: Teaching Methods, Synchronous Communication, Electronic Learning, Emotional Intelligence
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Christopher Dignam; Candace M. Smith; Amy L. Kelly – Journal of Education in Science, Environment and Health, 2025
The evolution of artificial intelligence (AI) and robotics in education has transitioned from automation toward emotionally responsive learning systems through artificial emotional intelligence (AEI). While AI-driven robotics has enhanced instructional automation, AEI introduces an affective dimension by recognizing and responding to human…
Descriptors: Robotics, Artificial Intelligence, Teaching Methods, Computer Software
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Gyuhun Jung; Markel Sanz Ausin; Tiffany Barnes; Min Chi – International Educational Data Mining Society, 2024
We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Artificial Intelligence, Teaching Methods
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Michael E. Ellis; K. Mike Casey; Geoffrey Hill – Decision Sciences Journal of Innovative Education, 2024
Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming…
Descriptors: Artificial Intelligence, Programming Languages, Programming, Homework
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Md. Mirajul Islam; Xi Yang; John Hostetter; Adittya Soukarjya Saha; Min Chi – International Educational Data Mining Society, 2024
A key challenge in e-learning environments like Intelligent Tutoring Systems (ITSs) is to induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL) often suffers from "sample inefficiency" and "reward function" design difficulty, Apprenticeship Learning (AL) algorithms can overcome them.…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Teaching Methods, Algorithms
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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)
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Giulia Polverini; Bor Gregorcic – Physical Review Physics Education Research, 2024
The well-known artificial intelligence-based chatbot ChatGPT-4 has become able to process image data as input in October 2023. We investigated its performance on the test of understanding graphs in kinematics to inform the physics education community of the current potential of using ChatGPT in the education process, particularly on tasks that…
Descriptors: Computer Software, Artificial Intelligence, Visual Impairments, Graphs
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Stankov, Lazar; Lee, Jihyun – Journal of Intelligence, 2020
This paper examined the effects of training in creative problem-solving on intelligence. We revisited Stankov's report on the outcomes of an experiment carried out by R. Kvashchev in former Yugoslavia that reported an IQ increase of seven points, on average, across 28 tests of intelligence. We argue that previous analyses were based on a…
Descriptors: Intelligence Quotient, Comparative Analysis, Creativity, Problem Solving
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Murphy, Michelle Pauley; Hung, Woei – TechTrends: Linking Research and Practice to Improve Learning, 2023
One hundred years ago, Paul Weiss and Ludwig von Bertalanffy independently proposed that living organisms interact with their environment through systems. In the century that has followed, systems thinking and modeling have grown in tandem with discovery of the vast complexity of the universe at microscopic through astronomic levels. As our…
Descriptors: Systems Approach, Cognitive Processes, Artificial Intelligence, Learning Processes
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Sternberg, Robert J. – Education Sciences, 2021
This article introduces the concept of adaptive intelligence--the intelligence one needs to adapt to current problems and anticipate future problems of real-world environments--and discusses its implications for education. Adaptive intelligence involves not only promoting one's own ability to survive and thrive, but also that of others in one's…
Descriptors: Intelligence, Adjustment (to Environment), Creative Thinking, Logical Thinking
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Joalise Janse van Rensburg – Discover Education, 2024
The ability to think critically is an important and valuable skill that students should develop to successfully solve problems. The process of writing requires critical thinking (CT), and the subsequent piece of text can be viewed as a product of CT. One of the strategies educators may use to develop CT is modelling. Given ChatGPT's ability to…
Descriptors: Critical Thinking, Writing Instruction, Computer Software, Artificial Intelligence
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Suna-Seyma Uçar; Inigo Lopez-Gazpio; Josu Lopez-Gazpio – Education and Information Technologies, 2025
Recent advancements in large language models (LLMs) have shown potential in enhancing educational practices, particularly in technology-assisted learning environments. This study critically evaluates the reasoning capabilities of LLMs, such as ChatGPT, within the context of chemistry education. We designed targeted adversarial prompts that…
Descriptors: Abstract Reasoning, Thinking Skills, Artificial Intelligence, Technology Uses in Education
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Matsuda, Noboru – International Journal of Artificial Intelligence in Education, 2022
This paper demonstrates that a teachable agent (TA) can play a dual role in an online learning environment (OLE) for learning by teaching--the teachable agent working as a synthetic peer for students to learn by teaching and as an interactive tool for cognitive task analysis when authoring an OLE for learning by teaching. We have developed an OLE…
Descriptors: Artificial Intelligence, Teaching Methods, Intelligent Tutoring Systems, Feedback (Response)
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Michael E. Robbins; Gabriel J. DiQuattro; Eric W. Burkholder – Physical Review Physics Education Research, 2025
[This paper is part of the Focused Collection in Investigating and Improving Quantum Education through Research.] One of the greatest weaknesses of physics education research is the paucity of research on graduate education. While there are a growing number of investigations of graduate student degree progress and admissions, there are very few…
Descriptors: Science Education, College Science, Science Instruction, Teaching Methods
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Andrey Lavrenov; Sergei Pozdniakov – Computers in the Schools, 2025
Currently, there is a rapid development of artificial intelligence systems that can solve and explain the solution of mathematical problems in the same way as students do. The problem of organizing interaction of artificial and human intelligence which does not lead to the degradation of the student's thinking skills arises. The article proposes…
Descriptors: Artificial Intelligence, Problem Solving, Mathematics Education, Mathematics Skills
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