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Showing 1 to 15 of 33 results Save | Export
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Qian Xu – Discover Education, 2024
This research suggests a methodology to examine the effectiveness Artificial Intelligence (AI) on the cognitive abilities of college students so that future researchers can utilize this experimental project to focus on how AI-powered Intelligent Tutoring Systems (ITSs) affect learning outcomes. As AI continues to revolutionize all walks of life,…
Descriptors: Artificial Intelligence, Cognitive Ability, College Students, Intelligent Tutoring Systems
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Wiegand, R. Paul; Bucci, Anthony; Kumar, Amruth N.; Albert, Jennifer; Gaspar, Alessio – ACM Transactions on Computing Education, 2022
In this article, we leverage ideas from the theory of coevolutionary computation to analyze interactions of students with problems. We introduce the idea of "informatively" easy or hard concepts. Our approach is different from more traditional analyses of problem difficulty such as item analysis in the sense that we consider Pareto…
Descriptors: Concept Formation, Difficulty Level, Computer Science Education, Problem Solving
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Conrad Borchers; Jiayi Zhang; Hendrik Fleischer; Sascha Schanze; Vincent Aleven; Ryan S. Baker – Journal of Educational Data Mining, 2025
Think-aloud protocols are a standard method to study self-regulated learning (SRL) during learning by problem-solving. Advances in automated transcription and large language models (LLMs) have automated the transcription and labeling of SRL in these protocols, reducing manual effort. However, while effective in many emerging applications, previous…
Descriptors: Artificial Intelligence, Protocol Analysis, Learning Strategies, Classification
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Xuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study
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Yung-Hsiang Hu – Education and Information Technologies, 2024
In this study, a generative artificial intelligence (AI)-assisted Think-Aloud Pair Problem-Solving (TAPPS) learning strategy was introduced to support ethical dilemma-related problem-solving learning activities. Then, an interactive virtual learning companion system was developed and tested in a business ethics course to evaluate the efficacy of…
Descriptors: Ethics, Problem Solving, Thinking Skills, Verbal Communication
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Chen, Xingliang; Mitrovic, Antonija; Mathews, Moffat – IEEE Transactions on Learning Technologies, 2020
Problem solving, worked examples, and erroneous examples have proven to be effective learning activities in Intelligent Tutoring Systems (ITSs). However, it is generally unknown how to select learning activities adaptively in ITSs to maximize learning. In the previous work of A. Shareghi Najar and A. Mitrovic, alternating worked examples with…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Learning Activities, Educational Technology
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Lamia, Mahnane; Mohamed, Hafidi – International Journal of Web-Based Learning and Teaching Technologies, 2019
Nowadays, students are becoming familiar with the computer technology at a very early age. Moreover, the wide availability of the internet gives a new perspective to distance education making e-learning environments crucial to the future of education. Intelligent tutoring systems (ITSs) provide sophisticated tutoring systems using artificial…
Descriptors: Problem Solving, Educational Technology, Technology Uses in Education, Intelligent Tutoring Systems
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Prihar, Ethan; Heffernan, Neil – International Educational Data Mining Society, 2021
Similar content has tremendous utility in classroom and online learning environments. For example, similar content can be used to combat cheating, track students' learning over time, and model students' latent knowledge. These different use cases for similar content all rely on different notions of similarity, which make it difficult to determine…
Descriptors: Computer Software, Middle School Teachers, Mathematics Teachers, College Students
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Aravind, Vasudeva Rao; McConnell, Marcella Kay – World Journal on Educational Technology: Current Issues, 2018
Educating our future citizens in science and engineering is vitally important to ensure future advancement. Presently, in the light of environmental sustainability, it is critical that students learn concepts relating to energy, its consumption and future demands. In this article, we harness the state of the educational technology, namely…
Descriptors: Intelligent Tutoring Systems, Science Instruction, Energy, Instructional Design
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Lavbic, Dejan; Matek, Tadej; Zrnec, Aljaž – Interactive Learning Environments, 2017
Today's software industry requires individuals who are proficient in as many programming languages as possible. Structured query language (SQL), as an adopted standard, is no exception, as it is the most widely used query language to retrieve and manipulate data. However, the process of learning SQL turns out to be challenging. The need for a…
Descriptors: Evaluation Methods, Information Systems, Intelligent Tutoring Systems, Computer Science Education
Pearson, 2018
Pearson sought to explore whether the use of MyLab Statistics, a teaching, learning and assessment system used to teach statistics at the higher education level, is related to higher exam scores. This Research Report presents findings from one research study: a correlational study conducted at Maastricht University School of Business and Economics…
Descriptors: Foreign Countries, Correlation, Statistics, Mathematics Instruction
Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil – International Educational Data Mining Society, 2015
A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…
Descriptors: Models, Student Behavior, Intelligent Tutoring Systems, Data Analysis
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Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Horng, Shi-Jinn; Lim, Heuiseok – Innovations in Education and Teaching International, 2018
In learning systems and environment research, intelligent tutoring and personalisation are considered the two most important factors. An Intelligent Tutoring System can serve as an effective tool to improve problem-solving skills by simulating a human tutor's actions in implementing one-to-one adaptive and personalised teaching. Thus, in this…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Skill Development, Programming
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Zhou, Guojing; Wang, Jianxun; Lynch, Collin F.; Chi, Min – International Educational Data Mining Society, 2017
In this study, we applied decision trees (DT) to extract a compact set of pedagogical decision-making rules from an original "full" set of 3,702 Reinforcement Learning (RL)- induced rules, referred to as the DT-RL rules and Full-RL rules respectively. We then evaluated the effectiveness of the two rule sets against a baseline Random…
Descriptors: Learning Theories, Teaching Methods, Decision Making, Intelligent Tutoring Systems
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Steif, Paul S.; Fu, Luoting; Kara, Levent Burak – Interactive Learning Environments, 2016
Problems faced by engineering students involve multiple pathways to solution. Students rarely receive effective formative feedback on handwritten homework. This paper examines the potential for computer-based formative assessment of student solutions to multipath engineering problems. In particular, an intelligent tutor approach is adopted and…
Descriptors: Formative Evaluation, Engineering Education, Problem Solving, Intelligent Tutoring Systems
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