NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 36 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Peer reviewed Peer reviewed
Direct linkDirect link
Mandal, Sourav; Naskar, Sudip Kumar – IEEE Transactions on Learning Technologies, 2021
Solving mathematical (math) word problems (MWP) automatically is a challenging research problem in natural language processing, machine learning, and education (learning) technology domains, which has gained momentum in the recent years. Applications of solving varieties of MWPs can increase the efficacy of teaching-learning systems, such as…
Descriptors: Classification, Word Problems (Mathematics), Problem Solving, Arithmetic
Peer reviewed Peer reviewed
Direct linkDirect link
King, Emily C.; Benson, Max; Raysor, Sandra; Holme, Thomas A.; Sewall, Jonathan; Koedinger, Kenneth R.; Aleven, Vincent; Yaron, David J. – Journal of Chemical Education, 2022
This report showcases a new type of online homework system that provides students with a free-form interface and dynamic feedback. The ORCCA Tutor (Open-Response Chemistry Cognitive Assistance Tutor) is a production rules-based online tutoring system utilizing the Cognitive Tutoring Authoring Tools (CTAT) developed by Carnegie Mellon University.…
Descriptors: Intelligent Tutoring Systems, Chemistry, Homework, Feedback (Response)
Vincent Aleven; Jori Blankestijn; LuEttaMae Lawrence; Tomohiro Nagashima; Niels Taatgen – Grantee Submission, 2022
Past research has yielded ample knowledge regarding the design of analytics-based tools for teachers and has found beneficial effects of several tools on teaching and learning. Yet there is relatively little knowledge regarding the design of tools that support teachers when a class of students uses AI-based tutoring software for self-paced…
Descriptors: Educational Technology, Artificial Intelligence, Problem Solving, Intelligent Tutoring Systems
Peer reviewed Peer reviewed
Direct linkDirect link
Viktor Wang, Editor – IGI Global, 2025
Artificial Intelligence (AI) integration in andragogical education offers significant enhancements to the learning experience for adult learners. By utilizing AI-powered platforms, instructors can provide personalized learning paths that adapt to the unique needs, interests, and goals of each individual. These systems can analyze performance data…
Descriptors: Andragogy, Artificial Intelligence, Computer Software, Technology Integration
Peer reviewed Peer reviewed
Direct linkDirect link
Davy Tsz Kit Ng; Jiahong Su; Jac Ka Lok Leung; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
Artificial intelligence (AI) literacy has emerged to equip students with digital skills for effective evaluation, communication, collaboration, and ethical use of AI in online, home, and workplace settings. Countries are increasingly developing AI curricula to support students' technological skills for future studies and careers. However, there is…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Secondary School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Hershcovits, Haviv; Vilenchik, Dan; Gal, Kobi – IEEE Transactions on Learning Technologies, 2020
This paper studies students engagement in e-learning environments in which students work independently and solve problems without external supervision. We propose a new method to infer engagement patterns of users in such self-directed environments. We view engagement as a continuous process in time, measured along chosen axes that are derived…
Descriptors: Electronic Learning, Problem Solving, Independent Study, Factor Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Barollet, Théo; Bouchez Tichadou, Florent; Rastello, Fabrice – International Educational Data Mining Society, 2021
In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…
Descriptors: Intelligent Tutoring Systems, Prediction, Internet, Purchasing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
Paneque, Juan J.; Cobo, Pedro; Fortuny, Josep M. – Technology, Knowledge and Learning, 2017
This ethnographical study aims to interpret how an intelligent tutorial system, geogebraTUTOR, mediates to the student's argumentative processes. Data consisted of four geometrical problems proposed to a group of four students aged 16-17. Qualitative analysis of two selected cases led to the identification of the development of argumentative…
Descriptors: Ethnography, Intelligent Tutoring Systems, Geometry, Mathematics Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Rastegarmoghadam, Mahin; Ziarati, Koorush – Education and Information Technologies, 2017
Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…
Descriptors: Teaching Methods, Problem Solving, Intelligent Tutoring Systems, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Khodeir, Nabila Ahmed; Elazhary, Hanan; Wanas, Nayer – International Journal of Information and Learning Technology, 2018
Purpose: The purpose of this paper is to present an algorithm to generate story problems via controlled parameters in the domain of mathematics. The generation process is performed in the problem generation module in the context of an intelligent tutoring system suggested in this paper. Controlling the question parameters allows for adapting the…
Descriptors: Problem Solving, Teaching Methods, Difficulty Level, Natural Language Processing
Peer reviewed Peer reviewed
Direct linkDirect link
Hoppe, H. Ulrich – International Journal of Artificial Intelligence in Education, 2016
The 1998 paper by Martin Mühlenbrock, Frank Tewissen, and myself introduced a multi-agent architecture and a component engineering approach for building open distributed learning environments to support group learning in different types of classroom settings. It took up prior work on "multiple student modeling" as a method to configure…
Descriptors: Guidelines, Intelligent Tutoring Systems, Cooperative Learning, Modeling (Psychology)
Previous Page | Next Page »
Pages: 1  |  2  |  3