Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 6 |
| Since 2007 (last 20 years) | 14 |
Descriptor
| Intelligent Tutoring Systems | 14 |
| Problem Solving | 14 |
| Science Instruction | 14 |
| Teaching Methods | 9 |
| Physics | 7 |
| Computer Software | 6 |
| Instructional Effectiveness | 6 |
| Models | 6 |
| College Students | 5 |
| Academic Achievement | 4 |
| Cooperative Learning | 4 |
| More ▼ | |
Source
Author
Publication Type
| Journal Articles | 10 |
| Reports - Research | 7 |
| Collected Works - Proceedings | 4 |
| Reports - Evaluative | 2 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 10 |
| Postsecondary Education | 8 |
| Secondary Education | 6 |
| High Schools | 4 |
| Junior High Schools | 4 |
| Middle Schools | 4 |
| Elementary Education | 3 |
| Adult Education | 1 |
| Grade 6 | 1 |
| Grade 7 | 1 |
| Grade 8 | 1 |
| More ▼ | |
Audience
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 1 |
What Works Clearinghouse Rating
Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics
Katz, Sandra; Albacete, Patricia; Chounta, Irene-Angelica; Jordan, Pamela; McLaren, Bruce M.; Zapata-Rivera, Diego – International Journal of Artificial Intelligence in Education, 2021
Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However,…
Descriptors: Physics, Science Instruction, Pretests Posttests, Scores
Rathod, Balraj B.; Murthy, Sahana; Bandyopadhyay, Subhajit – Journal of Chemical Education, 2019
"Is this solution pink enough?" is a persistent question when it comes to phenolphthalein-based titration experiments, one that budding, novice scientists often ask their instructors. Lab instructors usually answer the inquiry with remarks like, "Looks like you have overshot the end point", "Perhaps you should check the…
Descriptors: Handheld Devices, Telecommunications, Chemistry, Intelligent Tutoring Systems
Aravind, Vasudeva Rao; Croyle, Kevin – Malaysian Online Journal of Educational Technology, 2017
Students learn scientific concepts and mathematical calculations relating to scientific principles by repetition and reinforcement. Teachers and instructors cannot practically spend the long time required during tutorials to patiently teach students the calculations. Usually, teachers assign homework to provide practice to students, hoping that…
Descriptors: Physics, College Science, Computation, Scientific Concepts
Hagge, Mathew; Amin-Naseri, Mostafa; Jackman, John; Guo, Enruo; Gilbert, Stephen B.; Starns, Gloria; Faidley, Leann – Advances in Engineering Education, 2017
Students learn when they connect new information to existing understanding or when they modify existing understanding to accept new information. Most current teaching methods focus on trying to get students to solve problems in a manner identical to that of an expert. This study investigates the effectiveness of assessing student understanding…
Descriptors: Intelligent Tutoring Systems, Thermodynamics, Problem Solving, Decision Making
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
Lee, Young-Jin – Educational Technology & Society, 2015
This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…
Descriptors: Physics, Science Instruction, Computer Software, Accuracy
Kopp, Kristopher J.; Britt, M. Anne; Millis, Keith; Graesser, Arthur C. – Learning and Instruction, 2012
The current studies investigated the efficient use of dialogue in intelligent tutoring systems that use natural language interaction. Such dialogues can be relatively time-consuming. This work addresses the question of how much dialogue is needed to produce significant learning gains. In Experiment 1, a full dialogue condition and a read-only…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Mediated Communication, Synchronous Communication
Baker, Ryan S. J. d.; Corbett, Albert T.; Gowda, Sujith M. – Journal of Educational Psychology, 2013
Recently, there has been growing emphasis on supporting robust learning within intelligent tutoring systems, assessed by measures such as transfer to related skills, preparation for future learning, and longer term retention. It has been shown that different pedagogical strategies promote robust learning to different degrees. However, the student…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Genetics, Science Instruction
Hausmann, Robert G. M.; VanLehn, Kurt – International Journal of Artificial Intelligence in Education, 2010
Self-explaining is a domain-independent learning strategy that generally leads to a robust understanding of the domain material. However, there are two potential explanations for its effectiveness. First, self-explanation generates additional "content" that does not exist in the instructional materials. Second, when compared to…
Descriptors: Instructional Design, Intelligent Tutoring Systems, College Students, Predictor Variables
Krusberg, Zosia A. C. – Journal of Science Education and Technology, 2007
Three emerging technologies in physics education are evaluated from the interdisciplinary perspective of cognitive science and physics education research. The technologies--Physlet Physics, the Andes Intelligent Tutoring System (ITS), and Microcomputer-Based Laboratory (MBL) Tools--are assessed particularly in terms of their potential at promoting…
Descriptors: Intelligent Tutoring Systems, Physics, Science Laboratories, Educational Technology
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Sampson, Demetrios G., Ed.; Spector, J. Michael, Ed.; Ifenthaler, Dirk, Ed.; Isaias, Pedro, Ed. – International Association for Development of the Information Society, 2013
These proceedings contain the papers of the IADIS International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2013), October 22-24, 2013, which has been organized by the International Association for Development of the Information Society (IADIS), co-organized by The University of North Texas (UNT), sponsored by the…
Descriptors: Conference Papers, Cognitive Processes, Learning Processes, Short Term Memory
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

Peer reviewed
Direct link
