Publication Date
| In 2015 | 0 |
| Since 2014 | 2 |
| Since 2011 (last 5 years) | 3 |
| Since 2006 (last 10 years) | 3 |
| Since 1996 (last 20 years) | 3 |
Descriptor
Source
| International Journal of… | 3 |
Author
| Baker, Ryan S. J. D. | 1 |
| Durlach, Paula J. | 1 |
| Goldstein, Adam B. | 1 |
| Heffernan, Neil T. | 1 |
| Lenat, Douglas B. | 1 |
| Pareto, Lena | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 2 |
| Reports - Evaluative | 1 |
Education Level
| Grade 6 | 3 |
| Elementary Education | 2 |
| Middle Schools | 2 |
| Early Childhood Education | 1 |
| Grade 2 | 1 |
| Grade 3 | 1 |
| Grade 4 | 1 |
| Grade 5 | 1 |
| Grade 7 | 1 |
| Grade 8 | 1 |
| More ▼ | |
Audience
Showing all 3 results
Peer reviewed
Direct linkLenat, Douglas B.; Durlach, Paula J. – International Journal of Artificial Intelligence in Education, 2014
We often understand something only after we've had to teach or explain it to someone else. Learning-by-teaching (LBT) systems exploit this phenomenon by playing the role of "tutee." BELLA, our sixth-grade mathematics LBT systems, departs from other LTB systems in several ways: (1) It was built not from scratch but by very slightly…
Descriptors: Artificial Intelligence, Knowledge Level, Mathematics Instruction, Teaching Methods
Pareto, Lena – International Journal of Artificial Intelligence in Education, 2014
In this paper we will describe a learning environment designed to foster conceptual understanding and reasoning in mathematics among younger school children. The learning environment consists of 48 2-player game variants based on a graphical model of arithmetic where the mathematical content is intrinsically interwoven with the game idea. The…
Descriptors: Concept Formation, Mathematical Concepts, Mathematics Instruction, Educational Games
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level
