Publication Date
| In 2015 | 0 |
| Since 2014 | 0 |
| Since 2011 (last 5 years) | 2 |
| Since 2006 (last 10 years) | 2 |
| Since 1996 (last 20 years) | 2 |
Descriptor
| Prediction | 2 |
| Probability | 2 |
| Academic Achievement | 1 |
| Algebra | 1 |
| Bayesian Statistics | 1 |
| Computer Software | 1 |
| Correlation | 1 |
| Data | 1 |
| Evaluation | 1 |
| Geometry | 1 |
| More ▼ | |
Source
| International Educational… | 2 |
Author
| Aleven, Vincent | 2 |
| Baker, Ryan S. J. d. | 1 |
| Goldin, Ilya M. | 1 |
| Gowda, Sujith M. | 1 |
| Kalka, Jessica | 1 |
| Koedinger, Kenneth R. | 1 |
| Kusbit, Gail W. | 1 |
| Ocumpaugh, Jaclyn | 1 |
| Rossi, Lisa | 1 |
| Salvi, Aatish | 1 |
| More ▼ | |
Publication Type
| Reports - Evaluative | 2 |
| Speeches/Meeting Papers | 2 |
Education Level
Audience
Showing all 2 results
Download full textBaker, Ryan S. J. d.; Gowda, Sujith M.; Wixon, Michael; Kalka, Jessica; Wagner, Angela Z.; Salvi, Aatish; Aleven, Vincent; Kusbit, Gail W.; Ocumpaugh, Jaclyn; Rossi, Lisa – International Educational Data Mining Society, 2012
In recent years, the usefulness of affect detection for educational software has become clear. Accurate detection of student affect can support a wide range of interventions with the potential to improve student affect, increase engagement, and improve learning. In addition, accurate detection of student affect could play an essential role in…
Descriptors: Academic Achievement, Algebra, Tutors, Computer Software
Goldin, Ilya M.; Koedinger, Kenneth R.; Aleven, Vincent – International Educational Data Mining Society, 2012
Although ITSs are supposed to adapt to differences among learners, so far, little attention has been paid to how they might adapt to differences in how students learn from help. When students study with an Intelligent Tutoring System, they may receive multiple types of help, but may not comprehend and make use of this help in the same way. To…
Descriptors: Performance Factors, Intelligent Tutoring Systems, Individual Differences, Prediction
