Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Classification | 3 |
| Educational Experiments | 3 |
| Learning Processes | 3 |
| Computer Software | 2 |
| Foreign Countries | 2 |
| Instructional Design | 2 |
| Knowledge Representation | 2 |
| Models | 2 |
| Prediction | 2 |
| Programming | 2 |
| Accuracy | 1 |
| More ▼ | |
Author
| Baschera, Gian-Marco | 1 |
| Gross, Markus | 1 |
| Kellogg, Deborah L. | 1 |
| Liu, Jun | 1 |
| Sha, Sha | 1 |
| Smith, Marlene A. | 1 |
| Zhang, Wei | 1 |
| Zheng, Qinghua | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 2 |
| Reports - Descriptive | 1 |
Education Level
| Elementary Secondary Education | 2 |
| Elementary Education | 1 |
| Middle Schools | 1 |
Audience
Location
| China | 1 |
| Switzerland | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Smith, Marlene A.; Kellogg, Deborah L. – Decision Sciences Journal of Innovative Education, 2015
This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…
Descriptors: Group Activities, Assignments, Cooperative Learning, Individual Activities
Liu, Jun; Sha, Sha; Zheng, Qinghua; Zhang, Wei – International Journal of Distance Education Technologies, 2012
Assigning difficulty level indicators to the knowledge units helps the learners plan their learning activities more efficiently. This paper focuses on how to use the topology of a knowledge map to compute and rank the difficulty levels of knowledge units. Firstly, the authors present the hierarchical structure and properties of the knowledge map.…
Descriptors: Foreign Countries, Knowledge Level, Difficulty Level, Educational Technology
Baschera, Gian-Marco; Gross, Markus – International Journal of Artificial Intelligence in Education, 2010
We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…
Descriptors: Foreign Countries, Spelling, Intelligent Tutoring Systems, Prediction

Peer reviewed
Direct link
