Publication Date
In 2025 | 1 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Source
International Journal of… | 3 |
Author
Balyan, Renu | 1 |
Bernabé Batchakui | 1 |
Jaurès S. H. Kameni | 1 |
McCarthy, Kathryn S. | 1 |
McNamara, Danielle S. | 1 |
Ramírez Uresti, Jorge A. | 1 |
Roger Nkambou | 1 |
Valdés Aguirre, Benjamín | 1 |
du Boulay, Benedict | 1 |
Publication Type
Journal Articles | 3 |
Reports - Research | 3 |
Information Analyses | 1 |
Education Level
Audience
Location
Africa | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Flesch Kincaid Grade Level… | 1 |
What Works Clearinghouse Rating
Jaurès S. H. Kameni; Bernabé Batchakui; Roger Nkambou – International Journal of Artificial Intelligence in Education, 2025
The majority of Sub-Saharan African countries are facing a very negative teacher-learner ratio: one teacher for over 120 learners. In order to support the learner training, we propose optimizing search engines for learning contexts, to enable learners to take optimal advantage of the vast reservoir of Open Educational Resources (OER) available on…
Descriptors: Foreign Countries, Teacher Shortage, Open Educational Resources, Computer Assisted Instruction
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers