Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Artificial Intelligence | 2 |
| Intelligent Tutoring Systems | 2 |
| Knowledge Representation | 2 |
| Learning Theories | 2 |
| Automation | 1 |
| Computer Uses in Education | 1 |
| Decision Making | 1 |
| Instructional Design | 1 |
| Models | 1 |
| Tutors | 1 |
Source
| Technology, Instruction,… | 2 |
Author
| Scandura, Joseph M. | 2 |
| Novak, Elena | 1 |
Publication Type
| Journal Articles | 2 |
| Reference Materials -… | 1 |
| Reports - Descriptive | 1 |
| Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkScandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2018
This paper summarizes key stages in development of the Structural Learning Theory (SLT) and explains how and why it is now possible to model human tutors in a highly efficient manner. The paper focuses on evolution of the SLT, a deterministic theory of teaching and learning, on which AuthorIT authoring and TutorIT delivery systems have been built.…
Descriptors: Artificial Intelligence, Models, Tutors, Learning Theories
Scandura, Joseph M.; Novak, Elena – Technology, Instruction, Cognition and Learning, 2017
AuthorIT and TutorIT represent a fundamentally different approach to building and delivering adaptive learning systems. Intelligent Tutoring Systems (ITS) guide students as they solve problems. BIG DATA systems make pedagogical decisions based on average student performance. Decision making in AuthorIT and TutorIT is designed to model the human…
Descriptors: Intelligent Tutoring Systems, Decision Making, Knowledge Representation, Learning Theories
