Review of Intelligent Tutoring Systems: At the Crossroads of Artificial Intelligence and Education.

1991 ◽  
Vol 36 (12) ◽  
pp. 1114-1114
Author(s):  
No authorship indicated
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Tutoring Systems

Artificial Intelligence in Education

2021 ◽  
pp. 256-277
Author(s):  
Rashmi Khazanchi ◽  
Pankaj Khazanchi
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Pedagogical Practices ◽  
Student Centered ◽  
Tutoring Systems ◽  
Artificial Intelligence In Education ◽  
K 12 ◽  
Insight Into

Current educational developments in theories and practices advocate a more personalized, student-centered approach to teach 21st-century skills. However, the existing pedagogical practices cannot provide optimal student engagement as they follow a ‘one size fits all' approach. How can we provide high-quality adaptive instructions at a personalized level? Intelligent tutoring systems with embedded artificial intelligence can assist both students and teachers in providing personalized support. This chapter highlights the role of artificial intelligence in the development of intelligent tutoring systems and how these are providing personalized instructions to students with and without disabilities. This chapter gives insight into the challenges and barriers posed by the integration of intelligent tutoring systems in K-12 classrooms.

Constructing Intelligent Tutoring Systems Based on a Multiagent Architecture

2008 ◽  
pp. 228-259 ◽  
Author(s):  
Ig Bittencourt ◽  
Evandro de Barros Costa ◽  
Baldoíno Fonseca dos Santos Neto ◽  
João Guilherme Maia de Menezes ◽  
Jairo Simão Santana Melo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Reference Model ◽  
Intelligent Tutoring ◽  
Tutoring Systems ◽  
Education Community ◽  
Artificial Intelligence In Education ◽  
Relevant Topic ◽  
Pedagogical Models

Tools to make the development of intelligent tutoring systems (ITS) easier and more efficient are a relevant topic within the artificial intelligence in education community. This chapter presents a set of tools for constructing multiagent-based ITS, and describes a methodology for guiding the development of ITS. The main goal is to make multiagent-based ITS development more efficient and useful for both developers and authors. This has been done to support development of tutors based on Mathema’s environment as a reference model. Basically, in order to create a particular ITS, authors have to consider three main steps concerned with domain, student, and pedagogical models. A case study is presented to demonstrate the effectiveness of the proposed approach. Results of this case study show that this proposal makes the process of building the considered ITS easier and more efficient.

scholarly journals Methods and Standards for Research on Explainable Artificial Intelligence: Lessons from Intelligent Tutoring Systems

2021 ◽  
Author(s):  
Robert Hoffman ◽  
William Clancey
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Tutoring Systems ◽  
Explainable Artificial Intelligence ◽  
Explainable Ai

We reflect on the progress in the area of Explainable AI (XAI) Program relative to previous work in the area of intelligent tutoring systems (ITS). A great deal was learned about explanation—and many challenges uncovered—in research that is directly relevant to XAI. We suggest opportunities for future XAI research deriving from ITS methods, as well as the challenges shared by both ITS and XAI in using AI to assist people in solving difficult problems effectively and efficiently.

scholarly journals Incorporation of Artificial Intelligence Tutoring Techniques in Mathematics

2016 ◽  
Vol 6 (4) ◽  
pp. 12 ◽  
Author(s):  
Marios Pappas ◽  
Athanasios Drigas
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Mathematics Education ◽  
Expert Systems ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Personalized Feedback ◽  
Tutoring Systems ◽  
Artificial Intelligence Techniques ◽  
Human Tutor

Intelligent Tutoring Systems incorporate Artificial Intelligence techniques, in order to imitate a human tutor. These expert systems are able to assess student’s proficiency, to provide solved examples and exercises for practice in each topic, as well as to provide immediate and personalized feedback to learners. The present study is a systematic review that evaluates the contribution of the Intelligent Tutoring Systems developed so far, to Mathematics Education, representing some of the most representative studies of the last decade.

scholarly journals Artificial Intelligence and Its Role in Education

2021 ◽  
Vol 13 (22) ◽  
pp. 12902
Author(s):  
Sayed Fayaz Ahmad ◽  
Mohd. Khairil Rahmat ◽  
Muhammad Shujaat Mubarik ◽  
Muhammad Mansoor Alam ◽  
Syed Irfan Hyder
Keyword(s):  
Artificial Intelligence ◽  
Significant Role ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Education Sector ◽  
Access To Education ◽  
Tutoring Systems ◽  
Smart Learning ◽  
Modern Methods

The objective of this study is to explore the role of artificial intelligence applications (AIA) in education. AI applications provide the solution in many ways to the exponential rise of modern-day challenges, which create difficulties in access to education and learning. They play a significant role in forming social robots (SR), smart learning (SL), and intelligent tutoring systems (ITS) to name a few. The review indicates that the education sector should also embrace the modern methods of teaching and the necessary technology. Looking into the flow, the education sector organizations need to adopt AI technologies as a necessity of the day and education. The study needs to be tested statistically for better understanding and to make the findings more generalized in the future.

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