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AI and Machine Learning Techniques in the Development of Intelligent Tutoring System: A Review

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TLDR
An Intelligent Tutoring System (ITS) is critical in education because it provides one-to-one personalized teaching assistance to learners as they educate how to solve problems through guidance and prompt feedback as mentioned in this paper.
Abstract
An Intelligent Tutoring System (ITS) is critical in education because it provides one to one personalized teaching assistance to learners as they educate how to solve problems through guidance and prompt feedback. ITS is one application of Artificial Intelligence (AI) in education. It provides a smart learning environment for students without intervention from the teacher. ITS's primary goal is to support and help learners obtain domain-specific intellectual knowledge in a practical and productive manner through the use of different computing technologies. This paper presents a comprehensive survey for previous research on ITS that utilize various techniques of AI and Machine Learning (ML). It gives an overview of ITS, its architecture, and some existing ITS examples. In addition, it highlights and summarizes the current research efforts and obstacles to ITS using AI, as well as some future opportunities. This study shows the importance of AI and ML in ITS development. It is noticed that researchers focus more on Reinforcement Learning (RL), Artificial Neural Networks (ANN), clustering, Bayesian Network (BN) and Fuzzy Logic (FL) approaches.

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Citations
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Journal ArticleDOI

A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions

TL;DR: A huge and statistically significant increase in the learning outcomes is observed, with students on the Korbit platform providing full feedback resulting in higher course completion rates and achieving learning gains 2 to 2.5 times higher than both students on a MOOC platform and students in a control group who don’t receive personalized feedback.
Journal ArticleDOI

Leveraging Large Language Model and Story-Based Gamification in Intelligent Tutoring System to Scaffold Introductory Programming Courses: A Design-Based Research Study

Chen Cao
- 25 Feb 2023 - 
TL;DR: In this article , a gamification intelligent tutoring system was developed to adapt to Chinese international students learning needs and provide scaffolding to support their success in introductory computer programming courses and increase Chinese students sense of belonging in introductory programming courses.
Proceedings ArticleDOI

Scaffolding CS1 Courses with a Large Language Model-Powered Intelligent Tutoring System

Chen Cao
TL;DR: In this article , a gamification intelligent tutoring system was developed to adapt to Chinese international students' learning needs and provide scaffolding to support their success in introductory computer programming courses.
Journal ArticleDOI

A fuzzy-based mechanism for automatic personalized assessment in an e-learning system for computer programming

TL;DR: In this article , a fuzzy-based mechanism is presented for automatic personalized assessment in an e-learning system for computer programming, where the selection of the most appropriate test items for each individual student is based on a variety of criteria: (i) the student's knowledge level, (ii) prior knowledge of computer programming and (iii) the type of programming errors that the student is prone to make, and (iv) the difficulty level of the test items.
Proceedings ArticleDOI

Survey for Smart and Adaptative Education

TL;DR: In this article , the authors identify the most recent studies on the application of artificial intelligence in education and make a comparative study of the different models and existing applications that use this technology to promote learning efficiently.
References
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Book

The Teaching Gap: Best Ideas from the World's Teachers for Improving Education in the Classroom

TL;DR: Stigler and Hiebert as discussed by the authors compared the teaching practices in Japan and Germany with those in the United States and found that American teachers are not incompetent, but the methods they use are severely limited, and American teaching has no system in place for getting better.
Journal ArticleDOI

Intelligent tutoring systems and learning outcomes: A meta-analysis

TL;DR: In this paper, a meta-analysis was conducted on research that compared the outcomes from students learning from Intelligent Tutoring Systems (ITS) to those learning from non-ITS learning environments.
Journal ArticleDOI

Evolution and Revolution in Artificial Intelligence in Education

TL;DR: It is suggested that two parallel strands of research need to take place in order to impact education in the next 25 years: one is an evolutionary process, focusing on current classroom practices, collaborating with teachers, and diversifying technologies and domains, and the other is a revolutionary process.
Proceedings ArticleDOI

ITSPOKE: an intelligent tutoring spoken dialogue system

TL;DR: ITSPOKE is a spoken dialogue system that uses the Why2-Atlas text-based tutoring system as its "back-end" and generates an empirically-based understanding of the ramifications of adding spoken language capabilities to text- based dialogue tutors.

Artificial intelligence in education : challenges and opportunities for sustainable development

TL;DR: In this article, a new curriculum for a digital and AI-powered world is proposed, which is based on a post-basic education and training curriculum for AI-enabled learners.