The week's pick
Reseach Article
Smart Tutor an Intelligent Tutoring System for C Sharp Programming Bahria University Karachi Campus
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 180 - Number 27 |
| Year of Publication: 2018 |
| Authors: Asma Khan, M. Junaid Quadri, Muhammad Noman |
10.5120/ijca2018916646
|
Asma Khan, M. Junaid Quadri, Muhammad Noman . Smart Tutor an Intelligent Tutoring System for C Sharp Programming Bahria University Karachi Campus. International Journal of Computer Applications. 180, 27 ( Mar 2018), 28-33. DOI=10.5120/ijca2018916646
Abstract
In this paper, application software has been presented called as smart Tutor, which in reality an intelligent tutoring System. The proposed system will let the user to learn the C# programming language. The decision making process conducted in our intelligent system is guided by a Bayesian network approach to support students in learning computer programming, which is framework for uncertainty management in the field of Artificial management. This system would provide a platform for the students to understand the basic programming concepts through sequence of training concept of programming language. In this paper we will discuss about how system is integrated with Bayesian network as an inference engine to improve student learning process. The significance of this work is that ,it has replaced the traditional Static Tutorials, Where students learn through video tutorials or text lectures who never come to know about the student learning potential or either the learner has learnt the topic properly before moving on to the next topic. ST will lead the student to navigate through all the available online Course material and will provide the necessary recommendations.
References
- A Bayes Net Toolkit for Student Modeling in Intelligent Tutoring Systems Kai-min Chang, Joseph Beck, Jack Mostow, and Albert Corbett
- Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques.
- “A Brief Introduction to Graphical Models and Bayesian Networks”, By Kevin Murphy, 1998.
- Mitrovic, A. (2003). An Intelligent SQL Tutor on the Web. International Journal of Artificial Intelligence in Education, 13(2-4), 171-195
- Using Bayesian Networks to Manage Uncertainty in Student Modeling, by Cristina Conati, Abigail Gertner and Kurt VanLehn
- A Web-based Bayesian Intelligent Tutoring System for Computer Programming, C.J. Butz, S. Hua, R.B. Maguire Department of Computer Science
- Adaptive and Intelligent Web-based Educational Systems, Peter Brusilovsky and Christoph Peylo
- The Past, the Present and the Future of adaptive E-Learning, Felix Mödritscher, Victor Manuel Garcia-Barrios and Christian Gütl.
- Shute, V.J.; Psotka, J.: Intelligent tutoring systems: Past, present and future. In book Handbook of research on educational communications and technology, 1995.
- Advances in Intelligent Tutoring Systems: Problem-solving Modes and Model of Hints, Alla Anohina-Naumeca
- C.W. Woo, Instructional Planning in an Intelligent Tutoring System: Combining Global Lesson Plans with Local Discourse Control, Ph.D. Thesis, Illinois Institute of Technology, Chicago, IL, 1991
- N.L. Zhang, D. Poole, A simple approach to Bayesian network computations, in: Proceedings of The 10th canadian Conference on Artificial Intelligence, Banff, Alberta, Canada, 1994, pp. 171-178
- Jim Reye. Student Modelling based on Belief Networks. International Journal of Artificial Intelligence in Education (IJAIED), 2004, 14, pp.63-96.
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