SRS Intelligent Tutoring System

The aim of Intelligent Tutoring Systems (ITSs) is to provide students with personalized learning experiences through the use of deep-learning algorithms.These type of systems can have a direct impact on student learning, especially when it comes to the digital environments. Intelligent Tutoring Systems (ITSs) are computer systems that aim to provide personalized instruction and feedback to users, often through the use of AI technology and without a human teacher. ITSs have been receiving a lot of attention due to their ability to provide a one-on-one curriculum. The use of deep learning algorithms allows the systems to suggest certain studying strategies for individuals. ITSs have the opportunity to play a major role in the future of education, solving many of the problems that are present in the sector today. One of the greatest challenges surrounding the education of young individuals, and applicable to any individual regardless of age, is that humans are complicated and require personalized methods of learning to excel.

Scope of Project Intelligent Tutoring System:

Project scope is the part of project planning that involves determining and documenting a list of specific project  goals, deliverables, tasks, costs and deadlines. Defining the project scope involves adopting a clear vision and an agreement on the outcomes of the project. This allows each milestone of the project to stay on target

Functional and Non Functional Requirements ofIntelligent Tutoring System:

Functional Requirements :

A functional requirement shows that what the system must do what services the system present to users. It describes a software system or its component. A function is nothing but inputs to the software system, its behavior, and outputs

Functional Requirements of Intelligent Tutoring System:

System should contain artificial-intelligence component. The system must possess following
components (1) knowledge of the learner (student model), (2) knowledge of the domain (expert model), and (3) knowledge of teaching strategies (pedagogical model).
1. A student learns from an intelligent system primarily by solving problems – ones that are appropriately selected or tailormade, and that serve as learning experiences for that
student.
2. The system may start by assessing what the student already knows. Information about the student is maintained within what is called the student model, which is updated during the course of learning.
3. The system then must consider what the student needs to know. This information is
embodied in the domain-expert model.
4. Finally, the system must decide what unit of content (e.g., assessment task or instructional element) ought to be presented next, and how it should be presented. This is achieved by the pedagogical model (or tutor).
5. From all of these considerations, the system selects or generates a problem, then either
works out a solution to the problem (via the domain-expert model), or retrieves a prepared
solution. The intelligent system compares its solution to the one the student has prepared
and performs a diagnosis based on differences between the two as well as other
information available in the student model.
6. Feedback is offered by the system based on considerations such as how long it has been
since feedback was last provided, whether the student already received some particular
advice, and so on.
7. After this, the program updates the student model, and the entire cycle is repeated,
starting with selecting or generating a new problem.

NON-FUNCTIONAL REQUIREMENTS Intelligent Tutoring System:

• Application is user friendly.
• Application Perform fast manipulation and calculations.
• Application is adaptable.
• Application will be able to work on all types of operating systems.
• Application will be capable to handle multi user activities simultaneously.
• There will be back up system to face any problem in system
• All the options should be learning friendly I.e. member could easily understand what that option will do if he clicked on it.
• Response Time is very awesome.

Some others are:

• Accessibility
• Maintainability
•  Fault Tolerance.
• Security
• Robustnes

Use Case Diagram of Implementation of Intelligent Tutoring System

a use case diagram can summarize the details of your system’s users   and their interactions with the system. Scenarios in which your system or application interacts with organizations, people, or external systems. Goals that your system or application helps those entities achieve

Usage Scenarios Implementation of Intelligent Tutoring System:

A brief user story explaining who is using the system and what they are trying to accomplish. A Scenario is made up of a number of simple, discrete steps that are designated as being performed by either the System or a  User.

ADOPTED METHODOLOGY for Intelligent Tutoring System:

The adopted methodology for this project is vu process model. Vu process model is a combination of water-fall model and spiral model. This combination has many advantages. This model has high risk analysis so avoidance of risk would be achieved. This model is easy to understand and use. Now first we will discuss the Water-fall model.

Work Plan of Intelligent Tutoring System:

Work plan

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