Design And Implementation Of Intelligent Tutoring System

1.0 Introduction

1.1 Background of the Study

Intelligent tutoring systems (ITSs) are computer programs that are designed to incorporate techniques from the AI community in order to provide tutors which know what they teach, who they teach and how to teach it. AI attempts to produce in a computer behaviour which, if performed by a human, would be described as ‘intelligent’: ITSs may similarly be thought of as attempts to produce in a computer behaviour which, if performed by a human, would be described as ‘goad teaching’ (Murray, 2019). The design and development of such tutors lie at the intersection of computer science, cognitive psychology and educational research; this intersecting area is normally referred to as cognitive science. For historical reasons, much of the research in the domain of educational software involving AI has been conducted in the name of ‘ICAI’, an acronym for ‘Intelligent Computer- Aided Instruction’. This phrase, in turn, evolved out of the name ‘Computer-Aided Instruction’ (CAI) often referring to the use of computers in education. Nevertheless, to all intents and purposes, ITSs and ICAI are synonymous. However, though some researchers still prefer ‘ICAI’. It is now often replaced by the acronym ‘ITS’ (Warendorf, 2017).

The latter, which is also the author’s personal preference, is certainly gaining support, as confirmed by the international conference on Intelligent Tutoring Systems held in Montreal, Canada, as recently as June 2013. This preference is motivated by the claim that, in many ways, the significance of the shift in research methodology goes beyond the adding of an T to CAI (Wenger, 1987). However, some researchers are understandably hesitant to use the term ‘intelligent’, instead opting for labels such as ‘Knowledge-Based Tutoring System’ (KBTS) or ‘Adaptive Tutoring System’ (ATS). Anderson (2018) prefers the label Knowledge Communication Systems. Nevertheless, most researchers appear to be reasonably content with the acronym ITS. This is fine as long as everyone involved with the area understands that the usage of the word ‘intelligent’ is, strictly speaking, a misnomer. Thisdoes not appear to be the case, resulting in some very ambitious goals/claims, particularly in the more theoretical parts of the literature: this also appears to be a valid criticism of the entire AI literature.

The fact that ITS research spans three different disciplines has important implications. It means that there are major differences in research goals, terminology, theoretical frameworks, and emphases amongst ITS researchers. This will become apparent later in this paper. ITS research also requires a mutual understanding of the three disciplines involved, a very stressful demand given the problems of keeping abreast with even a single discipline today. However, some researchers have stood up to the challenge. As a result, a great deal has been learnt about how to design and implement ITSs. A number of impressive ITSs described in chapter two this research paper bear testimony to this fact.

1.2 Statement of the Problem

Conventional learning (classroom learning) is normally fairly structured. It requires learners meeting on a regular basis, at scheduled times on the same days each week. This limits flexibility with work and other activities. Learners generally must be in class to get the learning experience and to keep up with requirements. Unless your instructors record lectures, in-class instruction is not available after the class session is over. Students who struggle to focus may also find classrooms and cohorts distracting to their learning experience.

Furthermore, it is very obvious that students tend to concentrate basically on the departmental compendium, as a result, this gives them little knowledge of what is expected of them, thereby impedes their performance when tested through mid-term assessments or examination. Hence, the problem centers on effective teaching and learning processes for the impacting and the advancement of the students’ theoretical and practical knowledge. This research work is carried out to design and develop an Intelligent Tutoring System (ITS); the proposed system will be aimed at reducing the level of student’s dependency on their teachers.

1.3 Aim and Objectives of the Study

The aim of the study is to design and implement an Intelligent Tutoring System (ITS). To achieve the stated aim, the following specific objectives were laid out:

The tendency to explain instructional material to oneself in terms of the underlying domain knowledge (self-explanation)

To allow students interact by asking questions.

To provide possible answers to the questions from students

Test the students.

Analyze their performance.

1.4 Scope of the Study

The design of an intelligent tutoring system is a very broad field, but this research work focuses on the development of a platform where students of Computer Science can easily access reference materials of the departmental compendium, can read, copy or print these materials. Also students can download or watch videos of lectures uploaded by the instructor. It also makes a provision for the students to assess themselves after each studied course (objective-based).

1.5 Significance of the Study

The significant of these study includes the following:

It makes learning easier and more interesting to student in the sense that one can learn from the comfort of his or her home.

Its improve the knowledge of lecturer strategies ( i.e. how to teach, in what order, typical mistakes and remediation,)

It improves the standard of learning for student.

1.6 Limitation of the Study

Intelligent tutoring systems are expensive both to develop and implement. The research phase paves the way for the development of systems that are commercially viable. However, the research phase is often expensive; it requires the cooperation and input of subject matter experts, the cooperation and support of individuals across both organizations and organizational levels. Another limitation in the development phase is the conceptualization and the development of software within both budget and time constraints. There are also factors that limit the incorporation of intelligent tutors into the real world, including the long timeframe required for development and the high cost of the creation of the system components. A high portion of that cost is a result of content component building. For instance, surveys revealed that encoding an hour of online instruction time took 300 hours of development time for touring content. Similarly, building the Cognitive Tutor took a ratio of development time to instruction time of at least 200:1 hours. The high cost of development often eclipses replicating the efforts for real world application. Intelligent tutoring systems are not, in general, commercially feasible for real-world applications.

1.7 Definition of Terms

Mobile:

With respect to technologies, ‘mobile’ generally means portable and personal, like a mobile phone.

Learning:

This is the act of acquiring new or modifying and reinforcing existing knowledge, behaviour, skills, values, or references and may involve synthesizing different types of information.

Intelligent Tutoring System:

An intelligent tutoring system (ITS) is a computer system that aims to provide immediate and customized instruction or feedback to learners, usually without requiring intervention from a human teacher.

Conventional Learning:

This means having education in the four walls of a school.

Website:

It is information of a particular people, individual, state, country etc, made available to be seen or can download on the net.

Login:

To connect to the scale and make use of available information provided by the designer within some range of specification.