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Design and implementation of an intelligence based system for students performance evaluation

 

Table Of Contents


Chapter ONE

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms

Chapter TWO

2.1 Overview of Intelligence-Based Systems
2.2 Theoretical Frameworks in Student Performance Evaluation
2.3 Previous Studies on Student Performance Evaluation
2.4 Technologies Used in Student Performance Evaluation
2.5 Data Analysis Techniques for Student Performance Evaluation
2.6 Role of Artificial Intelligence in Education
2.7 Impact of Student Performance Evaluation on Academic Institutions
2.8 Challenges in Implementing Intelligence-Based Systems for Student Evaluation
2.9 Best Practices in Student Performance Evaluation Systems
2.10 Future Trends in Student Performance Evaluation

Chapter THREE

3.1 Research Design
3.2 Research Approach
3.3 Data Collection Methods
3.4 Sampling Techniques
3.5 Data Analysis Procedures
3.6 Ethical Considerations
3.7 Validity and Reliability
3.8 Limitations of the Research

Chapter FOUR

4.1 Overview of Findings
4.2 Analysis of Student Performance Data
4.3 Comparison of Different Evaluation Methods
4.4 Impact of Intelligence-Based Systems on Student Evaluation
4.5 Feedback Mechanisms for Student Improvement
4.6 Recommendations for Academic Institutions
4.7 Implementation Strategies for Intelligence-Based Systems
4.8 Future Research Directions

Chapter FIVE

5.1 Summary of Findings
5.2 Conclusion
5.3 Implications of the Study
5.4 Contribution to Knowledge
5.5 Recommendations for Future Research

Project Abstract

Abstract
In the field of education, the assessment of students' performance is a critical aspect that requires continuous improvement and innovation. Traditional methods of evaluation, such as exams and quizzes, have limitations in providing a comprehensive understanding of students' capabilities and progress. Therefore, there is a growing need for more intelligent systems that can offer a more accurate and nuanced evaluation of students' performance. This research project focuses on the design and implementation of an intelligence-based system for students' performance evaluation. The system integrates various advanced technologies, including artificial intelligence, machine learning, and data analytics, to analyze and assess students' academic achievements, skills, and overall progress. The primary objective of this system is to provide a personalized and adaptive evaluation approach that takes into account individual student characteristics, learning styles, and strengths. By leveraging artificial intelligence algorithms, the system can identify patterns and trends in students' performance data, enabling more targeted interventions and support strategies. The system utilizes machine learning models to predict students' future performance based on their past achievements and behaviors. This predictive capability allows educators to proactively address potential challenges and provide timely assistance to students who may be at risk of falling behind. Moreover, the system incorporates data analytics techniques to generate insights from large volumes of student performance data. By analyzing this data, educators can gain a deeper understanding of students' learning patterns, preferences, and areas of improvement. This data-driven approach enables evidence-based decision-making and facilitates the continuous refinement of teaching strategies and curriculum development. Overall, the intelligence-based system for students' performance evaluation aims to enhance the quality and effectiveness of assessment practices in education. By leveraging advanced technologies, such as artificial intelligence and data analytics, the system offers a more comprehensive and insightful evaluation of students' progress, enabling educators to provide targeted support and interventions to maximize student success.

Project Overview

INTRODUCTION

1.0 Introduction

This chapter presents the introduction to an intelligence based system for students performance evaluation. It presents:

  • Introduction
  • Statement of the problem
  • Objectives of the study
  • Scope of the study
  • Significance of the study
  • Organization of the research
  • Definition of terms.

Performance in schools is increasingly judged on the basis of effective learning outcomes. Information is critical to knowing whether the school system is delivering good performance and to providing feedback for improvement in student outcomes. The OECD (Organization for Economic Co-operation and Development) has launched the Review on Evaluation and Assessment Frameworks for Improving School Outcomes to provide analysis and policy advice to countries. Countries use a range of techniques for the evaluation and assessment of students, teachers, schools and education systems. Many countries test samples and/or all students at key points, and sometimes follow students over time. In all countries, there is widespread recognition that evaluation and assessment frameworks are key to building stronger and fairer school systems. Countries also emphasize the importance of seeing evaluation and assessment not as ends in themselves, but instead as important tools for achieving improved student outcomes [1].

1.1 Statement of Problem

The following are the problems that necessitated this research to be conducted.

  1. Absence of an effective computerized performance evaluation system in schools.
  2. The manual method of conducting performance evaluation of students is time consuming and prone to many errors.
  3. Difficulty in obtaining instant reports of past performance evaluation records.

1.2Aim and Objectives of the Study

The aim of the study is to design and Implement an intelligence based system for students’ performance evaluation. The specific objectives are:

  1. To develop a computerized system to replace the manual method of assessing students.
  2. To develop a system that will intelligently determine the performance of students based on different variables such as attendance frequency, class work performance, neatness etc.
  3. To develop a system that will capture performance assessment records to a database.
  4. To develop a system that will aid in the easy retrieval of performance evaluation records

1.3 Scope of the Study

This study covers the Design and Implementation of an intelligence based system for students performance evaluation a case study of state college, Ikot Ekpene, Akwa Ibom state. It is limited to the assessment of the students performance by different variables such as attendance frequency, class work performance, ability to answer questions, general proficiency in study, English language proficiency, socialization ability, neatness/ dressing, obedience level.

1.4 Significance of the Study

The significance of the study are:

  1. It will provide valuable information to readers on how performance evaluation in schools is conducted.
  2. It will provide a system that will aid in the easy computation, storage and reporting of performance evaluation records.
  3. It will save time in the assessment of student’s performance.
  4. It will serve as a useful reference material for other researchers seeking related information.
  • Organization of the Research

This research work is organized into five chapters. Chapter one is concerned with the introduction of the research study and it presents the preliminaries, theoretical background, statement of the problem, aim and objectives of the study, significance of the study, scope of the study, organization of the research and definition of terms.

Chapter two focuses on the literature review, the contributions of other scholars on the subject matter is discussed.

Chapter three is concerned with the system analysis and design. It analyzes the present system to identify the problems and provides information on the advantages and disadvantages of the proposed system. The system design is also presented in this chapter.

Chapter four presents the system implementation and documentation. The choice of programming language, analysis of modules, choice of programming language and system requirements for implementation.

Chapter five focuses on the summary, conclusion and recommendations are provided in this chapter based on the study carried out.

1.6 Definition of terms

Artificial Intelligence: A field of computer science that is concerned with the development of systems that mimic the intelligence of human experts.

Performance: The amount of useful work accomplished to the time and resources used.

Evaluation:  An appraisal or assessment of an individual or thing to determine their level of performance


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