Intelligent System to Monitor Students Mental State

Intelligent System to Monitor Students Mental State

Project / Seminar Material
Reference ID: PS-24915-TM

DEDICATION

This research material titled “Intelligent System to Monitor Students Mental State” is dedicated to God for his enabling grace, and to all computer enthusiasts who contributed to make life a pleasant experience during my research documentation.

ACKNOWLEDGEMENT

I extend my sincere gratitude to all those who contributed to the completion of this project. Special thanks to my Supervisor (Name of your Supervisor), the Head of Department (Name of your HOD), the Lecturers in the department of Computer Science (CS), Book Authors and Profound Scholars of existing or related project material on “Intelligent System to Monitor Students Mental State” for their invaluable guidance, support, and expertise throughout the journey.

I am also grateful to your study area (mention any funding organizations, if applicable) for their financial assistance. This research would not have been possible without the encouragement and assistance of some stakeholders (mention any mentors, teachers, or colleagues). Additionally, I would like to acknowledge the understanding and patience of my family and friends during this endeavor. Your unwavering support has been a constant source of motivation. Thank you all for being part of this meaningful endeavor.

Intelligent System to Monitor Students Mental State

TABLE OF CONTENTS

PRELIMINARY PAGES

CHAPTER ONE

INTRODUCTION

  • 1.1 Introduction
  • 1.2 Background of Study
  • 1.3 Statement of Problem
  • 1.4 Aim and Objectives of the Study
  • 1.5 Significance of Study
  • 1.6 Scope of Study
  • 1.7 Limitations of the Study
  • 1.8 Definition of Terms

CHAPTER TWO

LITERATURE REVIEW

  • 2.1 Introduction
  • 2.2 Conceptual Review
  • 2.3 Mental Health, Well-Being and Academic Performance
  • 2.4 Theoretical Framework
  • 2.4.1 Internet-Based Mental Health Care
  • 2.4.2 Mental Health Care Chat-Bots
  • 2.4.3 Mental Health-Oriented Chatbot for Education
  • 2.5 Integrating the Life-Crafting Intervention with the AI-Enhanced Mental Health Chat-Bot
  • 2.6 Concept of Intelligent System User Registration
  • 2.6.1 Online System User Registration
  • 2.6.2 Usage of Online Registration Forms
  • 2.7 Intelligent System Web Portal
  • 2.7.1 Types of Intelligent System Web Portals
  • 2.8 Database for Intelligent System Web Portals
  • 2.8.1 Merits of Integrating Databases in Web Applications

CHAPTER THREE

SYSTEM ANALYSIS AND DESIGN

  • 3.1 Methodology Adopted
  • 3.1.1 Problem Identification Using SSADM
  • 3.2 Analysis of the Existing System
  • 3.2.1 Dataflow of the Existing System
  • 3.2.2 Disadvantages Of The Existing System
  • 3.2.3 Weakness of the existing System
  • 3.3 Feasibility Study
  • 3.3.1 Economic Feasibility
  • 3.3.2 Technical Feasibility
  • 3.3.3 Operational Feasibility
  • 3.4 Analysis of the Proposed System
  • 3.4.1 Data Flow Diagram of the Proposed System
  • 3.4.2 Advantages of the Proposed System
  • 3.4.3 Justification of the Proposed System
  • 3.5 Functional Requirements
  • 3.5.1 Use Case Diagram Of The Admin / User Privileges
  • 3.6 Data Requirements
  • 3.7 High Level Model of the Proposed System

CHAPTER FOUR

SYSTEM DESIGN AND IMPLEMENTATION

  • 4.1 Objectives of the Design
  • 4.2 Cohesion and Decomposition High level Model
  • 4.3 Control Center / Overall Dataflow Diagram
  • 4.3.1 Proposed System Operation Flowchart
  • 4.4 System Specification and Design
  • 4.4.1 Input and Output Specification
  • 4.4.2 Database Specification and Design
  • 4.4.3 Data Dictionary
  • 4.5 Choice and Justification of Programming Language
  • 4.6 Program Documentation
  • 4.7 Implementation Techniques
  • 4.8 Programming Module Specification
  • 4.8.1 Installation
  • 4.8.2 Security Design Specification
  • 4.8.3 System Architecture
  • 4.9 Computer Hardware Minimum Requirement
  • 4.10 Software Requirement
  • 4.11 Personnel / User Training

CHAPTER FIVE

SUMMARY, CONCLUSION AND RECOMMENDATION

  • 5.1 Introduction
  • 5.2 Summary
  • 5.3 Conclusion
  • 5.4 Recommendation

REFERENCES

APPENDIX A - “SOURCE CODE”

APPENDIX B - “OBJECT PROGRAM”

ABSTRACT

Student’s mental health is related to the decrease of students’ academic performance. Mental health, although not a new concern, has become increasingly acceptable to discuss in recent years. A growing body of research about college students’ mental health concerns underlines the need for educators to consider how mental health might affect students and what courses of action are available. The aim of the study is to design and implement a Intelligent System to Monitor Students Mental State. In achieving this aim, the following specific objectives were laid out as follows to develop an application software that will allow students interact by asking questions and explain instructional material to oneself in terms of the underlying domain knowledge.

The motivation that led to the implementation of the proposed system is that the college students with mental health problems are twice as likely to drop out and depression and suicidal thoughts relate to a lower GPA.

The methodology adopted in this study is the structured system analysis and design methodology (SSADM) which is a technical approach for analyzing and designing an application or system by applying object throughout the software development process. The programming language used is HTML, CSS, JAVASCRIPT, PHP, SQL and JQUERY. The reason why web programming languages was used is because, it is platform independent and it is a web based application. This research work will improve the standard of learning for student and make learning easier and more interesting to student. The expected result is an Intelligent System to Monitor Students Mental State that will provide possible answers to the questions from students and test the students’ mental state by analyzing their performance.

Intelligent System to Monitor Students Mental State

CHAPTER ONE

1.1 Introduction

Mental health and well-being are related and contribute to the decrease of students’ academic performance (in the current study defined as student retention, grade point average and obtained credits Bruffaerts et al., 2018). Intelligent Tutoring Systems (ITS) is the interdisciplinary field that investigates how to devise educational systems that provide instruction tailored to the needs of individual learners, as many good teachers do. Mental health, although not a new concern, has become increasingly acceptable to discuss in recent years. A growing body of research about college students’ mental health concerns underlines the need for educators to consider how mental health might affect students and what courses of action are available. This is imperative given how mental illness may hinder student success (Breslau, Lane, Sampson, & Kessler, 2008; Cranford, Eisenberg, & Serras, 2009; Elion, Wang, Slaney, & French, 2012; Keyes, Eisenberg, Perry, Dube, Kroenke, & Dhingra, 2012; Thompson, Connely, Thomas-Jones, & Eggert, 2013).

As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Limitations of the Study and Definition of technical terms.

1.2 Background of Study

Since the early 1970s, the field of Intelligent Tutoring Systems (also known as Artificial Intelligence in Education) has investigated combining research in Artificial Intelligence, Cognitive Science and Education to devise intelligent agents that can act as tutors in computer-aided-instruction (CAI).

The Overall Structure of the Mental Health Intelligent Evaluation System In order to enable people to have an accurate understanding of their own mental health and at the same time to promote the scientific and informatization of mental health guidance, a mental health intelligent evaluation system based on the decision tree algorithm is constructed, and scientific mental health evaluation tools are used to comprehensively and objectively reflect the user’s mental health level (Wang et al., 2020).

Traditional CAI systems support learning by encoding sets of exercises and the associated solutions, and by providing predefined remediation actions when the students’ answers to do not match the encoded solutions. This form of CAI can be very useful in supporting well-defined drill-and practice activities. However, it is difficult to scale to more complex pedagogical activities, because the system designer needs to define all relevant problem components, all solutions (correct or incorrect) that the system needs to recognize, and all possible relevant pedagogical actions that the tutor may need to take.

1.3 Statement of Problem

Investigation revealed the college students with mental health problems are twice as likely to drop out (Kessler et al., 1995; Hartley, 2010), and depression and suicidal thoughts relate to a lower GPA (Mortier et al., 2015; De Luca et al., 2016). Mental health and academic performance are thus interrelated. However, others might require more follow-up and interaction, or might need coaching on mental health problems that interfere with their academic performance. Coaches and psychologists could facilitate personalized follow-up and interaction, but it would be time-consuming and costly.

Most higher education institutions do not have the capacity to offer this kind of support. Therefore, there is a need for other scalable solutions that offer a personalized and interactive program and contribute to early recognition of problems with academic performance or well- being, in order to prevent more severe problems.

1.4 Aim and Objectives of the Study

The aim of the study is to design and implement a intelligent system to monitor students mental state. In achieving this aim, the following specific objectives were laid out as follows to develop an application software that will:

  1. Allow students interact by asking questions.
  2. Provide possible answers to the questions from students
  3. Test the students’ mental state by analyzing their performance.
  4. Explain instructional material to oneself in terms of the underlying domain knowledge (self-explanation)
…

CHAPTER TWO

2.0 Literature Review

2.1 Introduction

This chapter focuses on the review of related literature. A literature review includes the current knowledge as well as theoretical and methodological contributions to a particular topic. It documents the state of the art with respect to the topic you are writing. It surveys the literature in the topic selected. In this research work the literature review includes the …

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