Doctorate in Science (D.Sc)

Program Overview

A Doctorate in Science (D.Sc.) is a prestigious, research-intensive degree designed for professionals and scholars seeking to make groundbreaking contributions to scientific knowledge and innovation. This program focuses on cutting-edge research, interdisciplinary problem-solving, and the application of scientific principles to real-world challenges. Whether in natural sciences, engineering, technology, or applied sciences, a D.Sc. equips candidates with the expertise to lead high-impact research projects, develop innovative solutions, and influence industry advancements.

Why Pursue a Doctorate in Science (D.Sc.) from FLISM?

The Doctorate in Science (D.Sc.) at Florida Institute of Science and Management is designed for professionals, researchers, and innovators who seek to push the boundaries of scientific knowledge and its practical applications. This program is tailored for individuals aiming to make groundbreaking contributions to research, industry, and technological advancements across various scientific disciplines. FLISM provides a multidisciplinary research environment, expert faculty mentorship, and global networking opportunities to help scholars create real-world impact through scientific exploration.

Key Highlights

100% Online Program

Get the flexibility to complete your education along with your work commitments.

24*7 Access

State-of-the-art and advanced Learning Management System for enhanced self-learning

Comprehensive Curriculum

Curriculum developed by Industry Experts and world-class faculty members

Networking Opportunities

Gain global networking opportunity

Program Objectives

Conduct original, high-impact research in natural sciences, engineering, healthcare, and technology.
Develop innovative scientific methodologies to solve complex challenges.
Publish research in leading scientific journals and global conferences.
Utilize data science, artificial intelligence, and emerging technologies in research.
Contribute to advancements in environmental sustainability, healthcare, and business technology.
Engage with renowned scientists, researchers, and industry experts worldwide.
Participate in international research collaborations and industry projects.
Develop leadership skills to influence global scientific advancements.

Curriculum

Module 1: Thesis Management

Research

Scope and Significance
Types of Research
Research Process
Characteristics of Good Research
Identifying Research Problem
Meaning of Sampling Design
Steps in sampling
Criteria for good sample design
Types of Sample Design
Probability and non-probability sampling methods
Meaning of Measurement
Types of scales

Review of Literature

Data Collection
Types of Data
Sources of Data Collection
Methods of Data Collection
Constructing questionnaire
Establishing, reliability and validity
Data processing
Coding, Editing and tabulation of data
Meaning of Report writing
Types of Report
Steps of report writing
Precautions for writing report
Norms for using Tables
Charts and diagram
Appendix: – Index, Bibliography

Module 2: General Research Methodology

Meaning and importance of Research
Types of Research
Selection and formulation of Research Problem
Meaning of Research Design
Need of Research Design
Features of Research Design
Inductive, Deductive and Development of models
Developing a Research Plan
Exploration, Description, Diagnosis, Experimentation
Determining Experimental and Sample Designs
Analysis of Literature Review
Primary and Secondary Sources
Web sources
Critical Literature Review
Hypothesis
Different Types of Hypothesis
Significance
Development of Working Hypothesis
Null hypothesis
Research Methods: Scientific method vs Arbitrary Method
Logical Scientific Methods: Deductive, Inductive, Deductive-Inductive
Pattern of Deductive
Inductive logical process
Different types of inductive logical methods.

Module 3: Quantitative Research Methods

Introduction to Quantitative Research

Part 1:

a. Session Overview
b. RQ Hypothesis Course Context Video
c. What is Quantitative Research?
d. Ethics of Quantitative Research
e. Session Summary

Part 2:

f. Session Overview
g. Introduction to the Scientific Method of Research
h. Comparing Descriptive, Predictive and Prescriptive Research
i. Inductive and Deductive Approaches to Quantitative Research
j. Constructing Models
K. Session Summary

Exploring Quantitative Research Design

Part 1:

a. Session Overview
b. Fundamentals of Research Design
c. Components of a Research Design
d. Characteristics of a Research Design
e. Session Summary

Part 2:

f. Session Overview
g. Research Design for Experimental Research Studies
h. Research Design for Quasi Experimental Studies
i. Research Design for Non-Experimental Research Studies
j. Evaluating Quantitative Research Design
k. Session Summary

Data Collection for Quantitative Research

Part 1:

a. Session Overview
b. Defining Surveys
c. Exploring Survey Methods
d. Session Summary
Part 2:

e. Session Overview
f. The Process of Questionnaire Development
g. Designing a Questionnaire
h. Designing Rating Scales
i. The Art of Asking Questions
j. Session Summary

Part 3:

k. Session Overview
l. Tips to Conduct Effective Surveys
m. Ethics of Using Technology in Surveys
n. Session Summary

Measurement and Sampling

Part 1:

a. Session Overview
b. What is measurement?
c. True Score Theory, Estimating Measurement Errors
d. Evaluating Validity of Measures
e. Evaluating Reliability of Measures
f. Session Summary

Part 2:

g. Session Overview
i. Basic Concepts of Sampling
j. Problems and Blases in Sampling
k. Probability Sampling
l. Non-Probability Sampling
m. Session Summary

Part 3:

n. Session Overview
o. Determining the Sample Size
p. Sampling Distribution and Statistical Inference
q. Demonstrations on Sampling
r. Session Summary

Constructing Statistical Models
Part 1:

a. Session Overview
b. Significance of Comparing Means for Analysis
c. What is ANOVA?
d. Types of ANOVA
e. Calculating and Interpreting One-Way ANOVA
f. Session Summary

Part 2:

g. Session Overview
h. Building a Statistical Model
i. Effect of Moderating and Mediating Variables
j. Demonstration on Mediation and Moderation
k. Session Summary

Enhancing Statistical Models
Part 1:

a. Session Overview
b. What is Factor Analysis?
c. Conducting Factor Analysis
d. Demonstration on R: Factor Analysis
e. Interpreting Factor Scores
f. Session Summary

Part 2:

g. Session Overview
h. What is Factorial ANOVA?
i. Dealing with Interaction Effects in Factorial ANOVA
j. Calculating and Interpreting Factorial ANOVA
k. Session Summary

Multivariate Analyses
Part 1:

a. Session Overview
b. Multivariate regression
c. MANOVA
d. Logistic Regression
e. Structural Equation Modeling
f. Tree Structured Methods
g. Conjoint Analysis
h. Session Summary

Part 2:

i. Session Overview
j. Time Series
k. Cluster Analysis
l. Session Summary

Writing a Quantitative Research Paper
Part 1:

a. Session Overview
b. Introduction to Formatting the Research Project for Quantitative Research
c. Components of a Quantitative Research Paper
d. Writing the Summary, Background and Purpose of Quantitative Research
e. Writing the Literature Review
f. Detailing your Research Design/Methodology
g. Curating your Results, Analysis and Supplementary Findings
h. Outlining your Conclusions and Recommendations
i. Making Appendices
j. Session Summary

Part 2:

k. Session Overview
l. Writing Different Types of Quant Papers
m. Guidelines for Fine-Tuning your Research Presentation
n. Session Summary

Module 4: Qualitative Research Methods

Introduction to Qualitative Research

a .Key Elements of Qualitative Research
b. Writing Qualitative Research Question
c. Qualitative Research: Framework
d. Steps to Write a Qualitative Research Paper
e. Ethics for Qualitative Research and IRB
f. Introduction to Design Strategies
g. Data Collection and Analysis Strategies
h. Introduction to research design
i. Major aspects of research design

Data Collection in Qualitative Research

Sources of Evidence: A Comparative
b. Assessment (Forms-Strengths-Weaknesses)
c. Principles of Data Collection
d. Sampling
e. Reliability and Validity

Interviews and Focus Groups
Introduction to Data Analysis
An Introduction to Data Analysis
b. First Cycle Coding (Description Demo)
c. Second Cycle Coding (Description Demo)
d. Jottings and Analytic Memoing (Description Demo)
e. Assertions and Propositions (Description Demo)
f. Within Case and Cross-Case Analysis (Description Demo)

Data Display and Exploration

Matrix and Networks
b. Timing, formatting
c. Extracting Inferences and Conclusions
d. Exploring Fieldwork in Progress
e. Exploring Variables
f. Exploring Reports in Progress

Data Analysis Process – Next Steps

Describing Participants
b. Describing Variability
c. Describing Action
d. Ordering by time
e. Ordering by process
f. Explaining Interrelationship-Change
g. Explaining Causation
h. Making Predictions

Verifying Conclusions

Tactics to achieve integration among diverse pieces of data
b. Tactics to sharpen understanding by differentiation
c. Tactics of seeing relationships in data abstractly
d. Tactics to assemble a coherent understanding of data
e. Tactics for testing or confirming findings
f. Standards for quality of conclusions

Writing a Report and New Technologies

Other methods in Qualitative Research
b. Audiences and Effects
c. Different aspects / apa
d. An Introduction to Mixed Methods Research

Frequently Asked Questions

What specializations are available under the Doctorate in Science (D.Sc.)?

Doctorate in Science (D.Sc.) offers a range of specializations, including Physics, Chemistry, Biology, Environmental Science, Computer Science, and Medical Sciences, among others.

Is the Doctorate in Science research-focused?

Yes, the D.Sc. is primarily research-based, with students expected to conduct independent research and contribute significantly to advancements in their chosen field.

Can I pursue the Doctorate in Science part-time or online?

Yes, Florida Institute of Science and Management offers flexible study options, including an online learning format for students who wish to balance their professional commitments with their doctoral studies.

What career opportunities are available after completing the D.Sc.?

Graduates of the D.Sc. can pursue careers in academia, scientific research, government agencies, R&D divisions of private companies, and consulting roles across various industries.

Doctorate in Science (D.Sc)