Digital Identity Verification + Machine Learning + CyberSecurity

Summary
To come-up with a Ph.D Research Dissertation Proposal
Specialization: Ph.D in Information Technology
Concentration: Digital Identity Verification + Machine Learning + CyberSecurity
Type: Quantitative Study only – UTAUT-3/meta-UTAUT model – Population (IT/Cyber security
managers in Organizations) – Survey Instrument – Research Design (refer to last page, preferably
simple from first three of them)
Font: Times New Roman, 10 pt size, 0.5-inch margins, single spaced
Requirements
1) Title: (1-2 lines)
– Title Length, Word count should increase citation count, h-index and the like.
2) Proposed Topic
Briefly discuss a proposed topic in your discipline. For the Proposed Topic, please present a
succinct description of your dissertation research focus. Be as specific as possible and cite
the current scholarship that has noted the research focus as an area of needed inquiry.
The topic should be connected to BOTH “Digital Identity Verification + Machine/Deep
Learning + CyberSecurity” with references used in the past 2 years only.
The topic should be of current research with quality of foundation from Journals in
IEEE/ACM/Published PhD dissertations (ProQuest etc.,) and years 2021 and 2022 only.
3) Background of the problem
Why is this important?
One paragraph – must include One high quality scholarly reference (IEEE/ACM/Dissertation)
4) Problem Statement
What problem are you trying to solve? It should be of national importance, if possible.
1-2 paragraphs, Three high quality scholarly references
5) Purpose of the proposed study – must be specific and clear.
Provide information about the proposed research activities.
1-2 paragraphs, NO references
6) Significance of the Study
What contribution will the dissertation make to the literature?
1-2 paragraphs, 3-4 references
7) Research Questions (atleast three primary RQ)
What do you do in this section?
The research questions are where you articulate exactly what your study is attempting to
measure. Do NOT submit descriptive questions and AVOID shallow questions that do not
fully explain your dependent variable. All questions should have a unified focus based on
the problem statement.
Primary Research Question ONE
– Research Sub-Questions (atleast 3-4) and Hypothesis (Null, Alternate) statements
Primary Research Question TWO
– Research Sub-Questions (atleast 3-4) and Hypothesis (Null, Alternate) statements
Primary Research Question THREE
– Research Sub-Questions (atleast 3-4) and Hypothesis (Null, Alternate) statements
Grouping of dependent variables?
Conceptual framework of the study.
A schematic presentation and simulation of the relationship among variables. A
diagrammatic representation clearly showing Independent Variables and Dependent Variables
and relationships.
Variable Type Variable Category Variable Examined
Independent
Dependent
Construct Theoretical or nominal definitions
Construct Perspectives/approaches towards the construct
Construct Validity
Construct Reliability
8) Theoretical Framework/Background
What theories covered in the program are associated with your topic? Follow with a
description of how and why the theory or theories are best to use as the study’s theoretical
foundation.
4-5 paragraphs (1.5 – 2 pages)
9) Research Objectives (1 paragraph)
10) Scope, Assumption and Hypothesis (1 paragraph each)
11) What methodology are you planning to use?
Quantitative Model
Nature of the study
Theoretical Foundation of the study (Most Important is Theoretical Framework)
Theoretical Model of Study
Consider (but do NOT directly answer) the following questions when you write
your theoretical framework:
Is the theoretical foundation strong?
Are the theoretical sources apparent?
Are they appropriate for the topic?
Do they need further explanation?
Research Paradigm
Alternative Paradigm – Optional
Research Design
Please see the image at end of this document
12) Study Population
What is the population you would like to address? Where will you select your sample from?
Describe the characteristics of the study population, including the anticipated number of
subjects, age range, gender, ethnicity, and health status. Specify any inclusion and exclusion
criteria.
Feasibility (of access to population). In other words, Who will be your participants and how
will you reach them? Attach the recruitment materials to the application.
13) Subject Recruitment
What do you do with this section?
Describe the process of identifying and recruiting subjects for the research activities. Attach a
copy of any recruitment material, such as flyers, advertisements, cover letters, etc.).
Interaction with Research Participants: Will the researcher be collecting data by directly
interacting with the participants (electronic, paper, or in person)?
Recruitment Questionnaire (Survey?)
Informed Consent Questionnaire template
14) Research procedures, consent
What do you do with this section?
Describe the procedures that will be used. How will data be collected? Pilot study?
15) Data Collection Instrument
What do you do with this section?
Specify the data collection process that will be used and the data that will be collected from
subjects. If a survey is sent- who sends it. If data are provided who sends it? If interviewswhere and when? This must be clear enough that someone else could follow your steps.
For electronic surveys or questionnaires to be implemented, the live URL to the instrument
must be provided and included in the recruitment notice.
Justification for using that Instrument
16) Data Analysis Plan
How will you analyze your data? For example, how will you measure your independent and
dependent variables? What survey items measure the construct and what statistical analysis
(if applicable) will you use?
Sampling Procedures
Statistical Tests
17) Describe the connection of the topic to the program goals and courses.
How is your topic connected to specific goals in your program?
The program is a PhD in Information Technology concentration. The courses taken are
Information Governance, Data Science and Big Data, Emerging Threats and Counter
Measures, Enterprise Risk Management, IT in Strategic Planning and IT in Global Economy.
18) Alignment (Topic/Problem/Theoretical framework/Model/Research
Design/Instrument/Statistical Tests)
Map your instrument questions to theory or to other studies that support the use of the
question.
Survey item # or interview question Theory/article citation
System Theoretical Approach to Cyber Security Risk Analysis,
Variance and Process Theories for literature Review
Research Summary:
A brief write-up of research summary
Research Question Sources of data to
answer question
Analysis What “conclusion”
do you hope to make?
RQ1
RQ2
RQ3
19) References
– As appropriate but only from high quality Journals in IEEE/ACM/PhD dissertations
– Published works from the years 2021 and 2022 only.
An Example from a totally different education leadership is shown below – Quantitative
Background
The purpose of this quantitative comparative research is to investigate if there is a
statistically significant difference in the student success between online and traditional course
offerings within the applied science programs at a N.C. community college. In addition, to what
extent do differences exist in student success when measured by course grades, student success
rates, and persistence. For this study, the two course delivery methodologies of the community
college to be investigated are online course delivery and traditional in-seat delivery. Online
course delivery refers to courses offered without a physical meeting time or location in a
classroom setting. In contrast, traditional courses meet in some capacity in a physical classroom
or lab at least once per week. As a measurement of success, research consists of existing student
grades, success rates, and persistence data for each course. The student success rate calculation
compares positive grades of C or higher to negatively impacted lower grades such as D, F, and
withdrawals. In addition, individual course grades, student persistence to the following term are
factored when comparing overall student success with online versus traditional course offerings.
The researcher will use two statistical tests, independent-samples t-test and chi-square of
associations, to examine the differences of the student success measures
Research Questions
1. Is there a significant correlation between students living in poverty and student
achievement in reading and vocabulary development according to the Kentucky’s K-Prep
assessment for grades three, four, and five?
Note: In a quantitative study, you are seeking to measure an independent variable (students living
in poverty) against a dependent variable (student achievement) for a fixed population (grades
three, four, and five).
Study Population
Study population will be inclusive of all Associate of Applied Science degree and
diploma program students, excluding Associate in Science and Associate in Arts transfer
program students. Applied Science degree and diploma students from the Schools of Allied
Health, Business & Service, along with STEM & Trades will be included in this research.
Anticipated number of applied science subjects within the five-year data set should be more than
2500 total students. Further institutional demographic information regarding this population is
included below:
Male 43% Female 57%
69% of students are White while 11.6% of students are Black or African American
Subject Recruitment
An email will be sent to the school district superintendents from the target elementary
schools explaining the purpose of the research being conducted for this study and to gain
permission to conduct research utilizing a Likert survey from PBIS.org administered to the
elementary school teachers in their district via survey monkey. Upon obtaining written,
district-level permission to proceed, teachers from the aforementioned elementary schools will
then be contacted by email to explain the research methodology, their anonymity in the study,
and request their participation and consent in the cross-sectional survey.
Research Procedures
Data Collection and Data Analysis
RQ1 Procedure:
The independent variable for RQ1 is the grade level of each teacher for the 2021-2022
school year which will be answered in question one of the demographic portion of the survey.
The dependent variable for RQ1 is the survey data collected from the School Climate Survey
questions from the Office of Special Education Policy (OSEP) distributed through Survey
Monkey as a four-point Likert scale (1= Strongly Disagree, 4 = Strongly Agree). The statistical
test used to measure RQ1 is an Analysis of Variance (ANOVA) test to determine if a statistical
difference between the independent variable and the dependent variable exists.
RQ2 Procedure:
The independent variable for RQ2 is the years of experience of each teacher which will
be answered in question two of the demographic portion of the survey. The independent variable
for RQ2 is the grade level of each teacher for the 2021-2022 school year. The dependent variable
for RQ2 is the survey data collected from the School Climate Survey from the Office of Special
Education Policy (OSEP) distributed through Survey Monkey as a four-point Likert scale (1=
Strongly Disagree, 4 = Strongly Agree). The statistical test used to measure RQ2 is an Analysis
of Variance (ANOVA) test to determine if a statistical difference between the independent
variable and the dependent variable exists.
RQ3 Procedure:
The independent variable for RQ3 is the number of years PBIS has been implemented in
the teacher’s current school. The independent variable for RQ3 is the grade level of each teacher
for the 2021-2022 school year. The dependent variable for RQ3 is the survey data collected from
the School Climate Survey from the Office of Special Education Policy (OSEP) distributed
through Survey Monkey as a four-point Likert scale (1= Strongly Disagree, 4 = Strongly Agree).
The statistical test used to measure RQ3 is an Analysis of Variance (ANOVA) test to determine if
a statistical difference between the independent variable and the dependent variable exists.
Link to survey SurveyMonkey.com
Image for Quantitative Research Design Selection