You will develop a word document to include: Your research question in the form of a quantitative question -? This was m
You will develop a word document to include:
- Your research question in the form of a quantitative question -
This was my research question ( security of the personal information of health care system users – how to protect cyber threats to important personal health care information using AI.
2. Use any one of the instruments given in the sample attached document i.e, either a regular survey questionnaire or closed-ended survey or archival data that could be used to answer the quantitative version of your research question.
Special note: for those using archival data, you will describe the process of data retrieval for your archival data. See examples to help.
3. A one-paragraph description/justification of how your chosen instrument/protocol is the best choice for answering the quantitative version of your research question.
See rubric for how the paper will be graded.
Rubric for Data Collection Instrument
Emerging |
Approaches Expectations |
Meets Expectations |
Exceeds Expectations |
|
Instrument |
70% |
80% Most lines of inquiry are necessary but some do not contribute to the analysis of the research topic Many lines of inquiry are worded unclearly and ambiguously Most rating scales are not equidistantly distributed and are unclear Instrument design is difficult for users to follow and complete |
90% Most lines of inquiry are necessary and contribute to the analysis of the research topic Almost all lines of inquiry are worded clearly and unambiguously Most rating scales are equidistantly distributed and clearly stated Instrument design is neat but sometimes difficult for users to follow and complete |
100% All lines of inquiry are necessary and contribute to the analysis of the research topic All lines of inquiry are worded clearly and unambiguously All rating scales are equidistantly distributed and clearly stated Instrument design is neat and easy for users to follow and complete |
,
35 years
5+ years
I am _______. *Ma k only one oval. Male
Female
O her:
Instru tional Coa h Impa t Survey
1. I se ve as inst uctional coach at the ________ level. *Ma k only one oval.
Elemen ary
Middle
High
2. I cu ently have ________ yea s of expe ience in education. *Ma k only one oval.
05 years
610 years
1120 years
2130 years
30+ years
3. I cu ently have ________ yea s of expe ience as inst uctional coach. *Ma k only one oval.
02 years
4.
5. I p ovide p e- and post-confe ences within the coaching cycle fo my new and at- isk teache s in my building. * Ma k only one oval.
Strong y Disagree Strong y Agree
6. I p ovide monthly new teache meetings with agenda/schedule/sign-in sheet. * Ma k only one oval.
Strong y Disagree Strong y Agree
Survey
7. I p ovide examples of feedback to teache s as follow-ups to class oom obse vation. * Ma k only one oval.
Strong y Disagree Strong y Agree
8. I have evidence of modeling o co-teaching with teache s in my building. * Ma k only one oval.
Strong y Disagree Strong y Agree
9. I have documentation aligning my wo k with new teache s specific to thei needs. * Ma k only one oval.
Strong y Disagree Strong y Agree
10. I have evidence of teache equested assistance with follow up. * Ma k only one oval.
Strong y Disagree Strong y Agree
11. I have evidence of administ ation equested assistance with follow up. * Ma k only one oval.
Strong y Disagree Strong y Agree
12. I have evidence of student inte vention plans fo the most at- isk students in ou building. * Ma k only one oval.
Strong y Disagree Strong y Agree
13. I have evidence o data team meeting agendas and schedules fo students. * Ma k only one oval.
Strong y Disagree Strong y Agree
14. I have sample data of a student in my building making academic p og ess and sample data of a student in my building not making academic p og ess. * Ma k only one oval.
Strong y Disagree Strong y Agree
15. I have fidelity monito ing documentation fo students I conducted this school yea . * Ma k only one oval.
Strong y Disagree Strong y Agree
16. I have weekly inte vention documentation f om my academic inte ventionists. * Ma k only one oval.
Strong y Disagree Strong y Agree
17. I have evidence of wo king with a p io ity p ofessional lea ning community o othe p ofessional lea ning community in my building. * Ma k only one oval.
Strong y Disagree Strong y Agree
18. I have evidence of fidelity monito ing fo standa ds-based inte vention being completed in my building. * Ma k only one oval.
Strong y Disagree Strong y Agree
19. I have evidence of assistance given to teache (s) fo data analysis of Tie I data. * Ma k only one oval.
Strong y Disagree Strong y Agree
20. I have documentation of esou ces sha ed with staff membe s. * Ma k only one oval.
Strong y Disagree Strong y Agree
21. I have documentation of school imp ovement goals based on TVAAS and achievement data in my building. * Ma k only one oval.
Strong y Disagree Strong y Agree
22. I have evidence of PDs I o ganized du ing the school yea based on specific needs in ou building. * Ma k only one oval.
Strong y Disagree Strong y Agree
23. I have evidence of needs assessments completed by teache s in my building. * Ma k only one oval.
Strong y Disagree Strong y Agree
24. I have evidence of PDs I have attended this school yea based on ou building needs. * Ma k only one oval.
Strong y Disagree Strong y Agree
25. I have evidence of collabo ation with othe inst uctional coaches o dist ict staff du ing this school yea . * Ma k only one oval.
Strong y Disagree Strong y Agree
26. I have evidence of pa ent/family communication this school yea . * Ma k only one oval.
Strong y Disagree Strong y Agree
27. I have evidence of unive sal sc eening schedules, fidelity monito ing schedules, and p og ess monito ing schedules being completed in a timely manne . * Ma k only one oval.
Strong y Disagree Strong y Agree
Researc queston
The rese rch queston used “C n m chine le rning id in preventng cybersecurity t cks in he lthc re”,
d t will be collected by the following: surveys will be sent to Chief Inform ton Security Ofcers (CISO)
nd Chief Inform ton Ofcers (CIO) or ny designee for cybersecurity rel ted m ters.
Collecton Instrument
Survey with closed ended questons will be used nd s follows:
Dependent Variable:
Dependent v ri ble will be do “do you currently h ve m chine le rning sofw re (sometmes c lled AI) to
prevent cyber- t cks. (yes or no)
Independent Variables:
Did you experience cyber- t ck? (yes or no)
Wh t type of t ck did you experience? (Select the type of t ck. Multple selectons permited)
Type of t ck:
Brute force p ssword t ck
DDoS/DoS
m lw re
r nsomw re
phishing
suspected insider thre t
other (write in type of t ck)
Did intrusion detecton work? (yes or no)
Wh t ye r did you experience the t ck?
Ye r of t ck (2015 – 2020) (select the ye r, Check box)
Not Contained in t e Study
Size of insttuton will not be ccounted for
Closed-Ended Survey
Do you currently h ve m chine le rning sofw re (sometmes c lled AI) to prevent cybersecurity t cks?
Yes
No
Did you experience cyber- t ck
Yes
No
Wh t type of t ck did you experience? (Select the type of t ck. Multple selectons permited)
Brute force p ssword t ck
DDoS/DoS
M lw re
R nsomw re
Phishing
Suspected insider thre t
Other (write in type of t ck)
Did intrusion detecton work? Yes
No
Wh t ye r did you experience 2015 the t ck?
2016
2017
2018
2019
2020
1
Researc Question
The su vey espondents fo this esea ch was to unde stand whethe health ca e secu ity
is mo e impo tant as a conce n o to focus on the p oblem. Fo this data collection, the esea ch
question was to answe How machine lea ning can imp ove healthca e cybe secu ity and what
ML techniques can p otect health ca e data? (Ze ka et al., 2020). The pu pose of this study is to
measu e machine lea ning methods to imp ove healthca e cybe secu ity. Machine lea ning
techniques a e used fo cybe secu ity analysis to identify potential th eats and potential
vulne abilities in futu e systems and inf ast uctu e to p otect business systems and assets of
Healthca e systems. This focus on the p oblem of cybe secu ity in healthca e using cybe
secu ity ating as an indicato to identify cu ent th eats and potential vulne abilities in va ious
(Ze ka et al., 2020).
Data Measure
The secu ity events of health ca e data will be collected f om elect onic health ca e
eco ds EHR to find insights of malicious activity by analysing la ge data set fo malicious
activity. This data is gene ated fo medical diagnosis info mation and p ovides unique
healthca e info mation including diagnosis codes, patient cha acte istics, and medical t eatment
info mation (Ze ka et al., 2020). Fo healthca e secu ity it is impo tant to evaluate the amount
of info mation used to find new th eats and othe b eaches by looking at secu ity events elated
to healthca e. This is possible if thus study unde stand the unde lying secu ity issues of
healthca e and secu ity awa eness of use s of the p oducts, especially ca e of healthca e (Ze ka
et al., 2020).
The dependent measu e is the ate of b eaches in te ms of healthca e data by the
espective technologies. Data set fo Healthca e Health ca e events will be gene ated based on a
su vey of ove 20,000 consume s. The pu pose of this study is to gathe data about elect onic
Archival Data
2
health ca e eco ds ( EHRs) of ove 20,000 consume s within a pe iod of two to th ee yea s.
The sample size is f om ove 50,000 in case of healthca e data and also f om ove 25,000 in
case of medical diagnostics info mation. It will assess the secu ity data by analysing the sou ce
info mation of EHR data.
Howeve , some of the aspects of this esea ch fo data collection a e as following
Patients health data.
Elect onic health eco ds.
Healthca e secu ity ating.
Info mation about cybe isk.
Pe sonal Health ca e info mation PHI.
Telemedicine data.
Social media data.
To collect data fo the study, the pa ticipants will gathe f om p ivate health ca e
companies on a daily basis. Afte the data gathe ing, it is sto ed in a compute located at thei
home add ess. The data is sto ed using the machine vision that is in use and the data is analyzed
in o de to identify specific ML techniques used to achieve mo e secu e health ca e data. At
some stage of the esea ch, the sample of pa ticipants will also be analyzed with ML techniques
to identify what will be the most impo tant health ca e secu ity events fo EHRs and to gathe
additional data. The final stage of this esea ch p oject is to identify ML techniques which will
be used to imp ove health ca e data secu ity and the study of ML techniques elated to ML
techniques elated to ML techniques elated to secu ity issues.
Howeve , the ML techniques used in this esea ch a e following
Reinfo cement Lea ning RL.
Convolutional neu al netwo ks CNNs.
Deep Lea ning DL.
3
Supe vised Lea ning.
Unsupe vised Lea ning.
Semi-supe vised Lea ning.
In health ca e cybe secu ity machine lea ning techbiques a e used to c eate a p ofile of
the health ca e p ovide s, the patients, the docto s and the patients' habits and elationships
(Bouke che, & Coutinho, 2020). Data a e collected f om these individuals and the data a e
analyzed in o de to identify what the health ca e p ovide s do, the health ca e events that they
will engage in, and the types of events that they will be using health ca e secu ity tools fo . At
some stage of the esea ch, the health ca e is analyzed with ML techniques to identify what the
health ca e p ovide s use in o de to p otect health ca e se vices, and to gathe additional data
(Bouke che, & Coutinho, 2020).
4
References
Bouke che, A., & Coutinho, R. W. (2020). Design Guidelines fo Machine Lea ning-based
Cybe secu ity in Inte net of Things. IEEE Netwo k.
Ze ka, F., Ba akat, S., Walsh, S., Bogowicz, M., Leijenaa , R. T., Jochems, A., … & Lambin, P.
(2020). Systematic eview of p ivacy-p ese ving dist ibuted machine lea ning f om
fede ated databases in health ca e. JCO clinical cance info matics, 4, 184-200.
Researc Queston
The in luence o educators and universities on irst – time, reshman students with low
GPA and ACT scores is more prevalent than ever. Teaching students to be success ul in college
courses, speci ically those with low standardized test scores is essential. One would create a mock
dissertation on this topic, by studying proactive, motivational study skills to students who enter
college with lower academic entrances. The research question is “What is the bene it o enrolling
students who lower than average composite standardized test scores into study and li e skills
courses?”. The purpose o this study will be to examine the e ectiveness o teaching a particular
cohort using T-test and linear regressions to determine the impact on those who receive the service
and those who do not.
Data Mea ure
The success o these courses will be based on grade point average, degree completion, and
time o degree completion. This data is housed in many universities registrar o ice; however, it
can also be ound at Kentucky Council on Postsecondary Education. These organizations collect
all students who have been enrolled in a determined course in Kentucky, their standardized test
scores, demographic characteristics, high school test scores and more. Those who obtained a
degree will be ound rom the University and the year that they began at the university to the year
they completed a degree. Grade point average will be available through individual universities that
the student attended. The in ormation regarding the course, those enrolled, the rate that continued
each year, and more will be available through the Kentucky Council on Postsecondary Education.
Attainment o Associates degrees (typically at a community, two-year university) versus a
Bachelor’s degree, can be ound rom the Kentucky Council on Postsecondary Education.
Archival Data
1 DATA CO ECTION
Researc Question and Purpose
The research question for this study is: “Does higher educational leadership have an impact
on student persistence from first-year to second-year in a public four-year institution?”
This study will be looking at a public four-year institution in the Midwest that is accredited by the
regional accrediting agency Higher earning Commission (H C). The institution has undergone a
complete change of leadership four years ago. With this change, we will be evaluating if there was
an impact on first-year to second-year student retention.
Collection of Arc ival Data
Each year, the university is required to disseminate a climate survey as a part of the
regional accreditation requirements. The climate survey is solely focused on the leadership of the
institution and the support they provide. The survey is a ikert scale, the university archives the
survey results for accreditation purposes and for assessing trends. These past and current results
will be gathered and utilized from the period before and after the leadership change. The survey
results are housed in the Office of Institutional Effectiveness and Assessment and are readily
accessible with a request submission. The study will analyze the survey results for four years prior
to the leadership change and the results for the four years since the change.
Additionally, the Office of Institutional Effectiveness and Assessment will be able to
provide first-year to second-year retention rates for the corresponding years. With both sets of data,
the study will evaluate if there is a correlation using a Chi-Square test. Furthermore, enrollment
and retention information for the institution can be accessed from Integrated Postsecondary
Education Data System (IPEDS) in order to gather a complete picture of enrollment and retention
trends during the eight-year period the study will be examining.
Archival Data
2 Running Head: 3.1 Week 3 Discussion Forum
Research Question:
What is the Influence of Corporate Structure and Vision Statements on the Organizations
Financial Success in thePeriod of January 2019 Through January 2021?
In looking at the topic of the influence of visionary leadership on change management and
implementation, the period immediately preceding and through the current peak of Covid-19 is a
time of unprecedented change. This period also encompasses a highly contested political election
for the president that exacerbates the requirements for change management and implementation for
an organization to remain successful. Organizational structure has a significant impact on how
information moves within a company and the speed at which it can be assimilated and reacted
upon (Krishnan, 2018). The leader is primarily responsible for implementing the corporate
structure and articulating and communicating its vision statement. Theprevalence of an articulated
and well-communicated vision statement within various organizational structures can be correlated
to financial performance metrics such as free cash flows (FCF) and the weighted average cost of
capital (WACC) to form statistical correlations. This will be contrasted with the same
organizational structure without a well-articulated and accessible vision statement with the
expected outcome that the same financial metrics will suffer. It is also expected that more
decentralized structures will enhance financial performance during periods of significant change.
A combination of survey and archival data will beutilized. The survey will be emailed to a
random selection of HRdepartments of 217 of the Fortune top 500 companies for distribution to
front line and middle managers (Krejcie, 1970). Archival data frompublicly available financial
statements will be used to determine FCF and WACC.
Survey
3 Running Head: 3.1 Week 3 Discussion Forum
Data Measure
A survey instrument will capture the independent variables of demographic information,
corporate structure, and vision data.
Demographic Information
1. Gender (check one): ________Female _________Male
2. Geographic Location of theCompany (Check one):
_________Northeast _________Southeast
_________Northwest _________Southwest
_________Midwest
3. What industry do you work in? _______________________________________
4. Approximately how many people are employed by your organization? ______________
CorporateStructure (Bolea & Atwater 2016).
1. How would you defineyour corporate structure?
A. Functional: Centralized, people are organized based on similar job skills. Tasks are
defined and structured.
B. Divisional/Organic: Organized by business function (region, unit, product).
Decentralized, with a focus on a specific part or region of the business, but typically
one responsible supervisor.
4 Running Head: 3.1 Week 3 Discussion Forum
C. Matrix: A combination of functional and divisional. Necessary when there rapidly
changing business environments. Combines structured functions with function-based
work teams with dual or multiple departmental supervisors.
Corporate vision will be measured on aLikert scale utilizing the following closed-ended
questions utilized in previous studies, pending approval from the authors (Carsten, 2006).
Corporate Vision
1 = Strongly Disagree, 2 = Disagree, 3 =Neither AgreeNorDisagree, 4 =Agree, 5 =Strongly
Agree.
1. I am aware of my company’s vision 1 2 3 4 5
2. I would feel comfortable explaining my 1 2 3 4 5
company’s vision to a new co-worker.
3. Measures have been taken to make sure 1 2 3 4 5
I understand the vision.
4. There is a commonality of purpose in my 1 2 3 4 5
organization.
5. There is total agreement on our organizational 1 2 3 4 5
vision across all levels, functions, and divisions.
6. The vision is aligned with my company’s 1 2 3 4
overreaching goals.
5
5 Running Head: 3.1 Week 3 Discussion Forum
7. The vision reinforces my company’s 1 2 3 4 5
guiding purpose.
8. The vision is aligned with my company’s 1 2 3 4 5
core philosophy.
9. Attempts to make things better atmy company 1 2 3 4 5
will not produce good results.
10. Plans for future improvement are likely to 1 2 3 4 5
change things for the better.
11. Suggestions on how to solve problems 1 2 3 4 5
are likely to produce real change.
12. Employees were involved in creating our 1 2 3 4 5
company’s vision.
13. Top management asked employees to 1 2 3 4 5
participate in the visioning process.
14. The vison was produced entirely by 1 2 3 4 5
top management.
15. Employees were asked to provide input on the 1 2 3 4 5
content of the vision statement.
Thinking about yourdepartment or work group, please indicate whether you
agree with the following statements using the scale from 1 (strongly disagree) to 5
(strongly agree).
6 Running Head: 3.1 Week 3 Discussion Forum
16. The vision helps to guide the goals or 1 2 3 4 5
Objectives of my department/work group.
17. The vision has an influence on the decisions 1 2 3 4 5
that are made by my department/work group.
18. My department/work group is not influenced 1 2 3 4 5
by the vision.
19. My department/work group plays an essential 1 2 3 4 5
role in achieving the vision.
Now, Thinking about your specific job, please indicate thedegree to which you
agree with each statement by circling a number between 1(strongly disagree) and 5
(strongly agree).
20. My work directly contributes to carrying out 1 2 3 4 5
the vision of my organization.
21. The vision helps guide my work activities. 1 2 3 4 5
22. I don’t understand how thevision impacts 1 2 3 4 5
my particular job.
23. The vision helps me understand thepurpose 1 2 3 4 5
of my work.
24. Generally speaking, I amvery satisfied 1 2 3 4 5
with my job.
7 Running Head: 3.1 Week 3 Discussion Forum
25. I am interested in my work. 1 2 3 4 5
Corporate financial data will be obtained from archival data found on the 10-Q (quarterly)
reports filed with theSecurities Exchange Commission (SEC) and publicly available on their
website (www.sec.gov). Corporate value, the dependent variable, can bedetermined as follows
(Brigham & Ehrhardt, 2020):
Value = FCF1/(1+WACC) 1 + FCF2/(1+WACC)
2 + FCF3/(1+WACC) 3 + …
FCF =EBIT(1- Tax Rate) – (Present year Operating Capital – Previous year Operating Capital)
Corporate earnings before income taxes (EBIT) and tax rate will be obtained on the SEC website
in the condensed consolidated statement of income. Operating capital will be obtained from the
condensed consolidated balance sheet as the sum of net property and inventory.
After exploring the difficulty in obtaining the WACCfrompublic financial records, and its
anticipated limited impact in the low interest rate environment during theperiod of interest (2019-
2020), corporate value will be approximated as the sum of the future cash flows (FCF’s).
Value ≈ FCF1 + FCF2 + FCF3 + …
8 Running Head: 3.1 Week 3 Discussion Forum
References
Bolea, A., &Atwater, L. E. (2016). Applied Leadership Development: Nine Elements of
Leadership Mastery. New York: Routledge, Taylor & Francis Group.
Brigham, E. F., & Ehrhardt, M. C. (2020). Corporate finance: a focused approach. (7th ed.).
Boston, MA:Cengage.
Carsten, M. K. (2006). Vision in focus: Investigating follower processes that mediate vision
articulation and organizational outcomes (Order No. 3233754). Available from
ABI/INFORM Global. (305357922). Retrieved from
https://search.proquest.com/dissertations-theses/vision-focus-investigating-follower-
processes/docview/305357922/se-2?accountid=10378
Creswell, J. W., &Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed
methods approaches. Thousand Oaks, CA: SAGE Publications.
Krejcie, R. V. &Morgan, D. W. (1970). Determining sample size for research activities.
Educational and Psychological Measurements, 30, 607-610.
Krishnan, R. R. (2018). Organizational change readiness: Effects of organizational structure and
leadership communication in organizational change (Order No. 10791024). Available from
ProQuestDissertations &Theses Global. (205
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