The document provides a literature review for a study on the role of cloud computing in education during the COVID-19 pandemic. It discusses how the pandemic increased demand for cloud services and online learning. The review summarizes previous research on cloud computing adoption in various industries and its benefits. It also describes the mixed-method approach that will be used to understand the impact of cloud technology on student performance through surveys and statistical analysis.

1. BENCHMARK-DATA COLLECTION DESIGN
1
DATA COLLECTION AND INTERPRETATION OF RESULTS
2
Benchmark: Data Collection Design
Joshua Odusola-Stephen
COM-355: Communication Research Methods
Grand Canyon University
September 20, 2021
Data Collection and Interpretation of Results
Part 1
Data Collection
The study will be conducted through the mixed-method research
approach. The methodology will be divided into three sections,

2. namely:
1. Survey development, which will focus on the procedure
responsible for developing the survey questions. For example,
some questions from previous studies may be used to preserve
historical data. Moreover, the survey questions will target
academic performance appraisal, among other attributed critical
in appreciating the scope and details of the problem.
2. Survey application: addresses the approach through which the
survey questions will be distributed to collect enough and
reliable data. Moreover, it will also focus on the target
population for the survey.
3. Data statistical Analysis: the phase will address the proper
processing tools needed to understand the data. Depending on
the number of variables targeted, numerous statistical
techniques may be required. Thus, it will determine if the study
is multivariate or univariate.
The focus of the researchers will be to better understand the
role of cloud computing in the education sector. In addition, the
individuals that will participate in the study are the individuals
most affected by the implementation of cloud technology in
education institutions. Furthermore, the individuals will include
professors, students, and college administrators. The survey will
involve 90 respondents from 3 colleges in the locality, while the
respondents will respond to questions that are going to be asked
in the survey.
The researcher will ask individuals that are the most likely to be
affected by the change to participate in the study. A consent
form will be sent using DocuSign and get signatures. The
selected participants will submit the consent forms and
complete the interview using Zoom. Data will be collected on
Zoom which for a business account provided computer-
generated transcripts. These transcripts will be reviewed and
listened to as well as cleaned up for computer errors such as the
computer transcribing the word label as ladle. Transcripts once
cleaned will be uploaded into MaxQDA for analysis. The
transcripts and data analysis files will be saved in a password-

3. protected file on the computer and a password-protected USB
drive as a backup. They will be saved for 3 years and then
destroyed electronically and physically for the USB drive by
smashing it.
Data Analysis and Interpretation
Data analysis will be conducted using descriptive analysis,
followed by transcription from the tape recorder then the
analysis will be performed based on the interviews. Data
collected will be first manually coded with the themes of the
study. The coded themes will then be analyzed, and
explanations are given. The overall aim of the analysis is to
better understand the role of cloud computing in the education
sector. At the initial starting stage, individual interviews will be
conducted, recorded, and transcribed verbatim. The next step
will involve the researcher repeatedly reading and listening to
the content to get familiarized with it. As such, the researcher
will gain deeper and better familiarization with the contents; he
will also identify the answers to those questions asked as well
as identify the themes.
The data collected will be grouped into three categories, with
the first category being the person from which data was
collected. The second category will be the method used for data
collection, while the third category will be the contents of the
data collected. Through the categorization, it will be possible to
collect evidence that supports that the quantity, and the quality
of the data are enough to answer the research questions.
A thematic analysis will be used to analyze the data collected.
This was chosen because it is a common analysis technique for
qualitative data with a clear set of steps to follow. According to
Nowell et al., (2017), thematic analysis emphasizes the
identification, analysis, and interpretation of patterns of
meaning within qualitative data. The researcher particularly will
use MaxDQA in organizing and visualizing data.
Part 2
Answer the following question by identifying a rating that best
describes your view

4. 0 0 0 0 0 0 0 0 0
0
1 2 3 4 5 6 7 8 9
10
Agree
Disagree
No.
Opinion based questions
1.
Many professors find it convenient to use cloud solutions for
educating
2.
Many students find it convenient to use cloud solutions for
learning
3.
Most administrators find it convenient to use cloud solutions for
running their institution’s duties
4.
The cloud solutions implemented in our institution were enough
for education administration during the pandemic period
5.
The use of Cloud technology is making it easy for learners to
learn
6.
Use of cloud technology in the education sector is challenging
7.
Cloud solutions are in line with current technology
advancements and should be implemented in all learning
institutions

5. 8.
The cloud solutions are expensive and should not be
implemented in all learning institutions
9.
Cloud solutions reduce the quality of education as learners do
not get to physically interact with their educators
10.
Cloud solutions improve the learning experience
Reference
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J.
(2017). Thematic analysis: Striving to meet the trustworthiness
criteria. International journal of qualitative methods, 16(1),
1609406917733847.
Officer Renegade approached the Sheriff regarding the
placement of a GPS device on the automobile of a man
suspected of drug trafficking. The Sheriff told him to hold off
until he had some time to have legal counsel research what was
required. Officer Renegade was so convinced that the suspect
was about to pick up a substantial quantity of cocaine, he did
not wait to hear back from the sheriff. He planted a GPS device
on the suspect’s car and monitored his movements for ten days.
Based on those movements, Officer Renegade determined that
every two days the suspect drove to the same location, taking a
different route each time, but always returning to his residence.
Each trip took about the same amount of time. Officer Renegade
then obtained a search warrant of the suspect’s home based on

6. these monitored
movements and surveillance of the suspect’s home on his return
from these trips. When the warrant was executed, the police
found two pounds of cocaine neatly packaged in one-ounce
plastic bags, scales, and a loose white powder used to cut the
cocaine before packaging. The suspect was charged with
trafficking in cocaine and related charges. The suspect’s
criminal lawyer has filed motions to suppress any evidence
taken from the suspect’s home claiming that the warrantless
placing of the GPS device was a violation of the Fourth
Amendment and therefore the search warrant of his residence
was invalid. The Sheriff wants to know what her position should
be, what the law is, and what your recommendations are for
dealing with this claim. She also wants you to explain your
reasons for your recommendations. Additionally, the suspect’s
civil lawyer has filed a Section 1983 claim against Officer
Renegade, the Sheriff, and the city of Saint Leo. The Sheriff
wants to know what her position should be, what the law is, and
what your recommendations are for dealing with this claim. She
also wants you to state your reasons for your recommendations.
Finally, the Sheriff was so angry, she fired Officer Renegade
for insubordination without a hearing. Officer Renegade was the
subject of many previous internal investigations and the Sheriff
did not want to risk a lawsuit for failure to discipline. Because
she knew that Officer Renegade would try to obtain employment
in the town of Peaceful Valley, the sheriff sent a copy of
Officer Renegade’s personnel file to Peaceful Valley’s sheriff.
Officer Renegade is threatening to sue the Sheriff and the city
for violating his property rights and his liberty rights. The
Sheriff wants to know if Officer Renegade has valid claims and
what her position should be.
LITERATURE REVIEW 2

7. Benchmark -Literature Review
Joshua Odusola-Stephen
COM-355: Communication Research Methods
Grand Canyon University
September 9, 2021
Literature Review
The coronavirus pandemic has had numerous economic,
political, and social impacts. The result has been a surge in
demand for internet connections at various workplaces attempt
to adapt to the new social norms. Though numerous companies
have demonstrated their potential in sustaining economic
activities, the education sector negativel y affected student
academic performance. It is noteworthy that many learning
institutions suspended activities due to the state mandate to
limit the spread of the disease. Thus, numerous hypotheses were
proposed with the limited information available on the social
impact of the disease.
Regardless, to better understand the role of cloud
computing in the education sector, the research will employ a
mixed-method approach. In other words, it will implement both

8. qualitative and quantitative strategies. The purpose is to have a
detailed appreciation of the problem, making it more
straightforward to devise effective solutions. The information
will also include the scope of the problem, thus allowing for
better prioritization. Therefore, to achieve effective data
collection, statistical assessments and surveys will be
employed.
The study will implement a cross-sectional survey involving
assessing data from a population-based on variables critical to
the task. The methodology will be divided into three sections,
namely:
1. Survey development, which will focus on the procedure
responsible for developing the survey questions. For example,
some questions from previous studies may be used to preserve
historical data. Moreover, the survey questions will target
academic performance appraisal, among other attributed critical
in appreciating the scope and details of the problem.
2. Survey application: addresses the approach through which the
survey questions will be distributed to collect enough and
reliable data. Moreover, it will also focus on the target
population for the survey.
3. Data statistical Analysis: the phase will address the proper
processing tools needed to understand the data. Depending on
the number of variables targeted, numerous statistical
techniques may be required. Thus, it will determine if the study
is multivariate or univariate.
Nevertheless, though the primary approach of the study
will provide the needed data for the effective execution of the
research, it will also exploit data from other researchers. Some
data include a 2017 statistical evaluation of the cloud
computing market assessing its overall growth (Alsmadi &
Prybutok, 2018). The data identified that the technology was
slowly assimilated in various industries, with healthcare
portraying the greatest demand. However, Tuli et al. (2020)
state that with the onset of the pandemic, the demand for cloud

9. services rose by over 40%. It has been attributed to the rise in
demand for big data and data analytics which are essential for
organizational or industrial changes through decision-making. It
was mostly exploited by the retail sector, which was among the
few industries with the positive financial outcomes of the
pandemic (Al-Said Ahmad & Andras, 2019). Nevertheless,
supported by the low implementation requirements and high-
cost effectiveness, Stergiou et al. (2018) stated the technology
will continue being sought after in various sectors.
According to (), cloud computing has significantly
evolved in the past decade, and its availability has been able to
meet the demand. With over 30% of companies and institutions
in various industries dependent on cloud computing, the trend is
expected to continue growing, offering opportunities for other
industries (Wang, 2021). It is noteworthy that though the
research will rely on primary data to better understand the
pandemic on students, secondary data will also be implemented.
The objective is to appreciate both primary and secondary data
in developing solutions for students. According to Varghese and
Buyya (2018), cloud computing is a global trend that
significantly changes the business landscape with on-demand
computing services.
Some services offered include application, storage, and
processing power. They are provided over the internet with pay-
as-you-go services. Cloud computing operates by offering
consumers computing and database infrastructure for clients to
rent as they access the storage and applications provided by
cloud services (Qasem et al., 2019). Such services benefit
companies because they avoid initial costs and complexities
associated with owning and maintaining IT infrastructures. In
turn, cloud service providers benefit from economies of scale,
thus offering services at lower prices thus attracting numerous
consumers.
The argument is supported by data from various
researchers such as Qasem et al. (2019), identifying that cloud
computing has numerous applications in all industries. In

10. addition, the argument is founded on the rise in demand for
cloud computing services in various sectors, including public
education. The author states that the technology has been
progressively developing to meet demands in the current IT
environment. However, the pandemic augmented the demand for
cloud services as more people became reliant on the internet for
work due to movement and interaction restrictions (Alashhab et
al., 2021).
Zhang et al. (2019) support the notion by identifying the
healthcare sector, government agencies, manufacturing sector,
and the retail industry as having the greatest demand for cloud
computing services. Though the data does not directly address
public education, the researcher states that the diverse
applicability of cloud computing services can augment
development and performance (Zhang et al., 2019). By
exploiting the available tools, proactive data analysis can allow
for the effective exploitation of available resources. An example
provided is how the agricultural sector can help farmers better
understand their environment by providing data on crop
production and harvest, resulting in the exploitation of IoTs in
increasing yield (van Eyk et al., 2018). In other words, from a
qualitative perspective, the implementation of cloud computing
is essential in the development of the education sector. By
taking advantage of the communication channels provided by
technology, students will access information and resources
essential for their performance.
References
Alashhab, Z. R., Anbar, M., Singh, M. M., Leau, Y., Al-Sai, Z.
A., & Abu Alhayja’a, S. (2021). Impact of coronavirus
pandemic crisis on technologies and cloud computing
applications. Journal of Electronic Science and
Technology, 19(1), 100059. doi: 10.1016/j.jnlest.2020.100059
Al-Said Ahmad, A., & Andras, P. (2019). Scalability analysis
comparisons of cloud-based software services. Journal of Cloud

11. Computing: Advances, Systems and Applications, 8(1), 1-17.
doi:10.1186/s13677-019-0134-y
Alsmadi, D., & Prybutok, V. (2018). Sharing and storage
behavior via cloud computing: Security and privacy in research
and practice. Computers in Human Behavior, 85, 218-226. doi:
10.1016/j.chb.2018.04.003
Qasem, Y. A. M., Abdullah, R., Jusoh, Y. Y., Atan, R., &
Asadi, S. (2019). Cloud computing adoption in higher education
institutions: A systematic review. IEEE Access, 7, 63722-
63744. doi:10.1109/ACCESS.2019.2916234
Stergiou, C., Psannis, K. E., Gupta, B. B., & Ishibashi, Y.
(2018). Security, privacy & efficiency of sustainable cloud
computing for big data & IoT. Sustainable Computing
Informatics and Systems, 19, 174-184. doi:
10.1016/j.suscom.2018.06.003
Tuli, S., Tuli, S., Tuli, R., & Gill, S. S. (2020). Predicting the
growth and trend of COVID-19 pandemic using machine
learning and cloud computing. Internet of Things, 11, 100222.
doi: 10.1016/j.iot.2020.100222
Van Eyk, E., Toader, L., Talluri, S., Versluis, L., Uta, A., &
Iosup, A. (2018). Serverless is more: From PaaS to present
cloud computing. doi:10.1109/MIC.2018.053681358
Varghese, B., & Buyya, R. (2018). Next generation cloud
computing: new trends and research directions. Future
Generation Computer Systems, 79, 849-861. doi:
10.1016/j.future.2017.09.020
Wang, X. (Jun 28, 2021). Introducing cloud data technology
into economic statistics. Paper presented at the 865-869.
doi:10.1109/IWCMC51323.2021.9498770 Retrieved
from https://ieeexplore.ieee.org/document/9498770
Zhang, S., Byrnes, A. P., Jankovic, J., & Neilly, J. (2019, Mar).
Management, analysis, and simulation of micrographs with
cloud computing. Microscopy Today, 27, 26-33.
doi:10.1017/S1551929519000026 Retrieved
from https://dx.doi.org/10.1017/S1551929519000026