Online student Vs. on campus student in knowledge of disaster management
Distance education becomes a vitally important part of the higher education family. Just
about every major American university offers these courses. Distance education meets a
broader student audience, addresses student needs better, saves money, and, most critically,
uses modern learning pedagogy concepts (Fitzpatrick, 2001). Public and political interest in
distance education is particularly high in geographical regions where the student population
is widespread (Sherry, 1996). In fact, in some states, public-policy leaders recommend the
use of distance education as opposed to traditional learning. Distance education is defined as
structured learning, in which time and space separate the instructor and the student, uses the
latest technology to bridge the gap between the educational participants (Ham, 1995; McIsaac
& Gunawardena, 1996). Despite the rapid growth in technology-facilitated learning to meet
the increased demand of students, the quality of higher learning through distance education
has been questioned. In particular, there is a frequent public perception that distance learning
is not as active as traditional face-to-face education (Dede, 1996; Harrison, 2001).
Nevertheless, there is no significant difference, based on empirical evidence, between
conventional and technology-mediated learning (Verduin & Clark, 1991).
In this study, the researcher will try to investigate the effectiveness of the online courses vs.
on-campus classes in the teaching of disaster management by assessing the knowledge of the
student taking these courses in basic disaster management sciences and then comparing their
findings to reach to a conclusion. The researcher hypothesis that online students are as
capable as on-campus students in the knowledge of disaster management.
This article was published in Prehospital and Disaster Medicine journal in 2018. This
research study aimed to understand better how medical and non-medical hospital staff work
with online training regarding preparedness for pediatric disasters. In this research study,
improvements in the acquisition of knowledge of pediatric disaster pre-painfulness were
investigated within. Between the medical and non-medical staff of the children's hospital, all
of whom engaged in online training. Analysis and evaluation of pediatric disaster
preparedness training courses are required before the design and implementation of a national
program is feasible. The study location was a children's community hospital serving a
diverse, urban population in a large metropolitan area. In 2008, a multidisciplinary team
within the Children's Hospital Los Angeles Pediatric Disaster Education and Training Center
developed an online training course using the technique of developing A curriculum. This
research study showed that medical staff initially scored higher than non-medical staff in the
planning, triage, and age-specific care modules of an online pediatric disaster preparedness
training course on average. Still, in these three modules, they did not differ in their score
change levels. This research study showed that medical staff initially scored higher than nonmedical staff in the planning, triage, and age-specific care modules of an online pediatric
disaster preparedness training course on average. Still, in these three modules, they did not
differ in their score change levels. The study also found that in the disaster management and
hospital emergency code response modules, non-medical personnel initially scored lower
than medical staff on average but had higher score change rates in these two modules, and
their scores increased through additional attempts.
This research tested why students chose distance education and students ' perceptions of the
quality and difficulty of those courses compared to classroom courses. The data suggest that
students strongly prefer distance education, primarily because it helps them to balance their
other obligations more efficiently. In online learning environment, respondents also perceive
they achieve higher quality educational outcomes. We do not accept that for the ease of using
distance learning, and we lose a quality education. While distance learning may be most
suitable at colleges and universities with a large number of adult learners, commuters, and
part-time students, institutions may have some educational advantages in integrating some of
the best aspects of distance learning into traditional courses to build a "hybrid" learning to
This study examined the efforts of one state to plan and offer a selection of online career
development courses. The study examined the perspectives of both the teachers and the early
instructors in these online and technology-mediated professional development courses by
survey research methods. Findings in this study indicated that early educators were using
technology for personal use but may be less familiar with learning technologies. The research
findings suggest that some early teachers have the technical skills and confidence required to
use and benefit from the online modules for professional development. Still, most early
teachers also tend to use both technology and input from an educator or supervisor while
participating in professional development.
This research aims to concentrate on the difference between face-to-face and online training
through the Diagnosis and Echocardiography (ECG) telegram program for emergency
medicine residents. This quasi-experimental study was conducted during 2016-2017 through
the participation of 140 medical students studying emergency medicine at Isfahan Medical
Sciences University. Individuals were divided into two classes of 70 students trained by two
methods, like face to face and a mobile communication application (Telegram) for ECG
interpretation. To evaluate the ECG participants' interpretational and diagnostic skills before
and after the training, they used the same test and recorded the percentage and their scores of
the correct answers. Using SPSS Software, they analyzed the data. The mean student score
before and after training in the face-to-face group was 12.3 ± 2.37, and 16.53 ± 1.99
respectively, while the mean student score back and after exercise in the online class group
was 12.12 ± 2.06, and 16.56 ± 2.11. A significant increase in the level of knowledge and
skills of ECG interpretation in both groups was noted, but an increase in the level of
knowledge was noted.
This study was carried out by designing online training to improve the awareness and
minimize autism-related stigma among college students. Participants (N= 365) completed the
pre-test, online, and post-test training. Women reported less stigma regarding autism than
men. Participation in preparation was associated with reduced stigma and increased autism
awareness. Although the participants had relatively high baseline knowledge of autism,
misunderstandings were common, particularly in open-ended responses. Participants also
associated autism with other disorders, such as delays in learning.
The study aimed to assess changes in the self-reported performance of smoking cessation
interventions as per the 5A model (Ask; Advise; Assess; Assist, and Arrange follow-up)
among clinicians; and identify key barriers and facilitators in the implementation of smoking
cessation before and after an online smoking cessation training program. By using the Prepost evaluation model, they analyzed self-reported end of smoking interventions among
clinicians working in Catalan hospitals (Spain) in implementing the 5A model. Also, they
have analyzed factors at the human, behavioral, and organizational level that serve as
obstacles and facilitators in implementing the model 5A. They used a questionnaire (scored
from 0= none to 10= most possible) of 63 items reflecting each of the 5A performances. The
survey was completed both immediately prior to training and six months after. Researchers
analyzed data from those participants who had a clinical function and responded to pre-and
post-questionnaires using the paired data non-parametric test (Wilcoxon) to assess
improvements in scores. Ultimately, the performance of the assist component was
significantly increased, and a follow-up component was planned for the intervention. Scores
in the perception of the overall level of preparation, ability to use smoking cessation
medications, increased level of competence, and organizational acknowledgment at the
follow-up; nevertheless, the score in the perception that suggests cessation of smoking is part
of their job decreased.
This study was done to evaluate the effectiveness of an online resource for training designed
to improve the ability of medical students to recognize dying, using an Online multicenter,
double-blind, randomized controlled trial (NCT03360812). The teaching tool for the
intervention group was built from the weightings of different signs/symptoms of a panel of
specialist palliative care doctors to identify dying. The population of the study was senior UK
medical students who participated. They analyzed 92 patient summaries and gave pre, post,
and two weeks after training a likelihood of death within 72 hours (0 percent likely survival–
100 percent certain death). First result: (1) Mean Absolute Difference (MAD) score between
scores of the participants and the experts immediately after intervention. The study result was
out 168 participants, 135 (80 percent), completed the trial; 66 (49 percent) took the
intervention. After using the training resource, the intervention group had a better
understanding with the experts in their survival estimates and in the weighting of clinical
factors as well as in their survival estimates (πMAD ubiquitously ibid.= < 0.001). At the 2week time point, there was no learning impact of the MAD scores! (MAD= 1.50,
ubiquitously= 0.21). The intervention group was statistically more expert in their decisionmaking versus controls at the 2-week time point (intervention CWS= 146.04 (SD 140.21),
control CWS= 110.75 (SD 104.05); p= 0.01). The online training tool has proved effective in
altering medical students' decision-making to align more with professional decision-making.
One thing that I noticed in this study that caught my attention is the amount of vocabulary
mistakes that make me sometimes struggling to understand the content.
This paper analyzed attitudes regarding the effectiveness of distance learning and determined
the effect such views had on choices. Two hundred and one students (56% males and 44%
females) attending a major southeastern university and 26 employers (60% males and 40%
females) attending a university career fair took part in this report. Applicants reviewed two
job descriptions, two resumes, and the authors created two cover letters.The participants were
asked to review both an undergraduate and an MBA candidate's qualifications. Results,
partially supported the hypothesis, which is hypothesis 1 "that perceived technology
usefulness will be related to perceptions of distance learning and on-line degrees", hypothesis
2 "that the number of hours spent using technology in a week will be related to perceptions of
distance learning and on-line degree" showing that individuals assumed distance education
was of lower quality than traditional classes. This belief influenced Their hiring decisions.#9
This study tries to study the performance of online and traditional students taking the
Organization and Management course the study sample includes all students in seven
sections of an organization and management undergraduate course taken in either the Fall
2006 or Spring 2007 semesters at a large public university in a large Eastern metropolitan
area. Results complement previous analyzes by finding that when researchers-controlled
factors such as class, major, and GPA, online course students do the same in objective
performance measurements, but not better than traditional course students. Researchers have
also found that females performed at least as well as males in the online sections. Researchers
discussed these results with some changes in online education and some people's persistent
perception that online education is somewhat problematic because more discipline is needed
in online courses.
This study utilized inferential statistics to investigate the differences between the mean GPA
for a traditional information technology education program and a fully online program of the
same courses at a four-year public college in the Southeastern United States. Great efforts
have been made to make sure that the online program is as similar as possible to the Face-toFace Bachelor of Information Science program. There were 308 conventional students and 71
full-line students in the study. The study results found no significant difference in GPA
assessed student success in both the fully online curriculum and the conventional course.
Blau, G. (2008). Student Performance in Online and Traditional Sections of an
Undergraduate Management Course. Retrieved from
Dede, C. (1996). Emerging technologies in distance education for business. Journal of
Education for Business, 71, 197-204.
Fitzpatrick, R. (2001). Is distance education better than the traditional classroom? Retrieved
Ham, R. (1995). Distance education: Teaching tools for the 21st Century. The Technology
Teacher, 45, 43.
Harrison, N. (2001). Is distance learning the poor cousin of ‘proper’ training and education?
Intermedia, 29, 10-17.
Hannay, M. (2006). Perceptions of Distance Learning: A Comparison Of On Line. Retrieved
Johnathan, Y. (2013). An Investigation Of Traditional Education Vs. Fully-Online. Retrieved
Jillian, A. Katherine, R. (2004). The Competitive Advantage of Online versus Traditional
Education. Retrieved from https://eric.ed.gov/?id=ED492477
McIsaac, M.S., & Gunawardena, C.N. (1996). Distance education. In D.H. Jonassen (Ed.),
Handbook of Research for Educational Communications and Technology. New York, NY:
Martínez, C., Castellano, Y., Company, A., Guillen, O., Margalef, M., Arrien, M. A. (2018).
Impact of an online training program in hospital workers' smoking cessation interventions in
Bolivia, Guatemala, and Paraguay. Tobacco Prevention & Cessation, 4(Supplement). DOI:
Pham, P. K., Behar, S. M., Berg, B. M., Upperman, J. S., & Nager, A. L. (2018). Pediatric
Online Disaster Preparedness Training for Medical and Non-Medical Personnel: A MultiLevel Modeling Analysis. Prehospital and Disaster Medicine, 33(4), 349–354. DOI:
Richardson, J. T. E. (2010). Face-to-face versus online tuition: Preference, performance, and
pass rates in white and ethnic minority students. British Journal of Educational Technology,
43(1), 17–27. DOI: 10.1111/j.1467-8535.2010. 01147.x
Sherry, L. (1996). Issues in distance learning. Retrieved
Verduin, J. R., & Clark, T. (1991). Distance education: The foundations of effective practice.
San Francisco: Jossey- Bass.
White, N., Oostendorp, L. J., Tomlinson, C., Yardley, S., Ricciardi, F., Gökalp, H., Stone, P.
(2019). Online training improves medical students' ability to recognize when a person is
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Data Analysis Plan
The research will employ the use of an observation schedule based on a check-list to
complement the other data collection methods used like interviews and questionnaires. It helps in
the synchronization of the data collected through the other means.
Data analysis is the process through which research uses to find the meaning of the data
that was collected during the research (Sutton & Austin, 2015). It includes activities like coding,
sorting, data entry, processing, and result interpretation. The choice of the analysis techniques to
be used largely depends on the suitability in regards to the nature of the study.
For this research, the first step in the analysis will be data entry and editing. Data received
from the questionnaires and observation schedule will be checked for any errors. It is an important
proofreading step that helps in the elimination of any accidental misleading data that might result
from errors during the data collection stage (Loehnert, 2010). The data will then be subjected to
both quantitative and qualitative analysis. Qualitative analysis will be used to analyze the data
collected from the personal observations and the open-ended questions in the questionnaires. The
quantitative data will be made up of the close-ended questions in the questionnaires and
categorized data. The quantitative data will then undergo coding to prepare it for further analysis.
Statistical Package for Social Sciences (SPSS) will be used to carry out the coding process
and help in the generation of descriptive statistics such as graphs, frequency tables and percentages
where applicable. The reason for using this method is because the data were arranged into different
categories in relation to the views, opinions, and perceptions of the respondents. SPSS makes it
easy to code different types of data and does an excellent job of providing descriptive analysis and
is easy to use. It also has a huge number of statistical procedures that are specifically made to be
used in analyses of social sciences data and has the capability of handling a large amount of data
(Ozgur, Kleckner & Li, 2015).
Loehnert, S. (2010). About Statistical Analysis of Qualitative Survey Data. International Journal
of Quality, Statistics, and Reliability, 2010, 1-12. doi: 10.1155/2010/849043
Ozgur, C., Kleckner, M., & Li, Y. (2015). Selection of Statistical Software for Solving Big Data
Problems. SAGE Open, 5(2), 215824401558437. doi: 10.1177/2158244015584379
Sutton, J., & Austin, Z. (2015). Qualitative Research: Data Collection, Analysis, and
Management. The Canadian Journal of Hospital Pharmacy, 68(3). doi:
Data Analysis Plan
This section describes the research design and technical details for releasing and collecting
survey responses, as well as conducting the analytical work to develop insights.
The study will be a qualitative data study to understand more about the overall theme of
emergency preparedness of individuals in Puerto Rico. The study will also look to understand
subthemes of perceived threats and concerns detailed by the subjects, first-hand experiences to
understand gaps in the current system for providing assistance to individuals during these
Population and Sample
The population to be studied is the adult population of Puerto Rico. To complete the study, 50
participants will be sampled from this population by recruiting through Facebook and other
social media outlets. Those who sign up and qualify to participate will receive a secure link to a
Qualtrics survey. This is a one-time survey.
Social media channels will be used to source participants who meet the criteria. For those who
sign up and qualify, a Qualtrics survey tool will be used to create and distribute the survey. The
participant will answer open ended, qualitative survey questions that relate to their level of
preparedness for a disaster, what past experienc ...
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