Fluent Essays

TOPIC: Benchmark - Developing the Research Report This is the culmination of the lit review (Topic 2) and data collection (Topic 4). ATTACHED Demographic data and test stats need to be APA formatted—look in the Student Success Center for more information. This course has offered you the foundational materials required for performing Communication Research. This assignment will give you the opportunity to bring all of this knowledge together in an abbreviated research paper. Directions: Write a research paper of a total of 1,500-2,600 words that discusses the research you have performed—using 30-40 participants. Include the following: 1. Introduction (100-200 words) The purpose of the introduction is to familiarize your reader with the context of the research study. Paint a picture – in broader strokes – explaining the relevant cultural, historical, societal issues that inform this study. Explain, in short, how these ideas come together as a response to existing research. 2. Rationale for Research Questions (250-500 words) The purpose of the rationale is to briefly summarize themes from the literature review and explain how these themes justify your research question and hypotheses.   3. Methods (100-200 words) The purpose of the methods section is to clearly explain data analysis, method, and rationale for test statistics. The survey must contain 30-40 participants. It is important to be systematic, detailed, and clear in the explanation of these processes/methods. This should include an explanation of your analysis for the open-ended question too. 4. Results (300-500 words) The purpose of the results section is to clearly communicate your findings in the data collection and analysis portion of the project and relate these findings to your research questions and/or hypotheses. This section must include your test statistic (written in APA) and a table (also written in APA). In addition, you must show your thematic codes and exemplars. 5. Discussion (250-500 words) The purpose of the discussion section is to interpret the results and share insights you have gained about the communication phenomena examined in the study. This should include a discussion of the meaning derived from both the quantitative test statistic and the open-ended analysis. You should reflect on articles from literature review to discuss your findings. 6. Limitations and Future Research (250-500 words) No research study can take into consideration every variable influencing the results or shaping the outcomes of the research, but this section provides the opportunity to reiterate the limited scope of the study (This was accomplished, but due to other variables we were not able to…) and explain the unique variables that may skew results. In this section, you should explicitly discuss sampling techniques and measuring variables. The other purpose of this section is to propose future investigations or directions for inquiry/research. Compare and contrast the strengths and weakness of survey style research and explain future opportunities for alternative methods of communication research. You must include discussion of either participant observation, textual analysis (qualitative or quantitative), or interviews/focus groups. 7. Conclusion (100-200 words) 8. References LITERATURE REVIEW 2 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 negatively 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 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 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 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 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 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, 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-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 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 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.