Post-Reply: Mixed Methods Design
INSTRUCTIONS
Please read the 6 topics here and
read the replies in the pictures( must be the same way in the replies in the pictures that i attached here )then start the assignment.
please watch out for the plagiarism the last assignment I reserved from you was more than 15% are plagiarism
please follow this steps
1- I will list 6 different articles. I want you to make one reply in each one
total 6 replays
Each reply is 300 words
2- I need you to make total 6 replays .
3- ON each topic make one reply.
4- # I need it to be done on APA 7th – professional template.
5- # I want each reply in one page independent with its own references
6- I loaded a few pictures as an example of a reply from another student in my class.
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1- Matthew Bragen,
Factors for Choosing a Mixed Methods Design
Topic and Design
I chose to revisit the topic of pilot fatigue in commercial aviation for this week’s discussion post. Previously I had imagined a mixed methods study on the topic, and I believe using the framework of the six factors to consider when choosing a mixed method design will help to determine if this is a good approach. In the hypothetical study I first thought an explanatory sequential design worked best, but I have decided on a convergent design after going through the six factors detailed below, as well as looking at several pilot fatigue studies. In Bennett’s (2019) mixed methods study on pilot fatigue and workload he used quantitative data already available and compared it to interviews and jumpseat observations he conducted. This convergent study of comparing numerical data to the observations and interviews of flying commercial pilots is useful in determining what the quantitative data gets right, and what may be missed or under represented. Caldwell’s (2012) paper highlights several high-profile cases in which pilot fatigue played a role in an accident. To me it is logical to compare the quantitative data of accidents and pilot fatigue, to interviews and testimonials from pilots that have either been in accidents or were in situations that developed due to fatigue, and what underlying factors caused that state of fatigue. Quantitative data on pilot fatigue in commercial aviation would be taken such as: when do pilots get most fatigued, what sleeping, schedule, or work situations contribute to this, and other similar data that can be measured. Concurrently, I would conduct interviews and surveys of current commercial pilots and qualitatively measure when they felt fatigue was worse, most impactful, and what situations led to increases in fatigue.
Six Factors
The six factors given by Creswell and Creswell (2018) when choosing a mixed methods design are: outcomes expected, integrating data, timing in data collection, emphasis placed on each database, design most suited for the field, and whether there is a single researcher or a team. Creswell and Creswell (2018) state that outcomes are shaped by the intention of using a mixed methods approach. The intent I have for using such an approach for the topic of pilot fatigue is to compare numerical data, that is often cold and removed, to qualitative data from interviews and personal experiences. I expect that the outcome will show that data on pilot fatigue, its causes and results, are similar from both data sets, but not entirely identical. I believe the differences found could lead to interesting areas for further research and improvement. The expect outcomes and intent are best suited by a convergent mixed methods design. When integrating the two data sets, I am looking to merge to separate sets of data, not build from one approach to another. At first, I thought that building from a quantitative data set would best suit this topic, but came to the conclusion that interviewing pilots on whether or not they experienced fatigue in the exact ways that the numerical data showed would likely not uncover anything new or interesting, but rather reinforce what one data set already shows. The timing for collection of the two data sets is not extremely important for this topic. The two data sets could be collected concurrently or sequentially. The databases do not necessarily build on each other, the separate analysis and comparison is what is important. The two datasets, quantitative and qualitative, will have equal emphasis and importance. The goal is to compare and contrast the data, not to have one set be the primary basis of an outcome or conclusion. I believe that many of the mixed method design are suited for this field. I had considered doing an explanatory sequential design before deciding on a convergent design. I could also see a exploratory sequential or other complex mixed methods design giving interesting and meaningful results as well. Finally, this hypothetical study would be done by one researcher, me, and this is more suited to sequential designs typically. However, it is not important that I collect both datasets at the same time for my study, and this alleviates the assumed burden of excessive work for a convergent design.
References
Bennett, S. (2019). Pilot workload and fatigue on four intra-European routes: a 12-month mixed-methods evaluation. Journal of Risk Research, 22(8), 983–1003. https://doi.org/10.1080/13669877.2018.1430704
Caldwell, J. (2012). Crew Schedules, Sleep Deprivation, and Aviation Performance. Current Directions in Psychological Science, 21(2), 85-89. Retrieved January 21, 2021, from http://www.jstor.org/stable/23213098
Creswell, J. W., & Creswell, J. D. (2018). Research design: qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications, Inc.
Onwuegbuzie, A., & Leech, N. (2005). On Becoming a Pragmatic Researcher: The Importance of Combining Quantitative and Qualitative Research Methodologies. International Journal of Social Research Methodology, 8(5), 375–387. https://doi-org.cyrano.ucmo.edu/10.1080/13645570500402447
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2- Michael Stein
A mixed methods experimental design is a great method for discovering and testing new methods for improving current methods. The mixed methods experimental design “involves the researcher collecting and analyzing both quantitative and qualitative data and integrating the information within an experiment or intervention trial (Creswell & Creswell, 2018, p.228). Using the mixed methods experimental design would be an excellent tactic to test the development of new technology for pilots. The use of mixed method research is not a new idea to the aviation industry, as it is the most commonly used when researching aviation. During the exploratory sequential core design stage, we can develop and understand what advances in technology a pilot could utilize for better improvement of the piloting. Also, during this stage, we will recruit participants for the study and develop pre and posttest measures to better understand the improvement. This all happens before the experiment begins. During the experiment, or the convergent core design stage, “an interactive approach may be used where iteratively data collection and analysis drives changes in the data collection procedures” (Fetters & Curry & Creswell, 2013). We can observe and record data on how the new technology is affecting the pilots and their ability to fly the aircraft. While observing and collecting this data, we can also discover any potential mediating and moderating factors. Lastly, we finish the experiment and dive into the data and discover our conclusions and future research questions. We embed the “explanatory sequential design into the experiment after the study to follow up on the experiment outcomes” (Creswell & Creswell, 2018, p.228). An explanatory sequential design consists of two distinct phases: quantitative followed by qualitative. In this design, a research first collects and analyzes the quantitative (numeric) data. The qualitative (text) data are collected and analyzed second in the sequence and help explain or elaborate on, the quantitative results obtained in the first phase” (Ivankova & Creswell & Stick, 2006). During this last phase of the experimental design, we can infer on why the results occurred. This is a vital portion to any research study. Using the explanatory sequential core design allows up to both examine the numeric data but also interview the participants for additional data. I think this would be most beneficial for developing new aviation technology. We want to discover not only does it provide better results for flying, but if it benefits the pilots. Maybe we will discover that it can lead to better pilotage but increases a pilot’s workload. That may not be beneficial to the safety in aviation. Maybe we will find out that the new technology could have better user interface that will aid in easier usage for the pilot. The combination of raw data and participant interviews will also lead researchers to explain how the new technology may have worked during the trial. Without having post experiment feedback and interviews, some of this information will never be discussed. Using the information gathered using both the qualitative and quantitative method with create a more thorough and accurate result of the experiment. I think the experimental design is a perfect method for development of new technology in aviation.
References
Creswell, J. W., & Creswell, J. D. (2018). Research Design Qualitiative, Quantitative, and Mixed Methods Approaches (5th ed.). Los Angeles, LA: SAGE.
Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs-principles and practices. Health services research, 48(6 Pt 2), 2134–2156. https://doi.org/10.1111/1475-6773.12117
Ivankova, N. V., Creswell, J. W., & Stick, S. L. (2006). Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice. Field Methods, 18(1), 3–20. https://doi.org/10.1177/1525822X05282260
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3- Christine Sperdut
A sequential explanatory research design is a mixed-methods research strategy that collects and analyses quantitative data in the first phase of research then build on the results of the initial quantitative results in the second phase of qualitative data research. This design method is typically used to interpret quantitative results by examining the initial results qualitatively (Cresswell, 2009).
In order to conduct a sequential explanatory research project, I will first need to collect data. For my particular project regarding noise impacts surrounding airports, I will conduct sound trials surrounding a major metropolitan airport. Important considerations for collecting data include: instrumentation to be used, where to collect the data, organization of data received, and outliers (Cresswell, 2009).
Once I can determine quantitatively where the sound is the loudest and for the longest periods of time, then I can begin with the qualitative research. For this portion, I will interview and/or residents living in the areas that I surveyed and found to be impacted negatively by noise disruptions. This will allow me to determine what is the most impactful – short but loud noise impacts, ambient noise heard all day, or a combination thereof. Once the qualitative data is received, I will then need to transform the data to understand how it relates to the quantitative data I already received (Cresswell, 2009).
Van Pragg and Baarsma did a similar research project in 2005 and found aviation noise impacted the residents closest to the airport and even had an impact on the value of the properties. They utilized a survey for their qualitative research (2005). That could also be an option for my project that could allow for stellar results.
As with any research project, it will be important to validate the data at the end of the study. Is the data correct? Can it be validated by another study? Both the quantitative and qualitative aspects of my study will need to be valid in order for this project to be successful (Cressell, 2009).
Advocates for mixed-methods approaches see that value in mixing both quantitative and qualitative data into one project. The results are a more unified look at the problem being researched and credibility of the results (Creamer, 2018).
Once the data collection process is complete, the information will need to be organized for the report. Typically, sequential studies organize the data first by quantitative methods and data, then qualitative methods and data, then conclusions and interpretation. In the interpretation is where the researcher can outline how to qualitative findings helped the quantitative aspects of the research (Cresswell, 2009).
References
Creamer, E. G. (2018). Striving for Methodological Integrity in Mixed Methods Research: The Difference Between Mixed Methods and Mixed‐Up Methods. Journal of Engineering Education, 107(4), 526–530. https://doi-org.cyrano.ucmo.edu/10.1002/jee.20240
Cresswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches. SAGE.
van Pragg, B. M. S., & Baarsma, B. E. (2005). Using happiness surveys to value intangibles: the case of airport Noise. Economic Journal, 115, 224–246.
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4- Sho Mehring
Mixed Method Designs
As previously studied, the mixed methods approach provides a mix of quantitative and qualitative research to develop a conclusion. In developing a mixed method experiment it is critical for the researcher to establish set boundaries so that the readers understand what is going on. Creswell (2018) states, “Because mixed methods research is still somewhat unknown in the social and human sciences as a distinct research approach, it is useful to convey a basic definition and description of the approach in a method section of a proposal” (p. 297). The clear explanation of a definition and approach are some of the factors that are mentioned in the textbook to create a successful mixed methods experiment as it provides the reader with a clearer understanding of the type of experiment in addition to how the experiment is conducted differently with regards to quantitative and qualitative experiments.
Experiment
An experiment I would like to design is to analyze the effects that multi-cultural learning has on an individual’s ability to learn and conclude whether it provides a greater benefit to their overall academic development. There is a general understanding that an individual’s culture effects their learning. As TSEOL states, “Cultural differences can often be subtle; however, they do impact students’ learning” (p. 1). Additionally, according to Mantiri (2013), the variety in an individual’s cultural background as well as other factors can also affect the student’s ability to learn. As a result, an individual who learns in multiple cultures can potentially gain an advantage as they potentially have a greater ability to understand and process knowledge. While providing some challenges, it is a topic that interests me greatly as I personally believe I benefited from this and would like to see if there are similar effects in others.
Design
The design for the experiment will incorporate a convergent design. I think that the convergent mixed method design best suits this experiment due to its ability to simultaneously collect qualitative and quantitative data. As this experiment will require the examination of the cultural effects on learning, the qualitative data will be collected and compared to the quantitative data which would ultimately be the academic results of the participants.
Factors and Rationale
The first three factors that the textbook mentions are definition, terminology, and background of methodology. Each of these are relatively straightforward to explain to the reader as they appear in most research papers regardless of the type of experiment being conducted. Many of these factors exist either in the abstract or the introduction of the research paper providing readers with an immediate understanding of what to expect throughout the research paper.
The fourth factor is the reason for choosing a mixed methods approach. For this experiment, the mixed methods approach is best compared to strictly adhering to qualitative or quantitative experiments as it examines the impacts social and cultural influences have on an individual’s academic performance. Without the ability to analyze the cultural impact on a student, the experiment would not have any merit or reasoning to be continued, thus utilizing a mixed methods approach is best suited for this kind of experiment.
Fifth is the mixed methods design to be used. As mentioned earlier, the convergent design is best suited for this experiment as it provides a simultaneous analysis of the qualitative and quantitative data that can be compared to determine various intervals throughout the experiment and see whether there is a difference between the experimental group and control group.
Lastly, the biggest challenges that affect his experiment would be finding participants as well as the length of the experiment. As this would require families to move to different countries and adjust to a new academic style, finding participants for this study who are willing to be a part of the experiment and be monitored for an extended period will be difficult. Overcoming these challenges will be critical in determining the success of the experiment.
Conclusion
If all these factors can be managed, the experiment should be able to produce data that points to a multi-cultural background assisting students in becoming better learners that will hopefully benefit them further on in their life and career.
References
Creswell, J. W., & Creswell, J. D. (2018). Research design: qualitative, quantitative, and mixed methods approaches. SAGE Publications, Inc.
Mantiri, Oktavian, The Influence of Culture on Learning Styles (February 17, 2013). Available at SSRN: https://ssrn.com/abstract=2566117 or http://dx.doi.org/10.2139/ssrn.2566117
Teachers of English to Speakers of Other Languages, Inc. (2006). Position Statement on the Diversity of English Language Learners in the United States. https://www.tesol.org/docs/pdf/7212.pdf
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5- 2 days ago
Nathan Hinds
Mixed Methods
A participatory-social justice design is well-suited to any field of study, and aviation is no exception. For example, Ferla and Graham (2019) conducted a study “To identify and understand the causes underlying female underrepresentation in the industry” (p. 2). A study I would consider conducting is the prevalence of sexual harassment in the workplace for pilots. Unfortunately, the issue remains prevalent in aviation, and Appelnaum and Fewster (2002) discussed in their study on human resource issues in the industry that a common theme is “the lack of respect and outright sexual harassment experienced by women working in the airline industry” (p. 72). The study would require a large amount of involvement with support groups of victims of workplace sexual harassment, including “feedback” and a continuous open dialogue “with community stakeholders” (Creswell & Creswell, 2018, p. 232). An imbedded convergent mixed-methods design would be used, and the quantitative aspect might include a collection of statistical research and studies regarding workplace sexual harassment both inside and outside of the aviation industry. Qualitative aspects could include interviews of victims willing to share their experiences. Additionally, an imbedded “exploratory core design” may also be utilized, in which a “quantitative instrument based on the qualitative findings” of the relationship with victims is developed. In this particular study, this may include a survey sent to participants who have experienced workplace sexual harassment as part of a flight crew, asking them uniform questions about their experiences. At the end of the study, after all components have been completed and all the data compiled, conclusions can then be drawn giving equal weight to each aspect of the study.
Question #3:
The mixed methods intervention design offers the researcher the multifaceted nature of qualitative research combined with the experimental nature of the quantitative design. This type of study typically involves the foundations of quantitative study, but then engages in deeper qualitative activities, such as examining “participants’ barriers and facilitators’ experiences during the trial” or examining “how the participants are experiencing the treatment” (Creswell & Creswell, 2018, p. 229). Understandably, such a design produces numerous threats to validity. Onquegbuzie (2006) presents a number of threats to validity for mixed method studies in general, and many of those mentioned are applicable to the design presented. For example, the author points out “new types of legitimation,” which includes “insider-outsider legitimation” (p. 60). In other words, the researcher needs to present “the insider’s view and the observer’s view” (p. 58). In a study in which both the observer and the participants are being scrutinized, striking the balance between the two entities can pose a challenge. It is also important to note the balance between the balance between qualitative and quantitative aspects. Onquegbuzie (2006) mentions the “multiple validities” issue, which is concerned with “the extent to which addressing legitimation of the quantitative and qualitative components of the study result from the use of quantitative, qualitative, and mixed method validity types” (p. 57). With regards to the mixed method intervention types, it is important that the results be interpreted based on all of the data acquired, rather than relying heavily on the empirical results or the interview phase.
References:
Appelbaum, S. H., & Fewster, B. M. (2002). Global aviation human resource management: Contemporary recruitment and selection and diversity and equal opportunity practices. Equal Opportunities International.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Ferla, M., & Graham, A. (2019). Women slowly taking off: An investigation into female underrepresentation in commercial aviation. Research in Transportation Business & Management, 31, 100378.
Onwuegbuzie, A. J., & Johnson, R. B. (2006). The validity issue in mixed research. Research in the Schools, 13(1), 48-63.
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6- Yohanna Enders
Mixed Method Design
When thinking of a study that is important in today’s day and age, as well as a study that needs to be researched more is aviation environmental factors and the effects on communities. This study will be having three variables that will be considered these being air pollutants, noise pollutants, and lastly water pollutants. Even though in the aviation community these three pollutants are being studied daily by researchers more research needs to be conducted to continue to reduce the footprint of the aviation industry. The best study of mixed-method design for this type of research will be case-study. This is because different case studies will be needed to test the outcomes of new research on the new factors put in place. By choosing the mixed-method case study design the researcher uses one or more of the design styles can be any grouping of convergent, explanatory, sequential, or exploratory sequential (Creswell and Creswell, 2018). In the case study design method, the research will also use both quantitative and qualitative research methods to gather data which is important in the data within aviation to help ensure the safety of those around communities. Looking at the three pollutants in the research study that will be examined and what causes them one first examines air pollutants. Air pollutants are cause from engine emissions put out into the air. Other air pollutants that the aviation industry produce is from ground equipment. The second pollutant caused by aviation will be noise pollution again from engines and other aviation equipment that affect surrounding communities of airports. The last pollutant is water pollution cause from deicing fluid and other fluids such as oil, and gas. Back to relating the mixed methods design one needs to take quantitative survey which can be done by taking noise pollutant survey from surrounding communities. Next qualitative interviews and studies from research on engines and water pollution. This can be done from engine test with those that design and develop engines. Water pollution can be measured by the surrounding water areas that pollutants can disperse into around airports. Moving to data analysis first the research needs to see what the levels are in all of the research variable and how can what then needs to be done to change. In an article for example done around a Pennsylvania stream the water pollution that was in water sample and the effects on fish and game around the area. In the research studied it was found that in the water high levels of ammonia were found. Ammonia levels were directly found to be from runway deicing areas drainage (Koryak, Stafford, Reilly, Hoskin, and Haberman, 1998). Taking this information about the drainage engineers in the field of aviation can take the data and develop new areas that will be adequate in the drainage of dicing fluids. Another article that can be looked at that is a example of how engineers used research is from the Denver airport. The engineers took the landscape and information based on runoff from ramp spaces to develop drainage under the airports concourses that separated clean and contaminated runoff into ponds (Backer, Smith, and Habben,1994). Overall looking at all of these examples and using the mixed method design is the best option for the type of research that needs to be conducted in the development and studying of pollutants caused from aviation.
Refence
Backer, D. S., Smith, D., & Habben, C. E. (1994). Deicing Dilemma. 56-59.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed., p. 4). Sage Publications, Inc.
Koryak, M., Stafford, L. J., Reilly, R. J., Hoskin, R. H., & Haberman, M. H. (1998). The impact of Airport Deicing Runoff on Water Quality and Aquatic Life in a Pennsylvania Stream. Journal of Freshwater Ecology, 13, 288-298. doi:10.1080/02705060.1998.9663621