Pub Date : 2019-09-09DOI: 10.22488/okstate.19.100402
J. Deaton
It goes without saying that I certainly don’t have a crystal ball, but I think it would be informative (and perhaps useful?) to examine where we are currently in aviation research, and maybe where we might want to be in the next five years. I don’t pretend to have special qualifications in that regard (predicting future developments), but I have worked in aviation human factors for nearly 40 years and hopefully I’ve learned something along the way that might be of use to students, researchers, and even journal editors. Just a quick note on my background: I retired from the Navy as an Aerospace Experimental Psychologist (AEP), and subsequently worked for small business, and currently academia (the latter for the past 18 years). So I consider myself fairly well acquainted with various entities that conduct research in aviation or at least promulgate its impact. Please note that the following comments are reflections resulting from my experience in the field, and thus opinion-based. I have not consulted peer-reviewed sources to support my contentions, but my intention here is to perhaps stimulate dialog and examine my experiences and those of others working in the field of aviation research.
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Pub Date : 2019-09-09DOI: 10.22488/okstate.19.100405
D. Trafimow, Tonghui Wang, Cong Wang, Hunter A. Myüz
Researchers feel they have the green light to ignore low levels of skewness because the central limit theorem indicates that such levels do not seriously compromise the validity of significance tests (e.g., Rouaud, 2013). And yet, significance testing is not the only issue, and the present focus is on two other issues where the central limit theorem does not come to the rescue. First, there is the question of how well the sample location statistic estimates the population location parameter. Surprisingly, skewness increases the precision of the estimation, and this increase in precision is impressive even with very low levels of skewness. Thus, by ignoring low levels of skewness, researchers are throwing away an important advantage. Second, experimental manipulations can cause differences in means across conditions, when there is no difference in locations across conditions; so the experiment seems to have worked based on means, when it really has not worked based on locations. Thus, moderate effect sizes can be caused by slight changes in skewness. For both reasons, it is recommended that researchers always attend to skewness, even when it is slight; and consider locations whenever they consider means.
{"title":"Does Slight Skewness Matter?","authors":"D. Trafimow, Tonghui Wang, Cong Wang, Hunter A. Myüz","doi":"10.22488/okstate.19.100405","DOIUrl":"https://doi.org/10.22488/okstate.19.100405","url":null,"abstract":"Researchers feel they have the green light to ignore low levels of skewness because the central limit theorem indicates that such levels do not seriously compromise the validity of significance tests (e.g., Rouaud, 2013). And yet, significance testing is not the only issue, and the present focus is on two other issues where the central limit theorem does not come to the rescue. First, there is the question of how well the sample location statistic estimates the population location parameter. Surprisingly, skewness increases the precision of the estimation, and this increase in precision is impressive even with very low levels of skewness. Thus, by ignoring low levels of skewness, researchers are throwing away an important advantage. Second, experimental manipulations can cause differences in means across conditions, when there is no difference in locations across conditions; so the experiment seems to have worked based on means, when it really has not worked based on locations. Thus, moderate effect sizes can be caused by slight changes in skewness. For both reasons, it is recommended that researchers always attend to skewness, even when it is slight; and consider locations whenever they consider means.","PeriodicalId":173443,"journal":{"name":"International Journal of Aviation Research","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115995445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-09DOI: 10.22488/okstate.19.100406
S. Winter, Justine L. Trombley
Technological advancements in space travel have brought the concept of private, commercial space transportation closer to reality. Companies such as Blue Origin and Virgin Galactic are working to offer commercial, low orbit space flights to paying customers, and SpaceX is even considering private trips to Mars. As these developments become closer to reality, an essential and missing gap in the literature relates to identifying what type of person would be willing to travel to and live on Mars. The purpose of this study was to develop and validate a statistical model to identify the significant predictors of a participant's willingness to travel to and live on Mars with 536 participants. The findings from the study indicate that nine of the 18 variables were significant predictors. Model fit was assessed through three measures and found to exist for the statistical model. The paper concludes with a discussion of the significant predictors, practical applications, and recommendations for future research.
{"title":"A Prediction Model for the Type of Consumer Willing to Travel to and Live on Mars","authors":"S. Winter, Justine L. Trombley","doi":"10.22488/okstate.19.100406","DOIUrl":"https://doi.org/10.22488/okstate.19.100406","url":null,"abstract":"Technological advancements in space travel have brought the concept of private, commercial space transportation closer to reality. Companies such as Blue Origin and Virgin Galactic are working to offer commercial, low orbit space flights to paying customers, and SpaceX is even considering private trips to Mars. As these developments become closer to reality, an essential and missing gap in the literature relates to identifying what type of person would be willing to travel to and live on Mars. The purpose of this study was to develop and validate a statistical model to identify the significant predictors of a participant's willingness to travel to and live on Mars with 536 participants. The findings from the study indicate that nine of the 18 variables were significant predictors. Model fit was assessed through three measures and found to exist for the statistical model. The paper concludes with a discussion of the significant predictors, practical applications, and recommendations for future research.","PeriodicalId":173443,"journal":{"name":"International Journal of Aviation Research","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128283762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-09DOI: 10.22488/okstate.19.100407
S. Winter, Dothang Truong, J. Keebler
Risk and risk perception remain focal areas of research within the aviation domain. The purpose of the current study was to assess an existing measure of a 26-item self-risk perception scale for pilots. A sample of 490 participants was used in the present study, and a confirmatory factor analysis was conducted on the original 26-item instrument. The findings indicated that there was a poor model fit of the original instrument. Through the use of modification indices, a new 13-item scale was produced, which resulted in a second-order CFA model. Flight risk was shown to be the second-order construct with general flight risk, high risk, and altitude risk as the first-order constructs. The new model reported good psychometric values of GFI of 0.933, AGFI of 0.893, CFI of 0.947, NFI of 0.923, normed chi-squared of 3, and RMSEA of 0.071. The findings produce a new 13-item scale that can be used by aviation researchers who wish to conduct studies related to the pilot's self-assessment of risk perception.
{"title":"The Flight Risk Perception Scale (FRPS): A Modified Risk Perception Scale for Measuring Risk of Pilots in Aviation","authors":"S. Winter, Dothang Truong, J. Keebler","doi":"10.22488/okstate.19.100407","DOIUrl":"https://doi.org/10.22488/okstate.19.100407","url":null,"abstract":"Risk and risk perception remain focal areas of research within the aviation domain. The purpose of the current study was to assess an existing measure of a 26-item self-risk perception scale for pilots. A sample of 490 participants was used in the present study, and a confirmatory factor analysis was conducted on the original 26-item instrument. The findings indicated that there was a poor model fit of the original instrument. Through the use of modification indices, a new 13-item scale was produced, which resulted in a second-order CFA model. Flight risk was shown to be the second-order construct with general flight risk, high risk, and altitude risk as the first-order constructs. The new model reported good psychometric values of GFI of 0.933, AGFI of 0.893, CFI of 0.947, NFI of 0.923, normed chi-squared of 3, and RMSEA of 0.071. The findings produce a new 13-item scale that can be used by aviation researchers who wish to conduct studies related to the pilot's self-assessment of risk perception.","PeriodicalId":173443,"journal":{"name":"International Journal of Aviation Research","volume":"4 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120910965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-09DOI: 10.22488/okstate.19.100404
D. Trafimow
The importance of having reliable measures in science research is obvious and cannot be overestimated. But in aviation research it often is impractical to collect test-retest reliability data because adding sessions can be expensive. What can be done? Based on classical measurement theory, the present article offers a procedure whereby researchers can draw limited conclusions about reliability even in the absence of reliability data.
{"title":"Drawing Conclusions about Reliability Withough Measuring It","authors":"D. Trafimow","doi":"10.22488/okstate.19.100404","DOIUrl":"https://doi.org/10.22488/okstate.19.100404","url":null,"abstract":"The importance of having reliable measures in science research is obvious and cannot be overestimated. But in aviation research it often is impractical to collect test-retest reliability data because adding sessions can be expensive. What can be done? Based on classical measurement theory, the present article offers a procedure whereby researchers can draw limited conclusions about reliability even in the absence of reliability data.","PeriodicalId":173443,"journal":{"name":"International Journal of Aviation Research","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124472959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-09DOI: 10.22488/okstate.19.100403
Rian Mehta
Between 2000 and 2016, postsecondary enrollment at Unites States universities increased at a rate of 28% (McFarland, et al., 2018). The report comes from the National Center for Educational Statistics stating that enrollment increased from 13.2 million to 16.9 million peaking at 18.1 million in 2010 (McFarland, et al., 2018). Over the last decade, graduate student enrollment across the Unites States has been increasing significantly (Okahana & Zhou, 2017). According to the 2017 report from the Council of Graduate Schools (CGS), graduate applications increased on average at a rate of 5.7% from the years spanning 2006 to 2016 (Okahana & Zhou, 2017). The report also enumerated the increase in graduate degrees awarded and conferred between 2006 and 2016. In the span of that decade, doctoral degrees conferred within the United States increased at an average rate of 4.7% per year and master’s degrees awarded increased at an average rate of 2.4% (Okahana & Zhou, 2017). The number of master’s degrees awarded is of course far in excessive of the number of doctoral degrees conferred but the percentages show a larger increase in the rate of growth of doctoral degrees.
{"title":"The Graduate Advisor-Advisee Relationship: What Both Parties Should Expect","authors":"Rian Mehta","doi":"10.22488/okstate.19.100403","DOIUrl":"https://doi.org/10.22488/okstate.19.100403","url":null,"abstract":"Between 2000 and 2016, postsecondary enrollment at Unites States universities increased at a rate of 28% (McFarland, et al., 2018). The report comes from the National Center for Educational Statistics stating that enrollment increased from 13.2 million to 16.9 million peaking at 18.1 million in 2010 (McFarland, et al., 2018). Over the last decade, graduate student enrollment across the Unites States has been increasing significantly (Okahana & Zhou, 2017). According to the 2017 report from the Council of Graduate Schools (CGS), graduate applications increased on average at a rate of 5.7% from the years spanning 2006 to 2016 (Okahana & Zhou, 2017). The report also enumerated the increase in graduate degrees awarded and conferred between 2006 and 2016. In the span of that decade, doctoral degrees conferred within the United States increased at an average rate of 4.7% per year and master’s degrees awarded increased at an average rate of 2.4% (Okahana & Zhou, 2017). The number of master’s degrees awarded is of course far in excessive of the number of doctoral degrees conferred but the percentages show a larger increase in the rate of growth of doctoral degrees.","PeriodicalId":173443,"journal":{"name":"International Journal of Aviation Research","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131494564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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