Indicators of Engineering Students' Academic Performance: A Gender-Based Study (original) (raw)
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American Society for Engineering Education, 2020
Academic performance of college students, particularly those who are in an engineering program, continues to receive attention in the literature. However, there is a lack of studies that examine the simultaneous effects of students' systems thinking (ST) skills and proactive personality (PP) on academic performance. The linkage between ST skills and PP has not been investigated adequately in the literature. The study aims to examine the ST skills and PP to predict the academic performance of engineering students and to find if there is a relationship between students' PP and the level of ST skills. Two established instruments, namely, ST skills instrument with seven dimensions and PP with one dimension, are administrated for data collection. A web-based cross-sectional survey using Qualtrics was used to collect the data using a sample of college engineering students. Different classification techniques were applied to perform the analysis and to compare the validity of results. This study provides implications and contributions to the engineering education body of knowledge. First, the study provides a better understanding of students' academic performance. This intent is to help educators, teachers, mentors, college authorities, and other involved parties to understand students' individual differences for a better training and guidance environment. Second, a closer look at the level of systemic thinking and PP of engineering students would help to understand engineering students' skillset.
Determinants of students' systems thinking continue to receive attention in the literature. However, there is a lack of studies that assess students' systems thinking (ST) skills, along with their proactive personality in the aspect of academic performance. The relationship between ST and proactive personality is somewhat complex, although a high level of the overview might have been provided, the in-depth analysis has not been adequately investigated in the literature. The aim of the research paper is (1) to examine the ST skills and proactive personality of engineering students and (2) to find the relationship between students' proactive personality and the level of ST skills. This research paper would provide important implications and contributions to the body of knowledge of engineering education. First, the research will provide a better understanding of students' thinking and personality. This intent is to help educators, teachers, mentors, college authorities, and others involved parties to understand students' individual differences for a better training and guidance environment. Second, a closer look will be provided to better understand the relationship between the level of systemic thinking and the proactive personality of engineering students and how they influence each other in the complex system problem domain.
2020 International Conference on Decision Aid Sciences and Application (DASA) , 2020
The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.
Determinants of Systems Thinking in College Engineering Students: Research Initiation
The 126th Annual Conference & Exposition American Society for Engineering Education, Tampa, FL., 2019
As the world becomes increasingly complicated, systems thinking continues to gain recognition as an important and necessary skill for future engineers. Systems thinking does not replace traditional technical skills required of engineers; rather, it provides a complementary skillset to help better navigate complex systems and their corresponding problems. The increasing complexity of U.S. industries demands that universities train and educate future engineers with systems-thinking skills to solve the range of interconnected problems companies may face. Many factors have the potentials to impact systems-thinking skills. This paper aims to identify the effects of potential impacting factors on the systems-thinking skillset. Current college engineering students were the target population of the study. Structural Equation Modeling was performed to quantify the relationship between systems-thinking skills and potential impacting factors. The results of this study indicated that employment status would affect the overall systems-thinking skills of the engineering students and the engineering students with outside job experience will score higher than students without outside job experience in the systems-thinking skills.
Academic Performance: Mapping Traits of Engineering Students
Journal of Education and Practice, 2013
The purpose of the study is to assess the traits of engineering students in relation to their performance and adjustment. Participants were 272 engineering students. The tools used are Myers Briggs Type Indicator (MBTI) and student problem checklist to assess the personality traits and adjustment level of the students. The statistical procedures employed were t test. The analyses of the data signify that the students with personality traits such as Thinking and Sensing types show better performance and adjustment than the students with personality such as Feeling and Intuitive types. The study indicates that if students learning styles matches to their chosen academic course, they tend to show better performance and less adjustment problems though the mental abilities is same for both.
Cognitive Styles, Gender, and Student Academic Performance in Engineering Education
Education Sciences, 2021
Cognitive styles affect the learning process positively if tasks are matched to the cognitive style of learners. This effect becomes more pronounced in complex education, such as in engineering. We attempted to critically assess the effect of cognitive styles and gender on students’ academic performance in eight engineering majors to understand whether a cognitive style preference is associated with certain majors. We used the Cognitive Style Indicator (CoSI) with a sample of n = 584 engineering students. Multiple standard statistical tests, regression tree analysis, and cluster analysis showed that none of the three cognitive styles was exclusively associated with better performance. However, students who had a stronger preference for a cognitive style were more likely to perform better. Gender, the major, and students’ clarity about their cognitive style were shown to be the best predictors of academic performance. Female students performed better and were clearer about their pref...
2020
He received a BS in Material Engineering from Auburn University, an MBA from Nova Southeastern and a PhD in Industrial and System Engineering and Engineering Management from the University of Alabama-Huntsville. His professional experience includes positions with Chicago Bridge and Westinghouse. General research interests focus on engineering management and related processes. Specific interests include the role of leaders and followers in the leadership process.
The Role of Personality and Gender in Performance in Science and Engineering
Science, Technology, Engineering, and Mathematics (STEM) student success is important to universities across the nation. Existing studies have examined standardized exams and high school GPA as predictors of student success; fewer studies have examined the role of personality. The present study examined whether STEM students have different personalities than the general population, whether population-level gender differences in personality were evident among STEM students, and if personality predicts academic success. The Big Five Inventory (BFI) measuring personality was given to a diverse population of students in introductory physics and calculus classes, as well as developmental mathematics (non-science track) classes, at a large eastern university. Science and engineering students showed similar personality characteristics to the general population; these characteristics were also similar to the developmental mathematics students. The difference in personality between genders was also similar to the general population. In the physics classes, the BFI facets' power to explain students' test averages and the course grades were moderated by gender. Personality facets, when combined with high school grade point average, had substantially different power to explain variance in course grades for male and female physics students. iii ACKNOWLEDGEMENTS I would first like to acknowledge my thesis advisors, Gay Stewart and John Stewart. I have thoroughly enjoyed working with both of them and have appreciated their diverse views, advice, and opinions on my research. I would not have completed this thesis without their support, encouragement, and confidence in me. I would like to thank my committee members, Edgar Fuller and Paul Miller, for agreeing to be on my committee. I would also like to thank our postdoc, Rachel Stoiko, for all the help, feedback, and cookies as I was writing up my thesis. I am also grateful to all the members of my research group, Seth DeVore, Rachel Henderson, Cabot Zabriskie, Kimberly Quedado, and Lynn Michaluk without whom this research could not have been done. Finally, I would like to acknowledge my amazing family. I would not have completed this thesis without the love, support, encouragement, smiles, and FaceTime chats from my mom and dad, Alma and Andy Miller, for their constant love and support, and for always encouraging me to pursue my interests. My sister, Claudia, for all the late nights and last minute reviews and encouraging speeches that motivated and inspired me to always be better, and kept me smiling even from a distance. Lastly, I would like to thank my friends, Brittany Johnstone, Olivia Pavlic, and Will Armentrout, for keeping me sane during graduate school. iv TABLE OF CONTENTS
2007
Engineering is design, analysis and synthesis. Analytical and systematic skills have been emphasized as one of the most important professional abilities for the XXI century. Hence, the need for instilling in engineering students those skills has been reinforced (e.g. ABET's A-K required outcomes for accreditation). But how math and engineering courses in fact promote the acquisition of those skills is still not clear. One tool developed to assess people's understanding of basic systems concepts is the systems thinking inventory, STI. The STI has been used with different populations of students in different countries. The results have consistently shown that people have poor understanding of systems concepts. We also propose for as a topic for further research that the problem might reside in the educational framework commonly used in the engineering classroom and propose that more research on the system-centered approach is needed since it requires an increased emphasis on teacher's contributions as learning facilitators. We present the results of applying two of the STI tasks, to sixty-eight Industrial Engineering undergraduate students whose level range from 4 th to last semester before graduation. It is hypothesized that students in the last semesters of IE training would have a better understanding of system dynamics. The results with controls of gender, high school of origin, and English language proficiency will be discussed.
Are we teaching our students to think systematicall y? Systems Thinking in Engineering Education
Analytical and systematic skills have been emphasized as one of the most important professional abilities for the XXI century. Hence, the need for instilling in engineering students those skills has been reinforced (e.g. ABET's A-K required outcomes for accreditation). But how math and engineering courses in fact promote the acquisition of those skills is still not clear. One tool developed to assess people's understanding of basic systems concepts is the systems thinking inventory, STI. The STI has been used with different populations of students. The results have consistently shown that people have poor understanding of systems concepts. We present the results of applying two of the STI tasks, to sixty-eight Industrial Engineering undergraduate students whose level range from 4 th to last semester before graduation. It is hypothesized that students in the last semesters of IE training would have a better understanding of system dynamics. The results with controls of gender, high school of origin, and English language proficiency will be discussed.