More Like this

1. The Relationship between Incentives, Views on Leadership and Socioeconomic Factors, and Associated Impacts Regarding a University Students' Leadership Training Program

   Tackie, David N; Henry, Findlay J; Jimmeh, Joe B; Gogo-Kumi, N (August 2024, International journal of economics commerce and management)

   Christopher, M; Sharma, P (Ed.)

   University students’ leadership training programs have different dimensions, and they may be impacted by several factors. Yet, relatively few studies have been conducted on this issue. This study, therefore, examined the relationships and impacts of specific factors regarding a university students’ leadership training program. Data were collected using a questionnaire and analyzed using descriptive statistics, including correlation, and regression analysis. Considering the study participants, there were more females than males; more sophomores relative to other class classifications, and more participants intended to hold a college leadership position than otherwise. Furthermore, on the views on leadership, a very high proportion of the participants strongly disagreed or disagreed that leadership in an organization or a community is over-hyped (View 1), and an even higher proportion of participants strongly agreed or agreed that leadership in an organization or a community is needed depending on the type of entity (View 2). The regression results revealed that for model 1, gender, age, and incentive classification had statistically significant effects on View 1, and for model 2, none of the factors had a statistically significant effect on View 2. However, a revised version of model 2 showed that incentive classification was statistically significant. It may be that gender, age, and incentive classification are important factors in students’ views on leadership. 

   more » « less
2. Computational Thinking in the Formation of Engineers (Year 1)

   Mendoza Diaz, N. V. (July 2021, 2021 ASEE Virtual Annual Conference)

   Computational thinking is an important skill in the formation of engineers. Many schools of engineering include a programming course during the first-year. In 2019, NSF funded the “Collaborative Research: Research in Improving Computational Thinking in the Formation of Engineers, a Multi-Institutional Initiative.” The project’s goal is to improve the way computational thinking is taught at the college engineering level via the understanding of the multiple factors that affect computational thinking development. The project’s research questions are: · Research Question 1: How does the integration of computing into the foundational engineering courses affect the formation of engineers? · Research Question 2: In what ways do social identities (e.g. gender, ethnicity, first generation college attending, socioeconomic status), choices (e.g. major, transfer status), and other factors impact the engineering student experience with computational thinking? · Research Question 3: In what ways do computational thinking skills develop over time in engineering students? In order to respond to these questions, the research team developed a Computational Thinking Hybrid Framework, an Engineering Computational Thinking Diagnostic (ECTD) and a Position of Stress Questionnaire. Amid COVID-19, the advances of the project include approximately 2000 participants responding to the diagnostic during the Fall of 2019 and the Fall of 2020. With this participation, two cycles of validation have taken place for the ECTD and results are presented in this poster session. The factors validated in this diagnostic are (1) Abstraction, (2) Algorithmic Thinking and Programming, (3) Data Representation, Organization, and Analysis, (4) Decomposition, and (5) Impact of Computing. The positions of stress have been collected for the Fall of 2020 and preliminary results are also presented in this session. 

   more » « less
3. A Preliminary Analysis of the Effects of Soft Skills on the Perceived Leadership Styles of College Students

   Tackie, David N; Henry, Findlay J; Jimmeh, Joe B; Gogo-Kumi, N (March 2024, International journal of economics commerce and management)

   Christopher, M; Sharma, P (Ed.)

   Soft skills are important to leadership and leadership styles; however, there are limited studies on how soft skills affect the perceived leadership styles of college students. Therefore, the study assessed the effects of soft skills on the perceived leadership styles of college students. The data were collected from a purposive sample of college students in a leadership training program. Data was analyzed using descriptive statistics and multiple regression analysis. The results show that the most dominant leadership styles were, telling, selling, and delegating. Regarding the selected soft skills vis-à-vis what participants would do in scenarios, there were four high combined “most likely” and “likely” responses, 70% or above for communication: particularly, for active listening, conflict resolution, writing a letter, and public speaking. For problem-solving, all five combined “most likely” and “likely” responses, were high, above 70% for creative skills, research and consult, consensus solutions, decision-making skills, and critical thinking skills. Furthermore, for work ethic, there were four high combined “most likely” and “likely” responses, above 60% for correcting an oversight, doting “is” and crossing “ts”, doing a task methodically, and completing a task on time. Additionally, the results of the multiple regression showed that the problem-solving soft skills, overall, dominated the composite leadership style. Therefore, problem-solving may be a critical soft skill that affects leadership styles. 

   more » « less
4. Prevalent Technical Leadership Styles and Impact on Early Engineering Careers

   Eigelberger, C.; Henson, H. (April 2021, The Technology Interface)

   In this study, the authors explored prevalent leadership styles found in industry from an engineering student’s internship experiences. Over four years of internships, observations and interview responses were recorded to address three questions: What is the dominant industrial leadership style? What is the dominant leadership style in the broader engineering sector? What is the dominant leadership style entry-level engineers should know to be successful? Reflections on personal experiences within the engineering industry suggest an ideal leadership style that an entry-level engineer or a similar technical individual can utilize. Previous research on leadership and success formed a basis for claims as to which leadership techniques can lead to success for an entry-level engineer. Further, this study builds upon prior research on the correlations between leadership skills taught in college and the resulting success beyond the classroom. Leadership styles are ranked in order of their utilization in industry with a corresponding value for entry-level engineers. They are: pacesetting, authoritative, democratic, coaching, and delegating. From the study, the authors concluded by suggesting that there is a correlation between knowledge in leadership for both subjective and objective success of entry-level engineers. Ideally, every engineer should be taught a multitude of techniques, and recommendations are that engineers should strive to learn many leadership styles, whether they intend to hold a position of leadership or not. 

   more » « less
5. Work in Progress: Assessment of Reflective Thinking in Graduate Engineering Students: Human and Machine Methods

   Taraban, R.; Isserman, M.; Pittman, J.C.; Yeo, N.; Campbell, R.C.; Kim, J.H.; Reible, D.D. (July 2021, 2021 ASEE Annual Conference Proceedings)

   Engineering education is increasingly looking to the liberal arts to broaden and diversify preparation of students for professional careers. The present study involves an elective graduate environmental engineering course that incorporated the arts and humanities. The goal of the course was to develop engineers and technical professionals who would become both more appreciative of and better equipped to address technical, ethical, social, and cultural challenges in engineering through the development of critical and reflective thinking skills and reflective practice in their professional work. A reflective writing assignment was submitted by students following each of fourteen course topics in response to the following question: Reflect on how you might want to apply what you learned to your development as a professional and/or to your daily life. Student responses were classified by human coders using qualitative text analytic methods and their classifications were attempted to be learned by a simple machine classifier. The goal of this analysis was to identify and quantify students’ reflections on prospective behaviors that emerged through participation in the course. The analysis indicated that the primary focus of students’ responses was self-improvement, with additional themes involving reflection, teamwork, and improving the world. The results provide a glimpse into how broadening and diversifying the curriculum might shape students’ thinking in directions that are more considerate of their contributions to their profession and society. In the discussion, we consider the findings from the human and machine assessments and suggest how incorporating AI machine methods into engineering provides new possibilities for engineering pedagogy. 

   more » « less