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Impacts of understanding conation on student satisfaction with engineering programs

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Engineering education has long sought to incorporate greater diversity into engineering programs to prepare the profession to meet the engineering challenges of society. Increasing or retaining the conative diversity of engineering programs may help extend other kinds of diversity in

Engineering education has long sought to incorporate greater diversity into engineering programs to prepare the profession to meet the engineering challenges of society. Increasing or retaining the conative diversity of engineering programs may help extend other kinds of diversity in the profession as well (Marburger, 2004). One measure of conation is the Kolbe ATM index.
Kolbe ATM is an index developed by Kathy Kolbe to measure the conative traits on an individual. The index assigns each individual a value in four categories, or Action Modes, that indicates their level of insistence on a scale of 1 to 10 in that Action Mode (Kolbe, 2004). The four Action Modes are:

• Fact Finder – handling of information or facts
• Follow Thru – need to pattern or organize
• Quick Start – management of risk or uncertainty
• Implementor – interaction with space or tangibles

The Kolbe A (TM) index assigns each individual a value that indicates their level of insistence with 1-3 representing resistant, preventing problems in a particular Action Mode; 4-6 indicating accommodation, flexibility in a particular Action Mode; and 7-10 indicating insistence in an Action Mode, initiating solutions in that Action Mode (Kolbe, 2004).

To promote retention of conative diversity, this study examines conative diversity in two engineering student populations, a predominately freshmen population at Chandler Gilbert Community College and a predominately junior population at Arizona State University. Students in both population took a survey that asked them to self-report their GPA, satisfaction with required courses in their major, Kolbe ATM conative index, and how much their conative traits help them in each of the classes on the survey. The classes in the survey included two junior level classes at ASU, Engineering Business Practices and Structural Analysis; as well as four freshmen engineering classes, Physics Lecture, Physics Lab, English Composition, and Calculus I.

This study finds that student satisfaction has no meaningful correlation with student GPA.
The study also finds that engineering programs have a dearth of resistant Fact Finders from the freshmen level on and losses resistant Follow Thrus and insistent Quick Starts as time progresses. Students whose conative indices align well with the structure of the engineering program tend to consider their conative traits helpful to them in their engineering studies. Students whose conative indices misalign with the structure of the program report that they consider their strengths less helpful to them in their engineering studies.
This study recommends further research into the relationship between satisfaction with major and conation and into perceived helpfulness of conative traits by students. Educators should continue to use Kolbe A (TM) in the classroom and perform further research on the impacts of conation on diversity in engineering programs.

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Date Created
2015-05

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Playtime, Striving, and Twitter for Homework: Facilitating Interdisciplinary Collaboration through Unconventional Methods

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This paper features analysis of interdisciplinary collaboration, based on the results from the Kolbe A™ Index of students in the Nano Ethics at Play (NEAP) class, a four week course in Spring 2015. The Kolbe A™ is a system

This paper features analysis of interdisciplinary collaboration, based on the results from the Kolbe A™ Index of students in the Nano Ethics at Play (NEAP) class, a four week course in Spring 2015. The Kolbe A™ is a system which describes the Conative Strengths of each student, or their natural drive and instinct. NEAP utilized the LEGO® SERIOUS PLAY® (LSP) method, which uses abstract LEGO models to describe answers to a proposed question in school or work environments. The models could be described piece by piece to provide clear explanations without allowing disciplinary jargon, which is why the class contained students from eleven different majors (Engineering (Civil, Biomedical, & Electrical), Business (Marketing & Supply Chain Management), Architectural Studies, Sustainability, Anthropology, Communications, Philosophy, & Psychology).

The proposed hypotheses was based on the four different Kolbe A™ strengths, or Action Modes: Fact Finder, Follow Through, Quick Start, and Implementor. Hypotheses were made about class participation and official class twitter use, using #ASUsp, for each Kolbe type. The results proved these hypotheses incorrect, indicating a lack of correlation between Kolbe A™ types and playing. The report also includes qualitative results such as Twitter Keywords and a Sentiment calculation for each week of the course. The class had many positive outcomes, including growth in the ability to collaborate by students, further understanding of how to integrate Twitter use into the classroom, and more knowledge about the effectiveness of LSP.

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Date Created
2015-12

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An Analysis of Craft Labor Productivity

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Productivity in the construction industry is an essential measure of production efficiency and economic progress, quantified by craft laborers' time spent directly adding value to a project. In order to better understand craft labor productivity as an aspect of lean

Productivity in the construction industry is an essential measure of production efficiency and economic progress, quantified by craft laborers' time spent directly adding value to a project. In order to better understand craft labor productivity as an aspect of lean construction, an activity analysis was conducted at the Arizona State University Palo Verde Main engineering dormitory construction site in December of 2016. The objective of this analysis on craft labor productivity in construction projects was to gather data regarding the efficiency of craft labor workers, make conclusions about the effects of time of day and other site-specific factors on labor productivity, as well as suggest improvements to implement in the construction process. Analysis suggests that supporting tasks, such as traveling or materials handling, constitute the majority of craft labors' efforts on the job site with the highest percentages occurring at the beginning and end of the work day. Direct work and delays were approximately equal at about 20% each hour with the highest peak occurring at lunchtime between 10:00 am and 11:00 am. The top suggestion to improve construction productivity would be to perform an extensive site utilization analysis due to the confined nature of this job site. Despite the limitations of an activity analysis to provide a complete prospective of all the factors that can affect craft labor productivity as well as the small number of days of data acquisition, this analysis provides a basic overview of the productivity at the Palo Verde Main construction site. Through this research, construction managers can more effectively generate site plans and schedules to increase labor productivity.

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Date Created
2016-12