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- 2010 Annual Conference & Exposition
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Joe Jien-Jou Lin, Purdue University; P.K. Imbrie, Purdue University; Qu Jin, Purdue University
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students in eachyear. Several modeling methodologies have been applied to develop competing predictivemodels. These methods include neural networks, logistic regression, and structural equationmodeling (SEM). These methods’ strength and weakness were studied and compared.To be presented in this poster:1) The motivation for developing Model of Student Success (MSS) in engineering.2) The structure of MSS, with various cognitive and non-cognitive factors as inputs, anddifferent measures of student success as outcomes.3) The most important cognitive and non-cognitive factors on student persistence/retentionidentified by different modeling methods.4) A comparison of modeling methods for student retention in engineering
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Elizabeth Van Ruitenbeek, University of Illinois, Urbana-Champaign
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her presentation.The three ASEE lunch seminars during the fall 2009 semester each met their maximumregistration capacity of approximately 25 participants. The limited size of the lunch meetingsfacilitated interaction between the student participants and the speaker.At the September seminar, Dr. Michael Loui (Department of Electrical and ComputerEngineering, University of Illinois) spoke on the topic “Adventures in Research on EngineeringEducation” (see Figure 1). At the October seminar, Dr. Michael Hirschi (Assistant Dean forUndergraduate Programs, College of Engineering, University of Illinois) challenged studentswith the topic “Engineering Accreditation: What is it, what good is it?” At the December lunchseminar, Dr. Charles L. Tucker III
- Conference Session
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Melanie Watson, Louisiana Tech University; Krystal Corbett, Louisiana Tech University; Kyle Prather, Louisiana Tech University; Jenna Carpenter, Louisiana Tech University; Stanley Cronk, Louisiana Tech University
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’ respective mentorships, a set of tips was generated from theadvice of experienced faculty and influential relevant works to aid other graduate studentinstructors in maximizing their effectiveness in teaching2, 3. The following is a list of the tips indecreasing order of perceived importance from faculty. 1. Focus on the students' learning of the material as opposed to the graduate student's performance as an instructor. 2. Teach the curriculum alongside a professor and use their feedback 3. Exhibit confidence to gain respect. 4. Become comfortable with content knowledge through lecture preparation, practice, and proven lesson plans. 5. Dress professionally. 6. Be comfortable with making mistakes. 7. Keep it
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Adam Melvin, North Carolina State University
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hesitating to shoot for the stars. Also, while it is a good idea tohave a #1 choice, I advocate it is better to have groups or tiers of choices, so you are notdisappointed in the scenario where you don't get your #1 choice. Getting into a few of your toptier schools, while maybe missing out on your #1 choice, can still make you feel good about thewhole application process. Since I was not precisely sure what area of research I wanted to Page 15.1163.3study, I selected a school that had the widest breath of topics with the most promising research.My selection was also strongly weighted by cordial and friendly atmosphere coupled with asincere sense of
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Austin Talley, University of Texas, Austin; Jason Albert, University of Texas, Austin
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