instructor and persistence in the class. Continued analyseswill delve further into these interesting results.SummaryThe evolution of student-student communication would seem to necessitate an evolutionin student-instructor communication. Initial results suggest that making texting availableto students may be a means by which to foster improved interactions, even if studentsgenerally are unwilling to text their instructor. Further study will be required to confirmthis conclusion and establish a downstream relationship to improved student retention.Methods and Results: Improving Student Enrollment and Retention in theUndergraduate Chemical Engineering Program at the University of RochesterE.H. Chimowitz, B. Ebenhack, J. Condit, Department of Chemical
Paper ID #11135Are Your Students Getting the Most out of the Process Simulator?Dr. Joseph A. Shaeiwitz, Auburn University Joe Shaeiwitz is a Visiting Professor of Chemical Engineering at Auburn University and an Emeritus Pro- fessor at West Virginia University. He is a co-author of ”Analysis, Synthesis, and Design of Chemical Processes,” 4th ed., published by Prentice Hall. Joe is active in ASEE, AIChE, and ABET. He co-chaired the 2012 ASEE CHE Division Summer School, is currently vice-chair of the AIChE Education and Ac- creditation Committee, has been an ABET program evaluator for over 20 years, and helps train new ABET
Paper ID #9976Results from the AIChE Education Annual Survey: Chemical EngineeringElectivesDr. Margot A Vigeant, Bucknell University Margot is a professor of chemical engineering and an associate dean of the college of engineering at Bucknell University. Her interests include conceptual learning in engineering, active, collaborative, and problem-based learning, and how the use of technology and games can engage students.Dr. David L. Silverstein P.E., University of Kentucky David L. Silverstein is the PJC Engineering Professor of Chemical Engineering at the University of Ken- tucky. He is also the Director of the College of
the survey was voluntary. Fourteen students participated in the pre-testand ten students participated in the post-test, out of an enrollment of fifteen students. Thequestions on the survey and survey results are summarized below. The first five questionscame from the tenth national report card survey on energy knowledge13.1. How is most electricity in the United States generated? Is it… a. By burning oil, coal, and wood Correct Answer; Pretest 71%, Posttest 100% b. With nuclear power Pretest 14%, Posttest 0% c. Through solar energy, or Pretest 0%, Posttest 0% d. At hydro electric power plants? Pretest 14%, Posttest 0% e. Don’t know Pretest 0%, Posttest
particular interest. We asked about what teaching methodsand classrooms are used. A condensed version of the survey is given in Appendix B. Responseswere not forced for questions, so some institutions chose not to answer certain questions. Otherquestions were conditional upon answers to previous questions and were not shown to allrespondents.Relevant Statistics of Responding InstitutionsEighty-two responses from 80 distinct institutions are reported on in this paper. Two universitieswere Canadian with the rest from the United States. Seventy-three institutions use semesters,eight use quarters, and one chose “other” and gave a description as a co-op program with aquarter timeline. The distribution of average graduation rates over the past three years
Paper ID #33339Using Existing University Resources: Integration of the UniversityWriting Center into a Senior-level Laboratory Series for ImprovedLearning OutcomesProf. Stephanie G. Wettstein, Montana State University - Bozeman Stephanie Wettstein is an Associate Professor in the Chemical and Biological Engineering department at Montana State University in Bozeman, MT. She is associated with MEERC and has been the faculty advisor of the MSU SWE chapter since 2013.Dr. Jennifer R. Brown, Montana State University - Bozeman Jennifer Brown is an Associate Professor in the Chemical and Biological Engineering Department at Montana
Paper ID #34342Work in Progress: Modeling the Effect of Hematocrit on Blood CellSeparations Using a Hands-on Learning Device and Microbead Blood Simu-lantKitana Kaiphanliam, Washington State University Kitana Kaiphanliam is a doctoral candidate in the Voiland School of Chemical Engineering and Bio- engineering at Washington State University (WSU). Her research focuses include miniaturized, hands-on learning modules for engineering education and bioreactor design for T cell manufacturing. She has been working with Prof. Bernard Van Wie on the Educating Diverse Undergraduate Communities with Affordable Transport Equipment
students. She was selected as a UIC Teaching Scholar for Spring 2017, named as an American Institute of Chemical Engineers (AIChE) ”35 under 35” winner in the education category for 2017 and named as American Society for Engineering Education (ASEE) ”20 under 40” awardee for 2018.Prof. James W. Pellegrino, The University of Illinois at Chicago James W. Pellegrino is Liberal Arts and Sciences Distinguished Professor and Founding Co-director of the Learning Sciences Research Institute at the University of Illinois at Chicago. His research and devel- opment interests focus on children’s and adult’s thinking and learning and the implications of cognitive research and theory for assessment and instructional practice. He
Paper ID #25324Using or Viewing a Demonstration of Inquiry-Based Computer Simulations:The Effectiveness of Both in Learning Difficult Concepts in Heat TransferDr. Katharyn E. K. Nottis, Bucknell University Dr. Nottis is an Educational Psychologist and Professor Emeritus of Education at Bucknell University. Her research has focused on meaningful learning in science and engineering education, approached from the perspective of Human Constructivism. She has authored several publications and given numerous presentations on the generation of analogies, misconceptions, and facilitating learning in science and engineering
Paper ID #22308Work in Progress: Assessment of Google Docs and Drive for Enhanced Com-munication and Data Dissemination in a Unit Operations LaboratoryDr. Christopher James Barr, University of Michigan Dr. Christopher Barr is the Instructional Laboratory Supervisor in the Chemical Engineering Department at University of Michigan. He obtained his Ph.D. at University of Toledo in 2013 and is a former Fellow in the N.S.F. GK-12 grant ”Graduate Teaching Fellows in STEM High School Education: An Environmen- tal Science Learning Community at the Land-Lake Ecosystem Interface”. His main responsibilities are supervising and
Paper ID #29382Student Confidence and Metacognitive Reflection with Correlations toExam Performance in a FE Review Course in Chemical EngineeringSheima J. Khatib, Texas Tech University Sheima J. Khatib is an Assistant Professor in the Department of Chemical Engineering at Texas Tech University. She received her Ph.D. in Chemistry in the area of heterogeneous catalysis from the Au- tonomous University of Madrid. Apart from her interests in chemical engineering and finding sustainable paths for production of fuels and chemicals (for we she has received several grants including the NSF CAREER award), she is passionate
AC 2007-2972: COMPARING STUDENT EXPERIENCES AND GROWTH IN ACOOPERATIVE, HANDS-ON, ACTIVE, PROBLEM BASED LEARNINGENVIRONMENT TO AN ACTIVE, PROBLEM-BASED ENVIRONMENT.Paul Golter, Washington State UniversityBernard Van Wie, Washginton State UniversityGary Brown, Washington State University Page 12.381.1© American Society for Engineering Education, 2007AbstractTwo questions that frequently come up when developing a teaching method that tries to combine bestpractices from multiple pedagogies are: Is this better than how we normally teach? And whichpedagogy is giving the most benefit. In the spring semester of 2006 we had a large enough junior classto separate our required Fluid
Paper ID #14740How We Teach Process Control: 2015 Survey ResultsDr. David L. Silverstein P.E., University of Kentucky David L. Silverstein is a Professor of Chemical Engineering at the University of Kentucky. He is also the Director of the College of Engineering’s Extended Campus Programs in Paducah, Kentucky, where he has taught for 15 years. His PhD and MS studies in ChE were completed at Vanderbilt University, and his BSChE at the University of Alabama. Silverstein’s research interests include conceptual learning tools and training, and he has particular interests in faculty development. He is the recipient of several
Paper ID #26429Work in Progress: Improving Critical Thinking and Technical Understand-ing as Measured in Technical Writing by Means of I-depth Oral Discussionin a Large Laboratory ClassDr. Mechteld Veltman Hillsley, Pennsylvania State University, University Park Dr. Hillsley is an Associate Teaching Professor in the Department of Chemical Engineering at Pennsylva- nia State University. She received a BS in Chemical Engineering from Virginia Tech in 1988 and an MS and PhD from Penn State in 1990 and 1994, respectively. Dr. Hillsley spent approximately 10 years doing research at Penn State on fluid shear stress effects on
Paper ID #15599Impacts of Engineering Engagement Activities for First-Year StudentsJacqueline K Burgher, Washington State University Jacqueline Burgher is a PhD Candidate at Washington State University in the Voiland School of Chemical and Biological Engineering. She received her bachelor’s degree from Anderson University, worked in industry, received an MBA from Anderson University and is currently working with Prof. Bernard J. Van Wie on fabricating, optimizing, and implementing a miniaturized gasification system for use in the engineering classroom.Prof. Bernard J. Van Wie, Washington State University Prof. Bernard
Paper ID #14724Hands-on, Screens-on, and Brains-on Activities for Important Concepts inHeat TransferDr. Margot A Vigeant, Bucknell University Margot Vigeant is a professor of chemical engineering and an associate dean of engineering at Bucknell University. She earned her B.S. in chemical engineering from Cornell University, and her M.S. and Ph.D., also in chemical engineering, from the University of Virginia. Her primary research focus is on engineering pedagogy at the undergraduate level. She is particularly interested in the teaching and learning of concepts related to thermodynamics. She is also interested in active
Paper ID #22947How We teach: Unit Operations LaboratoryDr. Margot A. Vigeant, Bucknell University Margot Vigeant is a professor of chemical engineering at Bucknell University. She earned her B.S. in chemical engineering from Cornell University, and her M.S. and Ph.D., also in chemical engineering, from the University of Virginia. Her primary research focus is on engineering pedagogy at the undergraduate level. She is particularly interested in the teaching and learning of concepts related to thermodynamics. She is also interested in active, collaborative, and problem-based learning, and in the ways hands-on activities
Paper ID #21146Work in Progress: Content Validation of an Engineering Process Safety Decision-making Instrument (EPSRI)Brittany Lynn ButlerDr. Daniel D. Anastasio, Rose-Hulman Institute of Technology Daniel Anastasio is an assistant professor at Rose-Hulman Institute of Technology. He received a B.S. and Ph.D. in Chemical Engineering from the University of Connecticut in 2009 and 2015, respectively. His primary areas of research are game-based learning in engineering courses and membrane separations for desalination and water purification.Prof. Daniel D. Burkey, University of Connecticut Daniel Burkey is the Associate
Paper ID #25970How We Teach: ThermodynamicsDr. Margot A Vigeant, Bucknell University Margot Vigeant is a professor of chemical engineering at Bucknell University. She earned her B.S. in chemical engineering from Cornell University, and her M.S. and Ph.D., also in chemical engineering, from the University of Virginia. Her primary research focus is on engineering pedagogy at the undergraduate level. She is particularly interested in the teaching and learning of concepts related to thermodynamics. She is also interested in active, collaborative, and problem-based learning, and in the ways hands-on activities such as making
AC 2011-1921: POSTER SESSION FOR TENURE TRACK FACULTYDonald P. Visco, Tennessee Technological UniversityJason M. Keith, Michigan Technological University Jason Keith is an Associate Professor of Chemical Engineering at Michigan Technological University.Dr. Jeffrey A Nason, Oregon State UniversityRoger C. Lo, Department of Chemical Engineering, California State University, Long Beach Roger C. Lo is an Assistant Professor of Chemical Engineering at California State University, Long Beach. He received his PhD from Texas A&M University in May 2008. Roger teaches undergraduate and grad- uate required courses (fluids, math, and transport phenomena) and also numerical analysis using Excel and MATLAB for chemical
approach used in class is to start with configurations of simple distillation columns (one feedstream and two product streams), and then progress to more complex column arrangements.Specifically, distillation column sequences with simple distillation columns are presented as amethod for separating ternary mixtures. This is a base case scenario shows how two or threecolumns may be sequenced to separate three compounds, as shown in Figure 1a. In this casethere is no thermal coupling between the columns, and each column has a reboiler and acondenser. A A, B A
) draw chemical processdiagrams of a given material and energy balance problem, (b) develop accompanyingsystems of equations, and (c) solve for the unknowns. Students were told that we wereinterested in how they approached the solution to the problem rather than the solutionitself. They were encouraged to discuss their approach so that we could follow their logicas the solution was developed. Our review of the recordings made it clear that there was one area in which all ofthe groups had difficulties: translating the problem statement into a process flow diagram(PFD) and then translating the PFD to a set of mathematical expressions. None of thegroups was able to put together a correct process flow diagram. Without a correctprocess flow
variables on a singlemeasured dependent variable. This dependent variable can be catalyst productivity, income,blood pressure or any similar quantitative property. DOE (also known as experimental design) isa structured approach used to establish and quantify causality relationships between independentvariables (factors), as well as their interaction effects, and the outcome of an experiment. TheDOE approach can be applied broadly to many fields outside of engineering, including finance,health and social sciences9.To illustrate the DOE method, suppose that you are planning a series of experiments thatinvestigate the effect of three independent variables (A, B and C) on a measured response (Y). Afirst impression may be to vary each of A, B and C one
publication.Table 1. Pre- / Post Assessment Test for Energy Module1) Modern spark ignition internal combustion engines are based on which one of the following thermodynamic cycles:a) Diesel Cycle b) Rankine Cycle c) Otto Cycle d) Carnot Cycle e) Stirling Cycle2) Modern compression ignition internal combustion engines are based on which one of the following thermodynamic cycles:a) Diesel Cycle b) Rankine Cycle c) Otto Cycle d) Carnot Cycle e) Stirling Cycle3) The amount of energy potentially liberated from a fuel by combustion is known as the:a) Energy Index b) Octane Number c) Heating Value d) Fuel Index e) Cetane number Number4) Which of the following step might be
(using a cubic B-spline algorithm implemented via VisualBasic for Applications, or VBA) and then drawing the McCabe-Thiele diagram in MicrosoftExcel. In this way, the effect of changes to the operating conditions can be easily demonstrated.Furthermore, the method will locate the azeotrope if the system has one.The goals of this paper are to provide instructors a quick, automated method of generating aMcCabe-Thiele diagram for a nonideal binary system to facilitate classroom instruction, to aidstudents in learning about and manipulating these diagrams, and to demonstrate how to integrateVBA calculations (including the cubic B-splines) into an Excel worksheet.NotationVariable Definitiona,b,c,d Cubic equation coefficientsA The
whom they have regular academic or social interaction. The end-of-yearquestionnaire also provided space for any qualitative feedback regarding the peer mentoringprogram.For comparative purposes, two groups served as control to the mentees participating in the peermentoring program. Control group A comprised of the ten concurrent sophomore students whoopted not to participate in the program. Control group B comprised of students who weresophomores in the year prior to the establishment of the peer mentoring program. Assessment ofgroup A occurred concurrently with that of the mentees. Assessment of group B occurred in theprevious year.ResultsThe self-perceived interaction levels of the mentees and the control groups are tabulated in tables1a and
required to solve the problem. b) Identify the process type (batch, semi-batch, or continuous). The system is defined as the fluid reservoir. Therefore, this is a semi-batch process, since mass will leave the system but no mass enters the system. c) Use various resources to obtain the molecular weight, density, heat capacity, normal boiling point, and heat of vaporization for the two components in the liquid reservoir. Data obtained from webbook.nist.gov unless otherwise noted Molecular Weight Glycerol (A) = C3H8O3, MWA = 92 g/mol Propylene glycol (B) = C3H8O2, MWB = 76 g/mol Density ρA = 1.261 (g/cm3) (source: Properties of Gases and Liquids, 4th ed. Reid, Prausnitz, and Poling) ρB = 1.036 (g
from engineering,chemistry, and biology) from various levels including freshmen through seniors (n=10). Thesestudents filled out surveys both before (“Group A : Before”) and after (“Group A : After”)performing the experiment. The second group, Group B are the engineers in the originalThermodynamics class who were surveyed approximately 9 months after having completed theexperiment (n=6). Responses from selected questions are included below. For free answerquestions, answers were categorized. Therefore, the data below represents aggregate data, notquoted responses.The first two questions were to define heat and temperature. All students correctly respondedthat temperature was a property of the material that represented the energy contained
into a beaker or clearcontainer, add several tablespoons of cornmeal, and a few drops of food dye to the water. Askthe students if they would drink the water now (hopefully not). Show images of dirty watersources. Ask the students if they would drink water from any of those sources. Explain that inthis country assumptions are made about the purity of our drinking water, but many peoplearound the world do not have that luxury. Figure 2: Illustrations to define a) filtration and b) pores.Ask the students if they know of any places where filters are used (pools, oil and water filters incars, vacuum cleaners, coffee makers, fish tanks). Have them list at least three filters. Explainthat engineers and scientists have found ways
engaged learning style preferencesacross the Felder-Silverman dimensions.With these observations, we became more interested in variability in student performance acrossdifferent sections of material balances, and whether faculty with “low performing” sectionsshared any similar features in their exams.Data on final grades were gathered for six faculty (aforementioned Faculty A through F) overfive semesters (Spring 2013, Fall 2013, Spring 2014, Fall 2014, and Spring 2015). Faculty B, C,and D taught the course twice in this time period, whereas Faculty A, E, and F each taught thecourse once. There is no statistically significant difference in final grade mean between FacultyA, B, C, and F. Faculty D adjusted raw scores up at the end of term for both