Why They Leave: Understanding Student Attrition from Engineering Majors

A large number of students leave engineering majors prior to graduation despite efforts to increase retention rates. To improve retention rates in engineering programs, the reasons why students leave engineering must be determined. In this paper, we review the literature on attrition from engineering programs to identify the breadth of factors that contribute to students’ decisions to leave. Fifty studies on student attrition from engineering programs were included in the primary part of this literature review. In the second half of the work, an additional twenty-five studies that focused on methods of increasing student retention, were examined. Six broad factors driving students to leave engineering were identified by examining the attrition literature: classroom and academic climate, grades and conceptual understanding, self-efficacy and self-confidence, high school preparation, interest and career goals, and race and gender. Evidence from the retention studies suggests that successful efforts to increase retention act on one or more of these factors. A clear gap in the literature is that of economics: the costs associated with losing students, and the costs associated with implementing retention strategies, are virtually unmentioned

A Coarse Techno-Economic Model of a Combined Fermentation-Catalysis Route to Sorbic Acid

The conversion of biomass into bulk chemicals provides the potential for multiple environmental and economic benefits. While current research in industrial biotechnology focuses primarily on biocatalysts, a significant opportunity exists when combining biological and chemical catalysis into one process train. This hybrid process approach will potentially produce a wide array of economically viable molecules. One test-case of this hybrid approach is the production of sorbic acid via biocatalytic conversion of glucose to 4-Hydroxy-6-methyl-2-pyrone (HMP), followed by catalytic conversion of HMP to sorbic acid. Current collaborative research has developed this process to the stage where gram-quantities of biologically-produced HMP have been delivered to catalysis to produce butyl sorbate (a hydrolysis step can then take this to sorbic acid). Although the final process details needed for a detailed technoeconomic analyses are several years away, it is desirable to understand a coarse structure of the economics of such a process. Such an understanding can provide insight into opportunities for process improvement, as well as into fundamental technoeconomic limitations of the approach. To this end, we have developed a spreadsheet-based model of this hybrid process and have estimated the sorbic acid production cost from the process, which are then compared to current wholesale prices. We also report results of a comprehensive sensitivity analysis to demonstrate potential process improvements

Detecting and categorizing hard-coding errors in Excel Spreadsheets using Visual Basic for Applications (VBA)

Electronic spreadsheets play an indispensable role in the simulation, modeling, and analysis of bioenergy systems, and their results have the ability to affect decision-making significantly. Prior research has shown that spreadsheets are highly error-prone, and that a large percentage of these errors are difficult to detect. To that end, we developed computer code (implemented in Visual Basic for Applications, running under Microsoft Excel) to detect a particularly insidious form of spreadsheet error: the hard-coding error. These errors are defined as the presence of one or more unreferenced numerical values in a cell formula. Hard-coding errors are dangerous because they are a likely source of erroneous constants and/or non-updating assumptions. The code was used to audit six spreadsheets relevant to bioenergy systems, three developed in our lab (and reported on in other sessions at the AIM), and three in the public domain. The preliminary audit results were analyzed to understand the nature and distribution of hard-coding errors. The preponderance and diversity of hard-coding errors in these spreadsheets motivated us to subcategorize them. Together, the hard-coding error detection program and sub-categorization program provide a robust and rapid means of detecting and categorizing multiple types of hard-coding errors. Use of these programs could increase the reliability of spreadsheet software used in simulation, modeling, and analysis of bioenergy systems

Detecting Insect Flight Sounds in the Field: Implications for Acoustical Counting of Mosquitoes

A prototype field-deployable acoustic insect flight detector was constructed from a noise-canceling microphone coupled to an off-the-shelf digital sound recorder capable of 10 h recordings. The system was placed in an urban forest setting 25 times over the course of the summer of 2004, collecting 250 h of ambient sound recordings that were downloaded to a personal computer and used to develop detection routines. These detection routines operated on short segments of sound (0.093 s, corresponding to 4096 samples at 44100 Hz). A variety of approaches were implemented to detect insect flight tones. Simple approaches, involving sensing the fundamental frequency (1st harmonic) and 2nd harmonic, were capable of detecting insects, but generated large numbers of false positives because of other ambient sounds including human voices, birds, frogs, automobiles, aircraft, sirens, and trains. In contrast, combining information from the first four harmonics, from the interharmonic regions, and from the sound envelope, reduced false positives greatly. Specifically, in the 250 h of recordings, 726 clear insect buzzes were detected by the final algorithm, with only 52 false positives (6.5%). Running the final algorithm with all criteria liberalized by 20% increased the number of clear insect buzzes by 8%, to 784, but increased false positives to 471 (28% of total detections). The potential of using this approach for detecting mosquito activity using low-cost sensors is discussed

Under the ASABE Umbrella — Engineering Degree Programs Need Curriculum Reform

The first-ever issue of Transactions of the ASAE, published in 1907, opens with a talk given by Howard W. Riley (after whom Riley-Robb Hall at Cornell University would later be named) that\u27s modestly titled The Courses in Agricultural Engineering that Should be Offered. Responses from several other luminaries, including J. B. Davidson (after whom Davidson Hall at Iowa State University would later be named), are included and make for fascinating reading for any student or practitioner of our discipline

Technical Note: Detecting and Subcategorizing Hard-coding Errors in Bioenergy-relevant Spreadsheets Using Visual Basic for Applications (VBA)

Electronic spreadsheets play an indispensable role in the simulation, modeling, and analysis of bioenergy systems, and their results have the ability to affect decision-making significantly. Prior research has shown that spreadsheets are highly error-prone, and that a large percentage of these errors are difficult to detect. To that end, we developed computer code (implemented in Visual Basic for Applications, running under Microsoft Excel) to detect a particularly insidious form of spreadsheet error: the hard-coding error. These errors are defined as the presence of one or more unreferenced numerical values in a cell formula. The code was used to audit six engineering spreadsheets relevant to bioenergy systems, three developed in our lab (and reported on in other sessions at the AIM), and three in the public domain. The preliminary audit results were analyzed to understand the nature and distribution of hard-coding errors. The preponderance and diversity of hard-coding errors in these spreadsheets motivated us to subcategorize them. Together, the hard-coding error detection program and sub-categorization program provide a robust and rapid means of detecting and categorizing multiple types of hard-coding errors. Use of these programs could increase the reliability of spreadsheet software used in simulation, modeling, and analysis of bioenergy systems

Student Perspectives on a New Biomass Production Module for Fundamentals of Biorenewable Resources

In 2007, a USDA Higher Education Challenge Grant funded the creation of a Virtual Education Center (VEC) for Biorenewable Resources at three partner land-grant institutions. Three new courses are taught through the VEC, each using multiple instructors and exchanges of video lectures between sites. The most heavily subscribed of these is a graduate survey type course entitled Fundamentals of Biorenewable Resources. In this paper, we report on student survey results for the biomass production module, which covered the production of corn, soybean, hay and forage, and short rotation woody crops, as well as biotechnology basics. The survey was administered using WebCT and SurveyMonkey in spring 2010. The survey instrument gathered student perspectives on the module content and delivery, and student learning. Quantitative and qualitative data were collected and analyzed

Conceptual and Mathematical Models of Batch Simultaneous Saccharification and Fermentation: Dimensionless Groups for Predicting Process Dynamics

This paper describes a modeling effort demonstrating that dimensionless groupings of classical process parameters can be used to predicting process dynamics of batch simultaneous saccharification and fermentation (SSF) processes. Michaelis–Menten enzyme kinetics and Monod growth kinetics were employed, and inhibition of enzyme action and inhibition of microbial growth were neglected. The SSF process was characterized by the relative durations of three phases: A microbially-limited phase, a hydrolysis-limited phase, and a monosaccharide-depletion phase. The duration of these three phases were interrelated, and well predicted by the dimensionless magnitude of the monosaccharide peak (MSP). Thus, the MSP could be used as a single-value descriptor of an SSF process. The dimensionless ratio of the initial hydrolysis rate to the initial substrate consumption rate was shown to predict MSP, and an overall system time constant was shown to predict the total run time of a batch SSF process

Differing Effects of Glycerin on Anaerobic Co-digestion of Mixed Substrates in Bench-Scale Assays and Sub Pilot-Scale Reactors

Bench-scale methods such as Biochemical Methane Potential (BMP) assays and Anaerobic Toxicity Assays (ATAs) are useful tools in evaluating potential feedstocks for anaerobic digestion. The BMP method provides a preliminary indication of substrate biodegradability and methane production, while the ATAs provide an indication of substrate toxicity to anaerobic microbial consortia. Previous research using small (\u3c20 \u3eL) reactors indicated that co-digestion of manures with small amounts of glycerin (ca. 1 – 2 %) can double methane production, but toxicity can result if glycerin exceeds 2% (volumetric basis). This paper investigated the relationship between bench-scale methods (BMPs and ATAs) and sub pilot-scale digester results, using glycerin as a test substrate mixed with a baseline feedstock (beef manure, corn processing wastewater, lagoon liquid, and short-fiber cardboard). The batch-fed, stirred ATAs indicated that glycerin was toxic to methane production at all inclusion levels. The batch-fed, stirred BMPs indicated no significant difference between methane production in the 0.0%to 4.0% addition levels; however at 8.0% addition, methane production tripled. The continuously fed, non-stirred, plug-flow sub pilot-scale reactors indicated toxicity effects in the 2.0% and 4.0% glycerin mixtures and no difference from the control in the 1.0% glycerin mixture. These results demonstrate the variations in scale performance of glycerin as a co-substrate and identify some serious challenges in extrapolating bench-scale assays to large-scale performance of mixed-waste anaerobic digestion systems

Comparison of Methane Production from Bench- and Sub Pilot-Scale Anaerobic Digesters

Design and construction of full-scale anaerobic digesters that co-digest manure with other substrates, such as food processing wastes, is challenging because of the large number of potential mixtures that can be fed to the digester. In this work we examine the relationship between results from bench-scale methods such as biochemical methane potential assays (BMPs) and sub pilot-scale reactors. The baseline feedstock for this study was beef manure from concrete feedlot pens (open and covered) in eastern Iowa. Additional co-digestion substrates tested were short-fiber cardboard, corn processing wastewater, enzyme processing wastewater and lagoon liquid. Substrates were characterized for total solids (TS), volatile solids (VS), chemical oxygen demand (COD), pH, alkalinity, and ammonia, after which BMPs were conducted on all substrates. Based on the BMP and anaerobic toxicity assay (ATA) results, a mixture was created and evaluated using BMPs and tested in 100-L sub pilot-scale reactors. This study showed that results from BMPs of feedstock co-digestion mixtures accurately estimated the range of methane produced from three 100-L, plug flow reactors