Margie and Bill Klesse College of Engineering and Integrated Design Faculty Research

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12588/829

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    Experiences in Delivering Online CS Teacher Professional Development
    (Association for Computing Machinery, 2024-03-07) Wilde, Jina; Beltran, Emiliano; Zawatski, Michael J.; Fernandez, Amanda S.; Prasad, Priya V.; Yuen, Timothy T.
    This paper describes our team's experience in designing and delivering the online teacher professional development (PD) program, Computer Science for San Antonio (CS4SA), aimed at empowering educators with computer science (CS) knowledge to increase Latinx participation in CS and STEM education within a large, urban predominantly Latinx school district in South Texas. This paper highlights the successes, challenges, and lessons learned while facilitating two cohorts of the CS PD through online platforms during the COVID-19 pandemic. As a result of this program, participants recognized the importance of integrating CS into their classroom and becoming advocates for the discipline at the high school level. Additionally, teachers, investigators, and other personnel learned important lessons for enhancing the program's impact through collaboration with district administrators and refinement of the online learning experience.
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    Combined Emission Economic Dispatch using Quantum-inspired Particle Swarm Optimization and its Variants
    (SAGE Publications, 2024-03-19) Asif, Muhammad; Amin, Adil; Jamil, Umar; Mahmood, Anzar; Ahmed, Ubaid; Razzaq, Sohail; Mahdi, Fahad Parvez
    The ever-increasing electricity demand, its dependency on fossil fuels, and the consequent environmental degradation are major concerns of this era. The worldwide domination of fossil fuels in bulk electricity generation is rapidly increasing the emissions of CO2 and other environmentally dangerous gases that are contributing to climate change. The economic and emission dispatch are two important problems in thermal power generation whose combination produces a complex highly constrained nonlinear optimization problem known as combined economic and emission dispatch. The optimization of combined economic and emission dispatch aims to allocate the generation of committed units to minimize fuel cost and emissions, simultaneously while honoring all equality and inequality constraints. Therefore, in this article, we investigate a solution of the combined economic and emission dispatch problem using quantum particle swarm optimization and its two modified versions, that is, enhanced quantum particle swarm optimization and quantum particle swarm optimization integrated with weighted mean personal best and adaptive local attractor. The enhanced quantum particle swarm optimization algorithm achieves particles’ diversification at early stages and shows good performance in local search at later stages. The quantum particle swarm optimization integrated with weighted mean personal best and adaptive local attractor boosts search performance of quantum particle swarm optimization and attains better global optimality. The suggested methods are employed to achieve solution for the combined economic and emission dispatch in four distinct systems, encompassing two scenarios with 6 units each, one with a 10-unit configuration, and another with an 11-unit setup. A comparative analysis with methodologies documented in existing literature reveals that the proposed approach outperforms others, demonstrating superior computational performance and robust efficiency.
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    Housing perceptions and code enforcement: An assessment of demolition orders using street view imagery and machine intelligence
    (SAGE Publications, 2024-03-04) López Ochoa, Esteban A.; Zhai, Wei
    The rapid growth of U.S. Sunbelt cities has intensified urban development pressures. Low-income housing demolitions are a result of such pressures as they are “low hanging fruit” for urban renewal, which can be further intensified by housing quality perceptions. By combining deep learning on Street View images (STV) with machine learning, we provide a model that accurately predicts demolition orders and allows assessing the heterogeneity of these predictions depending on the evaluator’s perceptions. Based on fast-growing San Antonio (TX) data, our results show that automated models can be useful to assess human perception biases of code enforcers.
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    Bridges Consumption Analysis for Oversize and Overweight Vehicles on Texas Roads
    (SAGE Publications, 2024-03-28) Weissmann, Jose; Weissmann, Angela J.; Inoue, Danilo Keniti Nais; Prozzi, Jorge A.
    Transportation infrastructure in Texas, U.S., particularly its extensive bridge network, plays a vital role in supporting economic growth and ensuring safe and efficient mobility. With over 57,000 bridges, including more than 22,000 culverts, Texas faces the challenge of maintaining its infrastructure while dealing with limited funding resources. This paper presents the findings of a study conducted for the Texas Department of Transportation that focused on assessing the costs associated with bridge consumption by oversize and overweight (OS/OW) vehicles. The study aimed to calculate bridge consumption costs per mile for different OS/OW categories, considering factors such as axle load, spacing, bridge design life, and vehicle miles traveled (VMT). These consumption costs were calculated by analyzing traffic data and bridge inventory ratings. The results showed that, although OS/OW vehicles are responsible for the majority of the bridge consumption costs per mile, their lower VMT, relative to regular commercial vehicles, mitigates their influence on total bridge consumption costs to less than 15% of the total. The findings of this study can contribute to the ongoing efforts of transportation engineers and policymakers in addressing funding deficits and developing strategies to sustain the state’s bridge infrastructure.
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    Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines
    (Association for Computing Machinery, 2023-08-28) Helfer, Peter; Teeter, Corinne; Hill, Aaron; Vineyard, Craig M.; Aimone, James B.; Kudithipudi, Dhireesha
    Memory storage and retrieval are context-sensitive in both humans and animals; memories are more accurately retrieved in the context where they were acquired, and similar stimuli can elicit different responses in different contexts. Researchers have suggested that such effects may be underpinned by mechanisms that modulate the dynamics of neural circuits in a context-dependent fashion. Based on this idea, we design a mechanism for context-dependent modulation of a liquid state machine, a recurrent spiking artificial neural network. We find that context modulation enables a single network to multitask and requires fewer neurons than when several smaller networks are used to perform the tasks individually.
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    NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning
    (Association for Computing Machinery, 2023-04-12) Daram, Anurag; Kudithipudi, Dhireesha
    Continual learning (sequential learning of tasks) is challenging for deep neural networks, mainly because of catastrophic forgetting, the tendency for accuracy on previously trained tasks to drop when new tasks are learned. Although several biologically-inspired techniques have been proposed for mitigating catastrophic forgetting, they typically require additional memory and/or computational overhead. Here, we propose a novel regularization approach that combines neuronal activation-based importance measurement with neuron state-dependent learning mechanisms to alleviate catastrophic forgetting in both task-aware and task-agnostic scenarios. We introduce a neuronal state-dependent mechanism driven by neuronal activity traces and selective learning rules, with storage requirements for regularization parameters that grow slower with network size - compared to schemes that calculate weight importance, whose storage grows quadratically. The proposed model, NEO, is able to achieve performance comparable to other state-of-the-art regularization based approaches to catastrophic forgetting, while operating with a reduced memory overhead.
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    An Stochastic Cold Food Supply Chain (CFSC) Design
    (Association for Computing Machinery, 2023-05-09) Hernandez-Cuellar, David; Castillo-Villar, Krystel K.
    Produce supply chains are a critical part of the food industry, as they are responsible for ensuring that fruits and vegetables are delivered to customers on time, at the right cost, and with the desired quality. Over the past few decades, researchers have been proposing the usage of Hub-and-Spoke networks as a modeling method to optimize large-scale food supply chains. Traditional optimization of supply chains involves identifying and eliminating inefficiencies, reducing lead times, improving inventory management, enhancing supplier relationships, and leveraging technology to improve visibility and control over the entire process. However, the majority of previous models are deterministic and fail to consider the implicit variability of crop yields and the consequence of climate change on the agricultural supply. The increasing amount of CO2 in the atmosphere, along with the shifts in temperatures and weather patterns, may influence harvests. Consequently, forcing distributors and consumers to look up for different suppliers in other areas to compensate for the fluctuations in the supply of produce. In this research, a stochastic Hub-and-spoke network model and an optimization algorithm are proposed to reduce transportation costs by finding an optimal production, distribution, and transportation network while considering climate variability and its impact on crop yield. A case study for an stochastic Cold Food Supply Chain (CFSC) considering several scenarios with different weather conditions is created using climate models and real soil data for the state of California. Strawberry is studied in this work, given that California is one of the major strawberry-producing states in the U.S. The preliminary results of the analysis indicate that weather scenarios showing more precipitation are more likely to increase crop yield, while scenarios with less precipitation yield lower amounts of fresh fruit.
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    A Neural Network Powered Solution Approach for Computationally Expensive Mixed Integer Programs for Bio Jet-fuel Supply Chain Network Design
    (Association for Computing Machinery, 2023-05-09) Keith, Kolton; Castillo-Villar, Krystel K.; Alaeddini, Adel
    Bio jet fuels derived from feedstock offer a sustainable alternative to meeting energy needs. Modeling supply chains that produce said fuels can lead to computationally prohibitive mixed integer linear programs (MILP) that consider optimal facility location and materials routing. The present work proposes an iterative machine learning-based hybrid solution procedure that transfers some of the responsibility of facility location to the learner. First, given a random selection of facility locations, a collection of model solutions is generated. Next, a neural network is fit to the collection of solutions, with facility locations being the input and total supply chain (SC) costs as the output. Then, the next set of locations is selected to optimize the predicted output of the neural network. Finally, the MILP optimization model is called to test the selected locations, and the results are fed back into the neural network and the process is repeated. Numerical experimentation demonstrates the proposed solution procedures yield near-optimal solutions with 0.10-0.18% increase in objective function value alongside a 40-65% reduction in computational time.
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    Evaluation and improvement of student learning experience in the post-COVID world: A lean six-sigma DMAIC study
    (SAGE Publications, 2023-08-07) Chang, Mike C.; Faruqui, Syed Hasib Akhter; Alaeddini, Adel; Wan, Hung-Da
    In 2020, the COVID-19 pandemic necessitated a shift to remote work-from-home (WFH) setups, including in the education sector. This transition had a significant impact on the interaction between students and instructors. To address this, our study aims to investigate the effects of the sudden transition to online learning on teaching methodology and to propose improvements to enhance its quality. We have developed a scoring system to evaluate teaching quality in the post-COVID-19 world. The scoring function incorporates various metrics, including students’ performance, sentiment towards the course (course material, teaching method, communication, etc.), feedback scores for weekly lectures, and students’ retention scores for recorded/live lecture videos. Following the Lean Six Sigma (LSS) procedure (Define, Measure, Analyze, Improve, and Control—DMAIC), we assessed the overall quality of online courses. The undergraduate courses demonstrated an increase in overall score from 86.67% during the online transition to 90.0% after implementing the suggested improvements. For graduate courses, the initial face-to-face lecture score was 55.81%, which dropped to 50.28% during the first online transition. However, after a year, the score improved to 61.59%, indicating successful improvement efforts. Upon careful analysis of the data, this paper provides suggestions to enhance students’ online learning experience during situations similar to the COVID-19 pandemic. The outcomes of the study aim to improve the quality of online learning experiences for students.
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    Architectural Design Qualities of an Adolescent Psychiatric Hospital to Benefit Patients and Staff
    (SAGE Publications, 2023-06-26) Norouzi, Neda; Martinez, Antonio; Rico, Zayra
    Objectives: This study is focused on how architectural design of adolescent psychiatric hospitals could positively affect not only patients but also staff members working at the hospitals. Background: Adolescents between the ages of 12 and 18 are among the young population with the highest percentage of mental illness. However, there are limited number of intentionally designed psychiatric hospitals for adolescents. Staff who work in adolescent psychiatric hospitals may face workplace violence. Studies on environmental impacts suggest that the built environment affects patients’ well-being and safety as well as staff’s satisfaction, working condition, safety, and health. However, there are very few studies that focus on adolescent psychiatric hospitals and the impact of the built environment on both staff and patients. Methods: Data were collected through literature analysis and semi-structured interviews with staff of three psychiatric state hospitals with adolescent patient units. The triangulation of multiple data sources informed a set of environmental design conditions that captures the complexity and connectedness of architectural design and the occupants of an adolescent psychiatric hospital. Results: The results present architectural composition, atmosphere, lighting, natural environment, safety, and security as indispensable design conditions to create an enclosed and city-like campus that provides a serene, secure, and structured environment that benefit staff and adolescent patients. Conclusion: The specific design strategies that need to be incorporated in the architectural design of a safe and secure adolescent psychiatric hospital include an open floor plan that respects patients’ autonomy and offers privacy while always providing staff with full visibility of patients.
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    Gold Nanomaterial System That Enables Dual Photothermal and Chemotherapy for Breast Cancer
    (2023-08-25) Wang, Lijun; Shrestha, Binita; Brey, Eric M.; Tang, Liang
    This study involves the fabrication and characterization of a multifunctional therapeutic nanocomposite system, as well as an assessment of its in vitro efficacy for breast cancer treatment. The nanocomposite system combines gold nanorods (GNRs) and gold nanoclusters (GNCs) to enable a combination of photothermal therapy and doxorubicin-based chemotherapy. GNRs of various sizes but exhibiting similar absorbance spectra were synthesized and screened for photothermal efficiency. GNRs exhibiting the highest photothermal efficiency were selected for further experiments. GNCs were synthesized in bovine serum albumin (BSA) and integrated into citrate-capped GNRs using layer-by-layer assembly. Glutaraldehyde crosslinking with the lysine residues in BSA was employed to immobilize the GNCs onto the GNRs, forming a stable "soft gel-like" structure. This structure provided binding sites for doxorubicin through electrostatic interactions and enhanced the overall structural stability of the nanocomposite. Additionally, the presence of GNCs allowed the nanocomposite system to emit robust fluorescence in the range of ~520 nm to 700 nm for self-detection. Hyaluronic acid was functionalized on the exterior surface of the nanocomposite as a targeting moiety for CD44 to improve the cellular internalization and specificity for breast cancer cells. The developed nanocomposite system demonstrated good stability in vitro and exhibited a pH- and near-infrared-responsive drug release behavior. In vitro studies showed the efficient internalization of the nanocomposite system and reduced cellular viability following NIR irradiation in MDA-MB-231 breast cancer cells. Together, these results highlight the potential of this nanocomposite system for targeted breast cancer therapy.
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    Measuring the Impact of Unique Entry-Level Instructional Course Modules Designed to Inspire Computer Science Interest
    (American Society for Engineering Education, 2016-06-26) Martinez Ortiz, Araceli; Guirguis, Mina
    Recent research regarding university student perceptions of “Computer Science” as a field of study and their motivation to pursue such studies as a career opportunity reveal student misconceptions and lack of motivation. Many students report that they regard the study of computer science as narrowly equivalent to “programming”. Moreover, many are not consistently provided the opportunity to realize the true impact of the field within their entry-level courses since these early courses tend to focus on programming and syntax skill development. It is not until they are in their upper-level courses that they gain a broader understanding and by then, many of them have already left the field. It is hypothesized that this lack of clarity of the field at an early point in students’ academic career, coupled with the perception that the curriculum is largely irrelevant to their lives, has impacted the retention rates of computer science majors in the first two years of their academic study programs. This paper will report on a preliminary stage of a comprehensive project effort that aims to improve retention rates for computer science students in their entry-level courses through the development of course modules intended for inclusion in their entry-level curriculum. The theoretical basis for these modules will be reviewed and the design framework for the development of these models is discussed. The aim of these models is to highlight the difference between Computer Science and Programming, to show the relevance of Computer Science in recent advances in various fields, and to inspire students to appreciate Computer Science and the role of algorithms in our daily lives. The modules will cover various topics about the role of CS in cyber warfare, understanding biology, electronic voting, etc. In subsequent work, these modules will be launched as part of a mixed methods study to determine their effectiveness as compared to a control group not learning through these models and the impact of those modules on the retention rates of Computer Science majors.
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    Fifth Grade Students’ Understanding of Ratio and Proportion in an Engineering Robotics Program
    (American Society for Engineering Education, 2011-06-26) Martinez Ortiz, Araceli
    The research described in this study explores the impact of utilizing a LEGO-robotics integrated engineering and mathematics program to support fifth grade students’ learning of ratios and proportion in an extracurricular program. One of the research questions guiding this research study was “how do students’ test results compare for students learning ratio and proportion concepts within the LEGO‐robotics integrated engineering and mathematics program versus when using a non-engineering textbook­‐based mathematics program?” A mixed method repeated measures experiment with a control group was conducted. The subjects were 30 fifth grade students from a large urban school district who participated in one of two intervention programs, a LEGO­‐robotics integrated engineering and mathematics program (experimental) versus a non-engineering textbook-­based mathematics program (control). The understanding of ratio and proportion through numerical computation was measured using the Intra­‐Mathematical Proportional Reasoning Test (Intra­‐Prop). The understanding of ratio and proportion in general­‐context mathematical word problems was measured using the Extra­‐Mathematical Proportional Reasoning Test in a General Context (Extra-­Prop) and the understanding of ratio and proportion in a LEGO engineering context was measured using a mathematical tool called Extra-Mathematical Proportional Reasoning Test in an Engineering Context (Engin-­Prop). Students’ understanding of select basic engineering and mathematics definitions was measured using the Background and Definitions Test (Definitions Test). Data collected included classroom video, student interviews and written mathematical assessments of ratio and proportion problems in the four forms defined above, using repeated measures across three time periods-­- prior to the beginning of the intervention programs, after the conclusion of the intervention program and ten weeks after the conclusion of the intervention program. The results of this study indicated that all students were able to make significant progress in learning new concepts of ratio and proportion as a result of participating in the intervention program learning experiences. Experimental students’ performance on the Intra-Prop was not significantly higher than that of the control students’ performance. However, experimental students’ performance on the Extra-Prop, Engin-Prop, and Definitions tests was significantly higher than that of the control students, indicating that students that learn about ratio and proportion in an engineering related context improve in their understanding significantly and retain their learning for a longer period of time when they encounter these situations in an extra-mathematical context versus in an intra-mathematical context. In addition, and of special note to practitioners, is the fact that students in the experimental group were able to learn at least as much and as well (if not more) the mathematics content of ratio and proportion as compared to the control group of students, and in addition, within the same amount of time, control group students learned and retained engineering and related ratio and proportion mathematics concepts.
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    Development And Implementation Of Challenge Based Instruction In Statics And Dynamics
    (American Society for Engineering Education, 2010-06-20) Freeman, Robert; Vasquez, Horacio; Knecht, Martin; Martin, Taylor; Fuentes, Arturo; Walker, Joan; Martinez Ortiz, Araceli
    This paper discusses challenge-based instructional (CBI) materials developed for courses in Statics and Dynamics. This effort is a component of a funded College Cost Reduction and Access Act (CCRAA) grant from the Department of Education, and focuses on student retention and development of adaptive expertise. Studies have shown that minority science, technology, engineering, and math (STEM) students leave STEM undergraduate fields in part due to lack of real world connections to their classroom learning experiences. Furthermore, in STEM fields the conventional approach is to teach for efficiency first and for innovation only in the latter years of the curriculum. This focus on efficiency first can actually stifle attempts at innovation in later courses. Our response to these issues is to change the way we teach. CBI, a form of inquiry based learning, can be simply thought of as teaching backwards. In this approach, a challenge is presented first, and the supporting theory (required to solve the challenge) second. Our implementation of CBI is built around the How People Learn (HPL) framework for effective learning environments and is realized and anchored by the STAR Legacy Cycle, as developed and fostered by the VaNTH NSF ERC for Bioengineering Educational Technologies. The developed materials are a result of collaboration between faculty members at the University of Texas-Pan American (UTPA) and South Texas College (STC), a two year Hispanic Serving Institution (HSI).
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    A Comprehensive Model for Motivating and Preparing Under-represented Students, Educators and Parents in Science, Engineering, and Technology
    (American Society for Engineering Education, 2014-06-18) Martinez Ortiz, Araceli
    A comprehensive informal learning STEM outreach program for kindergarten through grade 4 (K-­4) students is described along with the program’s theory of change and findings based on the participation of more than 200 urban minority students and their parents over a four-­year period. This NSF-­funded informal learning program was grounded in parental engagement theory of planned behavior and integrated both active-­learning pedagogies and in-­situ professional development for teachers. A unique age-­appropriate science, engineering and technology integrated curriculum was delivered as a series of Saturday workshops set in a community science museum. Each year, cohorts of K­‐3 African American and Hispanic students and their parents participated in eight 3-­hour workshops comprised of student/parent sessions of hands-on science and engineering activities as well as separate parent awareness and development sessions in STEM education and technology skill development. The aim of this program has been to increase the participation of underrepresented groups in the science, technology, engineering, and mathematics (STEM) fields by attending to students early in the educational process. To accomplish this, the program has been guided by the following goals: to increase the knowledge, skills, and interest of K–3 students from underrepresented population groups in STEM fields; to increase parents’ knowledge and skills in science and engineering and their capacity to support their children in pursuing education and careers in these fields; and to increase the effectiveness of teachers in engaging students and parents in the Saturday science-related learning activities. Mixed methods research methodology has been used to measure the program’s contribution to the advancement of the program goals. Learning, motivational, and efficacy outcomes have been measured with pre and post student, teacher and parent survey instruments. This program has incorporated major findings of more than 10-years of research that suggests that improving children’s academic outcomes are much more effective when the family is actively engaged. This program has offered opportunities for parents to work along side their children; provided strategies promoting positive parental/child engagement; and provided ongoing training and professional development for project teachers. Young minority children have been exposed to African American, Latino, and women scientists and engineers through personal contact at special events, and via a featured program website section. Preliminary evaluation findings based on pre and post surveys, interviews, and observational data will be presented that indicate this program is helping parents and students persist in the program for multiple years and is motivating positive changes in student content understanding and career motivation.
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    Implementing PBL in a Concrete Construction Course
    (American Society for Engineering Education, 2014-06-18) Hu, Jiong; Martinez Ortiz, Araceli; Sriraman, Vedaraman
    This paper presents an action-research case study detailing the evolutionary changes in the implementation of the problem-based learning (PBL) method in an undergraduate concrete construction course. The case study incorporates the perspective of the course instructor as action-researcher and the quantitative and qualitative student impact data. PBL was first implemented in this course in 2011 as a student centered active learning pedagogy. The first implementation adopted a minimalist approach owing to the issues typically associated with PBL adoption such as increased instructor effort and student resistance to a new learning paradigm. Through 2012 and 2013, the action researcher continued to adopt and increase the scope of PBL application. In 2013, the course moved from a summer offering to a spring offering. This change proved to be very positive for both instructor and students alike. Most significantly, the change in schedule permitted a longer time span in which the PBL activities could be more effectively implemented compared to the short, fast paced summer offering. The evolution in the adaptation of PBL pedagogy and key components for success in the implementation of PBL in the engineering and engineering technology classroom will be presented. In addition, a discussion of the assessment methods that also underwent an evolution in scope and detail will be presented. The paper concludes with recommendations for further research.
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    Engaging Students in Sustainability Education and Awareness of Green Engineering Design and Careers through a Pre-Engineering Program
    (American Society for Engineering Education, 2015-06-17) Martinez Ortiz, Araceli; Asiabanpour, Bahram; Aslan, Semih; Jimenez, Jesus Alejandro; Kim, Yoo-Jae; Salamy, Hassan
    A framework for an active learning summer program for middle school students is presented along with survey instruments and pre and post program data regarding student attitudes and awareness of sustainable design issues and career motivation in the field. This summer program was designed to attract students, especially from underrepresented groups, into early motivating experiences in the engineering fields and to increase their awareness of concepts and careers in renewable energy, and green engineering design principles and technologies. Twenty-four students from a low social economic school district were provided the opportunity to experience many state of the art engineering technologies at the university’s school of engineering and to learn from a diverse group of knowledgeable mentoring faculty. In the week-long program, students were involved in hands-on engineering and renewable energy activities appropriate to their age and knowledge. Topics covered included: the engineering design process, CAD solid modeling, 3D Printing and water jet cutting, hands-on assembly, renewable energy resources for homes, sustainable site selection, and water efficiency principles. Using project-based learning, student teams participated as designers of their own green home models by integrating their learning of renewable energy use, conservation practices, and appropriate design and material selection. Pre and post surveys revealed increases in student awareness of general engineering and renewable energy concepts as well as increased interest in pursuing engineering careers.
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    Considering the Effectiveness of Comprehensive Assessment and the Impact of PBL Implementation in a Concrete Industry Project Management Course
    (American Society for Engineering Education, 2016-06-26) Torres, Anthony; Sriraman, Vedaraman; Martinez Ortiz, Araceli
    The objectives of this study were two-fold: first, to assess the effectiveness of using Project Based Learning (PrBL) pedagogy and second, to determine the efficacy of a comprehensive set of assessment methods from the standpoint of assessing learning in a PrBL implementation. The project used in this study incorporates actual, in-the-field projects that represent real-life scenarios that the students will encounter once they graduate. Various direct assessment methods were implemented in this study. These assessment methods included a pre and post questionnaire of student beliefs and opinions, homework grades, in-class ‘clicker’ quiz grades, overall project grades, embedded test question grades, a video lecture project, and short answer case study questions on exams. The data sets collected with these assessment methods were compared to data taken from the past two offerings of the same course and with data from a similar course taught by the same professor in the same department. The analysis reshowed that the students favored both the actual concrete construction project and the milestone deliverable method. The particular assessment methods that provided the most feedback were the embedded test questions and the case study section of the exam. Since students had to work with an individual real-world case study on the exam, the individual student’s effort, understanding, and ability to solve technical problems from the milestone project were quantified through the exam. The overall grade assessment method revealed an average of 4.5 percentage point increase in grades from past offerings of the course and a similar course that does not include the PrBL pedagogy.
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    The Roots of Science, Mathematics and Engineering Self-confidence in College Students: Voices of Successful Undergraduate Women
    (American Society for Engineering Education, 2015-06-14) Torres, Anthony; Talley, Kimberly Grau; Martinez Ortiz, Araceli
    With the percentage of women in STEM majors at _____ University, a large Hispanic Serving Institution, significantly lower than the percentage of women attending the university in general, the authors sought to understand this gap by studying the perspectives of undergraduate women who have successfully persisted in a STEM field of study at the same university. Specifically, the goal of this study was to gain a deeper understanding of what experiences women credited for influencing their self-efficacy, the development of their career interest goals and their academic course outcomes as related to studying science, technology, engineering and mathematics (STEM). This study was also designed to identify experiences that appear to contribute to women’s identity development and self-confidence. Data was collected and analyzed to identify if similar patterns exist between subjects and if so, which are the greater influencers in their decision to select a STEM major and to persist beyond the critical first two years of undergraduate studies. The literature of socialization and identity development as related to women as STEM learners in diverse communities is reviewed. This study begins to create an understanding of how women think about their multiple social identities (field of study, gender, culture, etc.). Focus group strategies for obtaining in-depth feedback regarding young women’s attitudes, perceptions, motivations, and behaviors is discussed. Observations and recommendations regarding the 2015 ASEE Annual Conference & Exposition / Women in Engineering Division research methodologies for study design and data analysis are presented with particular attention to the rationale for cultural responsive practices in qualitative research. A mixed methods research approach including the use of surveys and focus groups was used to collect student perceptions from junior and senior status students in STEM fields of study. Preliminary results indicate that students identify early personal experiences as building their self-confidence and contributing to their identity development. Drawing on self-perception theory, women appear to develop a more robust sense of persistence and feel that they fit into STEM- even when faced with sexism from other students.
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    Early Internships for Engineering Technology Student Retention: A Pilot Study
    (American Society for Engineering Education, 2016-06-26) Sriraman, Vedaraman; Spencer, Bobbi J.; Talley, Kimberly Grau; Martinez Ortiz, Araceli
    Research in engineering technology major retention suggests that early internships present an outstanding opportunity for freshman and sophomore students to engage, socialize and learn in communities of practice and to “discover” the link between theory and practice early in their academic tenure, leading to a consequent improvement in retention rates. At xxxx State University, the traditional senior level capstone internship program was reengineered and converted into a sophomore level program with minimal prerequisites so as to enable sophomore level engineering technology students to participate early in the internships, explore their majors and undergo experiential learning in the world of practice in their chosen disciplines. The motivation for this project came from onsite internship industry interviews and our industrial advisory boards which strongly suggested that early, “immersion” type industrial experiences would prepare students to become better learners. This conversion coincided with the strategic imperatives that stemmed from a university wide second year STEM major retention effort. This latter effort culminated in a four year NSF funded project, of which the early internships are a module. This paper describes the internship program reengineering effort, the details of the early internship program implementation and aspects of how the program is facilitating the assessment of student learning outcomes for ABET and other accreditation processes. The paper concludes with preliminary results that were harvested from the pilot implementation in Summer 2015 and with directions for future work.