An Experience-Driven Pedagogy for the Instruction of Software Testing in Computer Science

In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.

United States certificate programs in technical communication : a feminist-sophistic investigation

Technical communication certificates are offered by many colleges and universities as an alternative to a full undergraduate or graduate degree in the field. Despite certificates’ increasing popularity in recent years, however, surprisingly little commentary exists about them within the scholarly literature. In this work, I describe a survey of certificate and baccalaureate programs that I performed in 2008 in order to develop basic, descriptive data on programs’ age, size, and graduation rates; departmental location; curricular requirements; online offerings; and instructor status and qualifications. In performing this research, I apply recent insights from neosophistic rhetorical theory and feminist critiques of science to both articulate, and model, a feminist-sophistic methodology. I also suggest in this work that technical communication certificates can be theorized as a particularly sophistic credential for a particularly sophistic field, and I discuss the implications of neosophistic theory for certificate program design and administration.

Fixed block configuration GDDs with block size 6 and (3, r)-regular graphs

Chapter 1 is used to introduce the basic tools and mechanics used within this thesis. Most of the definitions used in the thesis will be defined, and we provide a basic survey of topics in graph theory and design theory pertinent to the topics studied in this thesis. In Chapter 2, we are concerned with the study of fixed block configuration group divisible designs, GDD(n; m; k; λ1; λ2). We study those GDDs in which each block has configuration (s; t), that is, GDDs in which each block has exactly s points from one of the two groups and t points from the other. Chapter 2 begins with an overview of previous results and constructions for small group size and block sizes 3, 4 and 5. Chapter 2 is largely devoted to presenting constructions and results about GDDs with two groups and block size 6. We show the necessary conditions are sufficient for the existence of GDD(n, 2, 6; λ1, λ2) with fixed block configuration (3; 3). For configuration (1; 5), we give minimal or nearminimal index constructions for all group sizes n ≥ 5 except n = 10, 15, 160, or 190. For configuration (2, 4), we provide constructions for several families ofGDD(n, 2, 6; λ1, λ2)s. Chapter 3 addresses characterizing (3, r)-regular graphs. We begin with providing previous results on the well studied class of (2, r)-regular graphs and some results on the structure of large (t; r)-regular graphs. In Chapter 3, we completely characterize all (3, 1)-regular and (3, 2)-regular graphs, as well has sharpen existing bounds on the order of large (3, r)- regular graphs of a certain form for r ≥ 3. Finally, the appendix gives computational data resulting from Sage and C programs used to generate (3, 3)-regular graphs on less than 10 vertices.

Characterization of thermal and mechanical properties of polypropylene-based composites for fuel cell bipolar plates and development of educational tools in hydrogen and fuel cell technologies

In this project we developed conductive thermoplastic resins by adding varying amounts of three different carbon fillers: carbon black (CB), synthetic graphite (SG) and multi-walled carbon nanotubes (CNT) to a polypropylene matrix for application as fuel cell bipolar plates. This component of fuel cells provides mechanical support to the stack, circulates the gases that participate in the electrochemical reaction within the fuel cell and allows for removal of the excess heat from the system. The materials fabricated in this work were tested to determine their mechanical and thermal properties. These materials were produced by adding varying amounts of single carbon fillers to a polypropylene matrix (2.5 to 15 wt.% Ketjenblack EC-600 JD carbon black, 10 to 80 wt.% Asbury Carbon's Thermocarb TC-300 synthetic graphite, and 2.5 to 15 wt.% of Hyperion Catalysis International's FIBRILTM multi-walled carbon nanotubes) In addition, composite materials containing combinations of these three fillers were produced. The thermal conductivity results showed an increase in both through-plane and in-plane thermal conductivities, with the largest increase observed for synthetic graphite. The Department of Energy (DOE) had previously set a thermal conductivity goal of 20 W/m·K, which was surpassed by formulations containing 75 wt.% and 80 wt.% SG, yielding in-plane thermal conductivity values of 24.4 W/m·K and 33.6 W/m·K, respectively. In addition, composites containing 2.5 wt.% CB, 65 wt.% SG, and 6 wt.% CNT in PP had an in–plane thermal conductivity of 37 W/m·K. Flexural and tensile tests were conducted. All composite formulations exceeded the flexural strength target of 25 MPa set by DOE. The tensile and flexural modulus of the composites increased with higher concentration of carbon fillers. Carbon black and synthetic graphite caused a decrease in the tensile and flexural strengths of the composites. However, carbon nanotubes increased the composite tensile and flexural strengths. Mathematical models were applied to estimate through-plane and in-plane thermal conductivities of single and multiple filler formulations, and tensile modulus of single-filler formulations. For thermal conductivity, Nielsen's model yielded accurate thermal conductivity values when compared to experimental results obtained through the Flash method. For prediction of tensile modulus Nielsen's model yielded the smallest error between the predicted and experimental values. The second part of this project consisted of the development of a curriculum in Fuel Cell and Hydrogen Technologies to address different educational barriers identified by the Department of Energy. By the creation of new courses and enterprise programs in the areas of fuel cells and the use of hydrogen as an energy carrier, we introduced engineering students to the new technologies, policies and challenges present with this alternative energy. Feedback provided by students participating in these courses and enterprise programs indicate positive acceptance of the different educational tools. Results obtained from a survey applied to students after participating in these courses showed an increase in the knowledge and awareness of energy fundamentals, which indicates the modules developed in this project are effective in introducing students to alternative energy sources.

Adapting health-risk communication to the specific cultural contexts of diverse populations : an assessment of malaria-treatment programs in Liberia

Drawing on theories of technical communication, rhetoric, literacy, language and culture, and medical anthropology, this dissertation explores how local culture and traditions can be incorporated into health-risk-communication-program design and implementation, including the design and dissemination of health-risk messages. In a modern world with increasing global economic partnerships, mounting health and environmental risks, and cross-cultural collaborations, those who interact with people of different cultures have “a moral obligation to take those cultures seriously, including their social organization and values” (Hahn and Inhorn 10). Paradoxically, at the same time as we must carefully adapt health, safety, and environmental-risk messages to diverse cultures and populations, we must also recognize the increasing extent to which we are all becoming part of one, vast, interrelated global village. This, too, has a significant impact on the ways in which healthcare plans should be designed, communicated, and implemented. Because communicating across diverse cultures requires a system for “bridging the gap between individual differences and negotiating individual realities” (Kim and Gudykunst 50), both administrators and beneficiaries of malaria-treatment-and-control programs (MTCPs) in Liberia were targeted to participate in this study. A total of 105 people participated in this study: 21 MTCP administrators (including designers and implementers) completed survey questionnaires on program design, implementation, and outcomes; and 84 MTCP beneficiaries (e.g., traditional leaders and young adults) were interviewed about their knowledge of malaria and methods for communicating health risks in their tribe or culture. All participants showed a tremendous sense of courage, commitment, resilience, and pragmatism, especially in light of the fact that many of them live and work under dire socioeconomic conditions (e.g., no electricity and poor communication networks). Although many MTCP beneficiaries interviewed for this study had bed nets in their homes, a majority (46.34 percent) used a combination of traditional herbal medicine and Western medicine to treat malaria. MTCP administrators who participated in this study rated the impacts of their programs on reducing malaria in Liberia as moderately successful (61.90 percent) or greatly successful (38.10 percent), and they offered a variety of insights on what they might do differently in the future to incorporate local culture and traditions into program design and implementation. Participating MTCP administrators and beneficiaries differed in their understanding of what “cultural incorporation” meant, but they agreed that using local indigenous languages to communicate health-risk messages was essential for effective health-risk communication. They also suggested that understanding the literacy practices and linguistic cultures of the local people is essential to communicating health risks across diverse cultures and populations.

Simulating dioxane transport in a heterogeneous glacial aquifer system (Washtenaw County, Michigan) using publicly available models and data

The primary challenge in groundwater and contaminant transport modeling is obtaining the data needed for constructing, calibrating and testing the models. Large amounts of data are necessary for describing the hydrostratigraphy in areas with complex geology. Increasingly states are making spatial data available that can be used for input to groundwater flow models. The appropriateness of this data for large-scale flow systems has not been tested. This study focuses on modeling a plume of 1,4-dioxane in a heterogeneous aquifer system in Scio Township, Washtenaw County, Michigan. The analysis consisted of: (1) characterization of hydrogeology of the area and construction of a conceptual model based on publicly available spatial data, (2) development and calibration of a regional flow model for the site, (3) conversion of the regional model to a more highly resolved local model, (4) simulation of the dioxane plume, and (5) evaluation of the model's ability to simulate field data and estimation of the possible dioxane sources and subsequent migration until maximum concentrations are at or below the Michigan Department of Environmental Quality's residential cleanup standard for groundwater (85 ppb). MODFLOW-2000 and MT3D programs were utilized to simulate the groundwater flow and the development and movement of the 1, 4-dioxane plume, respectively. MODFLOW simulates transient groundwater flow in a quasi-3-dimensional sense, subject to a variety of boundary conditions that can simulate recharge, pumping, and surface-/groundwater interactions. MT3D simulates solute advection with groundwater flow (using the flow solution from MODFLOW), dispersion, source/sink mixing, and chemical reaction of contaminants. This modeling approach was successful at simulating the groundwater flows by calibrating recharge and hydraulic conductivities. The plume transport was adequately simulated using literature dispersivity and sorption coefficients, although the plume geometries were not well constrained.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

CHARACTERIZATION OF THERMAL AND MECHANICAL PROPERTIES OF POLYPROPYLENE–BASED COMPOSITES FOR FUEL CELL BIPOLAR PLATES AND DEVELOPMENT OF EDUCATIONAL TOOLS IN HYDROGEN AND FUEL CELL TECHNOLOGIES

In this project we developed conductive thermoplastic resins by adding varying amounts of three different carbon fillers: carbon black (CB), synthetic graphite (SG) and multi–walled carbon nanotubes (CNT) to a polypropylene matrix for application as fuel cell bipolar plates. This component of fuel cells provides mechanical support to the stack, circulates the gases that participate in the electrochemical reaction within the fuel cell and allows for removal of the excess heat from the system. The materials fabricated in this work were tested to determine their mechanical and thermal properties. These materials were produced by adding varying amounts of single carbon fillers to a polypropylene matrix (2.5 to 15 wt.% Ketjenblack EC-600 JD carbon black, 10 to 80 wt.% Asbury Carbons’ Thermocarb TC-300 synthetic graphite, and 2.5 to 15 wt.% of Hyperion Catalysis International’s FIBRILTM multi-walled carbon nanotubes) In addition, composite materials containing combinations of these three fillers were produced. The thermal conductivity results showed an increase in both through–plane and in–plane thermal conductivities, with the largest increase observed for synthetic graphite. The Department of Energy (DOE) had previously set a thermal conductivity goal of 20 W/m·K, which was surpassed by formulations containing 75 wt.% and 80 wt.% SG, yielding in–plane thermal conductivity values of 24.4 W/m·K and 33.6 W/m·K, respectively. In addition, composites containing 2.5 wt.% CB, 65 wt.% SG, and 6 wt.% CNT in PP had an in–plane thermal conductivity of 37 W/m·K. Flexural and tensile tests were conducted. All composite formulations exceeded the flexural strength target of 25 MPa set by DOE. The tensile and flexural modulus of the composites increased with higher concentration of carbon fillers. Carbon black and synthetic graphite caused a decrease in the tensile and flexural strengths of the composites. However, carbon nanotubes increased the composite tensile and flexural strengths. Mathematical models were applied to estimate through–plane and in–plane thermal conductivities of single and multiple filler formulations, and tensile modulus of single–filler formulations. For thermal conductivity, Nielsen’s model yielded accurate thermal conductivity values when compared to experimental results obtained through the Flash method. For prediction of tensile modulus Nielsen’s model yielded the smallest error between the predicted and experimental values. The second part of this project consisted of the development of a curriculum in Fuel Cell and Hydrogen Technologies to address different educational barriers identified by the Department of Energy. By the creation of new courses and enterprise programs in the areas of fuel cells and the use of hydrogen as an energy carrier, we introduced engineering students to the new technologies, policies and challenges present with this alternative energy. Feedback provided by students participating in these courses and enterprise programs indicate positive acceptance of the different educational tools. Results obtained from a survey applied to students after participating in these courses showed an increase in the knowledge and awareness of energy fundamentals, which indicates the modules developed in this project are effective in introducing students to alternative energy sources.