Kevin Moore - US grants

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

The objective of this research is the development of methods for the control of energy flow in buildings, as enabled by cyber infrastructure. The approach is inherently interdisciplinary, bringing together electrical and mechanical engineers alongside computer scientists to advance the state of the art in simulation, design, specification and control of buildings with multiple forms of energy systems, including generation and storage. A significant novelty of this project lies in a fundamental view of a building as a set of overlapping, interacting networks. These networks include the thermal network of the physical building, the energy distribution network, the sensing and control network, as well as the human network, which in the past have been considered only separately. This work thus seeks to develop methods for simulating, optimizing, modeling, and control of complex, heterogeneous networks, with specific application to energy efficient buildings. The advent of maturing distributed and renewable energy sources for on-site cooling, heating, and power production and the concomitant developments in the areas of cyberphysical and microgrid systems present an enormous opportunity to substantially increase energy efficiency and reduce energy-related emissions in the commercial building energy sector. In addition, there is a direct impact of the proposed work in training students with backgrounds in the unique blend of engineering and computer science that is needed for the study of cyber-enabled energy efficient management of structures, as well as planned interactions at the undergraduate and K-12 level.

Graduate students in mathematics are often called on to teach sections of introductory courses ranging from college algebra, to precalculus, to calculus. In this project a team of mathematicians and mathematics education researchers are developing a sequence of courses and associated activities that support Ph.D. students in mathematics to adopt a scientific approach both to their teaching and to evaluating the effectiveness of the underlying curriculum. The intellectual merit of this effort lies in its use of previously developed research-based student and teacher materials that have been documented to transform precalculus and calculus teaching and learning. Based on this prior work the investigating team is creating a model education certificate program for mathematics graduate students that is envisioned to transform their teaching practice. Concurrent with these teaching experiences, students complete a sequence of courses and seminars in which they read select publications, review materials, and design and conduct small-scale research studies of student learning. These combined program components lay the groundwork for producing mathematics Ph.D. students who are prepared to take leadership roles in improving the teaching and learning of undergraduate mathematics. The project is exercising its broader impact both by engaging the faculty to change the culture and departmental infrastructure in the PI's own institution, and by serving as model for other departments of mathematics who can incorporate the education certification program into their graduate offerings, thus supporting pre-professional faculty development of their students.

Science, Technology, Engineering and Mathematics [STEM] and STEM education researchers and policy documents have directed mathematics educators at all levels to increase emphasis on quantitative reasoning so that students are prepared for continued studies in mathematics and other STEM fields. Often, teachers are not sufficiently prepared to support their students' quantitative reasoning. The products generated by this project fill a need for concrete materials at the pre-service level that embody research-based knowledge in the area of quantitative reasoning. The accessible collection of research and educational products provides a model program for changing prospective mathematics teachers' quantitative reasoning that is adoptable at other institutions across the nation. Additionally, the support of early CAREER scholars in mathematics education will add to the capacity of the country to address issues in mathematics education in the future.

Advancing Reasoning addresses the lack of materials for teacher education by investigating pre-service secondary mathematics teachers' quantitative reasoning in the context of secondary mathematics concepts including function and algebra. The project extends prior research in quantitative reasoning to develop differentiated instructional experiences and curriculum that support prospective teachers' quantitative reasoning and produce shifts in their knowledge. Three interrelated research questions guide the project: (i) What aspects of quantitative reasoning provide support for prospective teachers' understanding of major secondary mathematics concepts such as function and algebra? (ii) How can instruction support prospective teachers' quantitative reasoning in the context of the teaching and learning of major secondary mathematics concepts such as function and algebra? (iii) How do the understandings prospective teachers hold upon entering a pre-service program support or inhibit their quantitative reasoning? Advancing Reasoning addresses these questions by enacting an iterative, multi-phase study with 200 prospective teachers enrolled in a secondary mathematics education content course over 5 years. The main phase of the study implements a series of classroom design experiments to produce knowledge on central aspects of prospective teachers' quantitative reasoning and the instructional experiences that support such reasoning. By drawing this knowledge from a classroom setting, Advancing Reasoning contributes research-based and practice-driven deliverables that improve the teaching and learning of mathematics.

The recommendation to make generalization a central component of mathematics instruction from elementary school through undergraduate mathematics poses serious challenges in light of the research base that identifies students' difficulties in creating and expressing correct mathematical generalizations and the challenges teachers face in supporting students' abilities to generalize. Furthermore, although student difficulties are well documented, the instructional conditions necessary for fostering generalization are not well understood, particularly at the secondary and undergraduate levels. This project addresses these challenges by developing a comprehensive framework characterizing productive mathematical generalization in Grades 8-16 and identifying instructional interventions that can support correct generalizing. The project occurs within multiple mathematical domains extending from middle school to undergraduate mathematics, including algebra, geometry, calculus, and combinatorics. The project investigators will leverage student interviews, teaching experiments, and design experiment methodologies in order to characterize the processes of generalizing and to identify the instructional conditions that support productive generalization. The results of the project will identify specific tasks and activities fostering student generalizing in a diversity of mathematical settings, which will be of practical use to teachers, school districts, teacher educators, and university instructors.

Mathematical generalization, the ability to create general rules, formulas, and strategies, is a key aspect of doing mathematics. Policy makers recommend making generalization a central component of mathematics instruction at every grade level from elementary school through undergraduate mathematics, with the Common Core State Standards highlighting generalization as a major goal in both the content and the practice standards. However, these recommendations pose serious challenges given students' pervasive difficulties in creating and expressing generalizations. In a report on performance assessments from more than 60,000 secondary students, findings revealed only a 20% success rate in students' creation of correct general statements. Students' challenges with mathematical generalizations also contribute to difficulties in mathematics achievement in many domains, including algebra, geometry, and combinatorics. This project will address these challenges by investigating how students generalize productively and how teachers can support more effective mathematical generalization. Through student interviews and teaching experiments, the project investigators will explore these issues in algebra, geometry, calculus, and combinatorics. Student participants will range from middle school students through undergraduates. The diverse range of student ages and mathematical domains will contribute to a robust model characterizing how students generalize in Grades 8-16. These findings will also identify instructional activities that can better support generalization in many different settings, which will be of use to teachers, school districts, teacher educators, and university instructors. The knowledge generated from the project will support improved student performance in critical areas of undergraduate mathematics, thus contributing to a diverse and globally competitive STEM workforce.

ABSTRACT Many recent studies focused on radiotherapy treatment plan quality have begun to quantify what clinicians have long understood: even ?optimized? radiotherapy is no guarantee of a truly optimal treatment plan for every patient. Plan quality deficiencies have been shown to put a significant proportion of patients who should have been at low risk of radiation-induced complications at much higher risk for poor outcome. Available research clearly demonstrates a link between radiation provider volume and survival, which emphasizes the importance of quality radiation delivery. Radiation providers in rural or community practices by nature see a wide variety of cases, with lower provider volume for each individual disease site. Through no fault of their own, physician and non-physician practitioners at these rural and community centers could be inadvertently and systematically delivering low quality radiotherapy to their patients simply due to the fact that no platform currently exists that could benchmark their practice against a distributed, externally-validated plan quality control system. Our research team has developed, tested, and clinically-implemented an important tool to combat radiotherapy plan quality deficiencies known as knowledge-based planning (KBP). Knowledge-based planning relies on the use of statistical learning techniques that analyzed a plurality of prior treatments to discover patient-specific anatomical features can be precisely correlated to high quality radiation dose delivery. Unfortunately, the clinical use of KBP has been limited to a handful of high-volume academic centers and, without some external mechanism to increase utilization, its use is not likely to expand significantly to rural and community centers because of the lack of any billing code associated with its use. To provide just such an external mechanism, we intend to build ORBITeR (On-line Real-time Benchmarking Informatics Technology for Radiotherapy), a freely available, on-line knowledge-based radiotherapy plan quality control system. ORBITeR will allow clinicians to obtain automatic and immediate feedback on the quality of any individual treatment plan prior to treatment. We will develop a KBP-driven plan analysis system on a HIPAA-compliant web-based platform designed to give users real- time radiotherapy plan quality feedback. To provide real-time feedback to clinical users, we will develop reporting modules on the ORBITeR system that provide patient-specific feedback on the quality of the intended treatment plan using already-validated head-and-neck, brain, prostate, cervix, lung, pancreas, and liver cancer knowledge-based models. We then will disseminate and evaluate the effectiveness of the ORBITeR plan quality resource among the greater radiation oncology community. Finally, we will develop a quality analytics system to conduct widespread plan quality and patterns of care study across submitting sites on the ORBITeR system. .

This RAPID study incorporates a diverse project team of scientists and communicators to investigate how people interpret representations of quantitative data regarding COVID-19. Such representations include maps, graphs, and charts, which are commonly used in media such as newspapers, television, websites, and press briefings. Research indicates that many people have difficulty interpreting the information presented in these representations. As a result, the public may have limited tools for understanding the severity of the COVID-19 pandemic, which may limit their ability to use the data in making decisions about their risk and effective risk-mitigation actions. The project responds to this pressing issue by immediately enacting a study to investigate individuals? understandings and decisions during the pandemic. It will use this information to develop new approaches to displaying quantitative data that can promote greater understanding. Such approaches are likely to be useful for increasing scientific and mathematical literacy, and will also be incorporated into undergraduate STEM courses.


The study includes a multi-phase design-research approach to investigating COVID-19 quantitative data representations (QDRs) through an iterative sequence of task-based clinical interviews. In Phase I, the project team will investigate a diverse population to produce differentiated models of participants? QDR interpretations and juxtapositions of these models that reveal key conceptual categories across participants. In Phase II, the project team will apply findings from Phase I and STEM education research to create research-based, project-designed QDRs while simultaneously investigating the extent to which these QDRs better support individuals? understanding of the pandemic. In Phase III, the project team will actively disseminate the results, to draw attention to knowledge and products generated by the project. Reflecting the societal implications of COVID-19, the dissemination plan targets both educational and public communication media communities. Collectively, the project activities and deliverables have the potential to produce a deeper understanding and tangible examples of how STEM education research can be used to improve students? and citizens? learning and well-being. Through working directly with members of education and media communities, the project team will improve project exposure and the QDRs made available for public use to ensure that STEM education research impacts not only students? educational experiences, but also the general public?s ability to interpret quantitative data in ways that positively influence their lives. This RAPID award is funded by the Improving Undergraduate STEM Education Program in the NSF Education and Human Resources/Division of Undergraduate Education.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.