Dordt College is a private, Christian, liberal arts college located in Sioux Center, Iowa, United States. It was founded in 1955 and is affiliated with the Christian Reformed Church in North America. The college name is a reference to the Synod of Dordt .Dordt annually enrolls about 1,300 students from more than 30 states, seven Canadian provinces, and 10 other countries, with a student-faculty ratio of 15:1. U.S. News and World Report has included Dordt in its America’s Best Colleges listing for 18 straight years , including a six top 10 rankings in the Midwest region’s Best Baccalaureate Colleges. In 2008 it was tied for #3 in the Midwest region.The college is committed to a Reformed, Christian perspective that embraces the Bible as the word of God. The college offers 90 programs of study that lead to Associate of Arts, Bachelor of Arts, Bachelor of Science in Engineering, Bachelor of Social Work, Bachelor of Science in Nursing and Master of Education degrees. Wikipedia.
News Article | April 6, 2016
Bothell, WA — Silicon Mechanics, a provider of servers, storage and high-performance computing solutions, announced the recipients of its fifth annual Research Cluster Grant (RCG); the University of New Orleans and the University of California, Merced. Each grant awardee will receive a high-performance computing (HPC) cluster with the latest high-performance processing and GPU technologies, valued at over $100,000 for use in demonstrated research purposes going forward. This is the second year that Silicon Mechanics has made the award to two institutions. Since 2012, when Silicon Mechanics initiated the RCG, the program has extended its reach considerably, providing over $500,000 worth of much needed technology advancements to universities and institutions where access to important research funding to acquire high-performance computing technology has become more difficult in recent years. “Being part of a program which provides cluster technology to help positively impact research efforts is why we started this five years ago. Providing a solution to these universities where access to high-performance computing was either limited, outdated or was not previously available is ultimately what the RCG is all about,” said Art Mann, Silicon Mechanics’ Sr. Director, Life Sciences Practice. “Knowing we are helping to advance collaboration between university departments and researchers, and being able to look down the road at the advancements and findings these institutions are targeting is very exciting.” "We are happy to continue to support this program and provide the universities with leading EDR 100Gb/s InfiniBand interconnect technology," said Scot Schultz, director of HPC and technical computing at Mellanox Technologies. "The Research Cluster Grant supports HPC education with technologies that are state-of-the-art, and also provides a spring-board for enhancing skills that are in high demand in the industry." At the University of New Orleans, the HPC cluster will be used to build on the strengths of the medicinal chemistry, cyber security, advanced materials design, information assurance and computational biology programs featured at the university. The HPC equipment will improve research in big data analytical methods for cyber security and digital forensic purposes, the development of GPU-accelerated tools for computational chemistry, cyber-security and bioinformatics, and university resources using dockers and containers to solve scientific problems. “The cluster will be a boon to our research,” said Dhruva Chakravorty, assistant professor of chemistry at UNO, the lead investigator on the grant proposal. “We will be able to process data at rates that previously would not have been possible. It will also enable us to analyze data up to 20 times faster. We expect this cluster to help us remain competitive for federal and state grants in the years to come.” At the University of California, Merced, the HPC cluster will provide the university a variety of scientific research and training opportunities, including the capacity to train a diverse population of undergraduate and graduate students on a full set of computational skills needed to be competitive in the job market as independent researchers. “This cluster will help propel our science and engineering research forward in exciting new directions. An in-house cluster will also help train our graduate students to strategically use high-performance computing resources such as the parallel processing capabilities of GPUs,” said Christine Isborn, assistant professor in chemistry and chemical biology, who wrote the grant proposal. “I also foresee using the cluster in my computational chemistry undergraduate course.” Previous RCG awardees include both Dordt College and City College of New York (CCNY) in 2015, Wayne State University in 2014, Tufts University in 2013 and Saint Louis University in 2012. Silicon Mechanics’ partners that have donated product to this year’s grant include
News Article | November 17, 2015
Austin, TX — Silicon Mechanics, a provider of servers, storage and high-performance computing solutions, announced the opening of its 5th Annual Research Cluster Grant (RCG) program at Supercomputing 2015. Two institutions will be selected, and both will be awarded a complete high-performance computing (HPC) cluster. The competition is open to all United States and Canadian qualified post-secondary institutions, university-affiliated research institutions, non-profit research institutions, and researchers at federal labs with university affiliations. "We designed the Research Cluster Grant program to provide computational and storage technology resources to researchers who may not have been able to keep pace with technology acquisitions through traditional grant-funding programs like those at the National Science Foundation or the National Institute of Health,” said Art Mann, Silicon Mechanics' Sr. Director, Life Sciences Practice. "With the ever-growing demand for more powerful IT infrastructure to support research, the RCG represents a tremendous opportunity to work with our technology partners and support these research efforts. I’m excited and truly honored to see the RCG program achieve its fifth year.” Silicon Mechanics created the RCG in 2012 as a way of giving back to the educational community, as obtaining needed research funding for technology advancements continues to be challenging and can limit future impact at some educational institutions. In particular, the program is helping to jumpstart research efforts where access to high-performance computing is limited, outdated or was not previously available. The RCG program also provides institutions with an opportunity to showcase how collaboration across departments and researchers by providing cluster technology can positively impact research efforts through the use of cluster technology. Previous RCG awardees include The City College of New York (CCNY) and Dordt College in 2015, Wayne State University in 2014, Tufts University in 2013 and Saint Louis University in 2012. Silicon Mechanics' partners currently committed to supporting this year’s grant include: Intel, NVIDIA, Mellanox, Supermicro, Bright Computing, HGST, Avago, Kingston, Micron and Seagate. At CCNY, the HPC cluster is being used for cutting-edge research in biochemistry, chemistry, biology, physics, earth and atmospheric sciences, computer science, engineering, medicine, mathematics, social science, humanities and writing pedagogy. "For many of our research programs, this computer cluster was the missing piece that lowered the barriers that kept our work from moving forward smoothly," said David Jeruzalmi, professor of chemistry and biochemistry in CCNY's Division of Science, who wrote the grant proposal last year. "This award has touched the research of many colleagues by bringing together researchers from across CCNY, many of whom never knew that their work could be positively impacted by colleagues down the hall or in the next building over." At Dordt College and at its research partner, Hope College, the HPC cluster supports eight STEM-based research groups and nine distinct faculty members focused on a wide variety of research activities. Those activities include bacterial statistical genetics, processing and analysis of RNA sequencing, phylogenetic trees, computational chemistry, engineering integrity, analyzing genomic sequencing data, population genetic data and more. "Dordt has traditionally been a liberal arts school," said Dr. Nathan Tintle, Dordt College's Director for Research and Scholarship. "In recent years, however, we have ramped up our research department in partnership with Hope College and, in doing so, created a demand for an HPC system. Unfortunately, we didn’t have the budget to purchase a cluster that would suit our computational needs. Fortunately, Silicon Mechanics offered the annual RCG, a program that we are proud to be involved with. We feel fortunate to have been awarded this grant." Submissions for the 2016 RCG will be accepted December 15, 2015, through March 1, 2016. The grant recipients will be announced April 2016. Submissions will be reviewed for merit and for the potential impact the research may have on the institution's mission. Silicon Mechanics strongly encourages collaboration, within and across departments of a single institution, or across multiple institutions. Details on RCG rules, application requirements, and cluster technical specifications are available at www.researchclustergrant.com. About The City College of New York Since 1847, The City College of New York has provided low-cost, high-quality education for New Yorkers in a wide variety of disciplines. More than 16,000 students pursue undergraduate and graduate degrees in: the College of Liberal Arts and Sciences; the Bernard and Anne Spitzer School of Architecture; the School of Education; the Grove School of Engineering; the Sophie Davis School of Biomedical Education, and the Colin Powell School for Civic and Global Leadership. Dordt College is a private institution of higher education, committed to the Reformed Christian perspective. With 1,400 students, the college’s STEM programs are leading enrollment growth. Located in Sioux Center, Iowa, Dordt College provides a holistic residential learning experience for students, in which they can develop Christian insight in all areas of life.
News Article | February 28, 2017
The Community for Accredited Online Schools, a leading resource provider for higher education information, has ranked the best colleges and universities with online programs in the state of Iowa for 2017. Of the 17 four-year schools that were ranked, University of Iowa, Iowa State University, Buena Vista University, Saint Ambrose University and University of Northern Iowa came in as the top five institutions. Iowa’s top 14 two-year schools were also included, with Western Iowa Tech Community, Kirkwood Community College, Iowa Lakes Community College, Eastern Iowa Community College and Des Moines Area Community College taking the top five spots. “By 2025, 68 percent of all jobs in Iowa will require postsecondary training or education, according to research from the Iowa College Student Aid Commission,” said Doug Jones, CEO and founder of AccreditedSchoolsOnline.org. “The online programs at schools on our list provide the best opportunities for students to meet their educational and career goals.” To earn a spot on the Best Online Schools list, Iowa colleges and universities must be institutionally accredited, public or private not-for-profit entities and have a minimum of one online certificate or degree program. Each college is also scored based on more than a dozen unique data points that include graduation rates, student/teacher ratios, employment services and financial aid availability. For more details on where each school falls in the rankings and the data and methodology used to determine the lists, visit: The Best Online Four-Year Schools in Iowa for 2017 include the following: Allen College Briar Cliff University Buena Vista University Dordt College Graceland University-Lamoni Iowa State University Iowa Wesleyan University Maharishi University of Management Morningside College Mount Mercy University Northwestern College Saint Ambrose University University of Dubuque University of Iowa University of Northern Iowa Upper Iowa University William Penn University Iowa’s Best Online Two-Year Schools for 2017 include the following: Des Moines Area Community College Eastern Iowa Community College District Ellsworth Community College Hawkeye Community College Indian Hills Community College Iowa Central Community College Iowa Lakes Community College Kirkwood Community College Marshalltown Community College Northeast Iowa Community College-Calmar Northwest Iowa Community College Southeastern Community College Southwestern Community College Western Iowa Tech Community College ### About Us: AccreditedSchoolsOnline.org was founded in 2011 to provide students and parents with quality data and information about pursuing an affordable, quality education that has been certified by an accrediting agency. Our community resource materials and tools span topics such as college accreditation, financial aid, opportunities available to veterans, people with disabilities, as well as online learning resources. We feature higher education institutions that have developed online learning programs that include highly trained faculty, new technology and resources, and online support services to help students achieve educational success.
News Article | November 14, 2016
Philanthropy drives industry collaboration through donation of a high-performance computing cluster; Award recipient to be announced in April 2017 SALT LAKE CITY, UT--(Marketwired - Nov 14, 2016) - Supercomputing, booth #1907 - Silicon Mechanics, a leading provider of servers, storage and high-performance computing solutions to the world's most innovative organizations, announced today at Supercomputing 2016 the call to entry for its 6th Annual Research Cluster Grant (RCG) program. The competition is open to all United States and Canadian qualified post-secondary institutions, university-affiliated research institutions, non-profit research institutions, and researchers at federal labs with university affiliations. One institution will be selected and awarded a complete high-performance computing (HPC) cluster. "We and our program partners are excited to begin the search for our 9th Research Cluster Grant recipient, in our sixth year of this program," said Art Mann, Silicon Mechanics' Sr. Director of Education and Research Practice. "Through this program, our past awardees have accelerated a wide array of research in medicine, genetics, energy, and more. We know this critical HPC cluster will enable important research for a deserving new awardee in 2017." Silicon Mechanics created the RCG in 2012 as a way of giving back to the educational community, as obtaining needed research funding for technology advancements continues to be challenging and can limit future impact at some educational institutions. In particular, the program is helping to jumpstart research efforts where access to high-performance computing is limited, outdated or was not previously available. The RCG program also provides institutions with an opportunity to showcase how collaboration across departments and researchers by providing cluster technology can positively impact research efforts through the use of cluster technology. Previous RCG awardees include: The University of New Orleans (UNO) and The University of California, Merced in 2016; The City College of New York (CCNY) and Dordt College in 2015; Wayne State University in 2014; Tufts University in 2013; and Saint Louis University in 2012. Silicon Mechanics' partners currently committed to supporting this year's grant include: Intel, NVIDIA, Mellanox, Supermicro, Bright Computing, HGST, Broadcom, Sandisk, Micron, and Seagate. At the University of New Orleans, the HPC cluster it was awarded last year is being used to build on the strengths of the medicinal chemistry, cyber security, advanced materials design, information assurance and computational biology programs featured at the university. The HPC equipment is helping improve research in: big data analytical methods for cyber security and digital forensic purposes; the development of GPU-accelerated tools for computational chemistry, cyber-security and bioinformatics; and university resources using dockers and containers to solve scientific problems. "The cluster has been a boon to our research," said Dhruva Chakravorty, assistant professor of chemistry at UNO, and the lead investigator on last year's awarded grant proposal. "We are now able to process data at rates that previously would not have been possible. It also enables us to analyze data up to 20 times faster. We fully expect this cluster to help us remain competitive for federal and state grants in the years to come." Submissions for the 2017 RCG will be accepted starting today through March 1, 2017. The grant recipient will be announced April 2017. Submissions will be reviewed for merit and for the potential impact the research may have on the institution's mission. Silicon Mechanics strongly encourages collaboration, within and across departments of a single institution, or across multiple institutions. Details on RCG rules, application requirements, and cluster technical specifications are available at www.researchclustergrant.com. About Silicon Mechanics Silicon Mechanics, Inc., is a leading provider of servers, storage and high-performance computing technologies to the world's most innovative organizations. Since 2001 Silicon Mechanics has supported customers with its "Expert included" approach, reflecting the company's passion for providing complete customer satisfaction and customer confidence in the return on their technology investments. Recognized as one of the fastest growing companies in the greater Seattle technology corridor, Silicon Mechanics is changing the way systems providers engage with customers. To learn more, please click here. About UNO The University of New Orleans (UNO) is a major research university in one of the world's most fascinating cities. For more than 50 years, it has been one of the city's foremost public resources, offering a diverse set of world-class, research-based programs, advancing shared knowledge and adding to the city's industry, culture and economy. Since 1958, UNO has educated students from all 64 Louisiana parishes, all 50 states in the United States and more than 130 countries. Today UNO offers more than 40 undergraduate and pre-professional programs and more than 40 graduate programs. For more information, visit www.uno.edu.
Agency: NSF | Branch: Standard Grant | Program: | Phase: IUSE | Award Amount: 299.99K | Year: 2016
Demands for a statistically literate society are increasing, and the algebra-based introductory statistics course remains the primary venue for learning statistics for the majority of high school and undergraduate students. However, the typical introductory statistics course does not give students experience with multivariable statistical methods, which are the primary methods used in the workforce today. The primary barrier to students progressing beyond their first statistics course is that they have not yet taken (or do not intend to take) prerequisite courses in probability, calculus, and/or linear algebra. Toward increasing the number of students who take a statistics course that focuses on multivariable methods, this project will develop, pilot-test, and study the use of materials for an algebra-based second course. These materials will (1) emphasize the overarching statistical process in the context of multivariable hypotheses, (2) start with straightforward multivariable study design and exploratory data analysis concepts to build on student intuition and understanding, (3) utilize a writing style and pedagogical approach designed for the typical undergraduate student, (4) develop and integrate technology tools for facilitating student exploration and discovery, and (5) be informed by assessment results.
The proposed project will provide college faculty with a fully integrated set of curriculum materials to teach a substantially different curriculum for a second course in statistics, aimed at important multivariable statistical concepts. Such concepts include minimizing unexplained variability, planning and controlling for confounding variables, and exploring and modelling interactions between variables. These materials will leverage prior support that produced materials for introductory statistics centered on simulation-based inference. The projects accompanying assessment activities, development of a new assessment tool (a Multivariable Statistics Concept Inventory), and examination of student assessment results, will address research questions such as (1) In which areas of multivariable statistical thinking are there significant gains in conceptual understanding using this new curriculum? and (2) What are the characteristics of students learning trajectories for key inferential and descriptive statistics concepts?
Agency: NSF | Branch: Standard Grant | Program: | Phase: S-STEM:SCHLR SCI TECH ENG&MATH | Award Amount: 550.10K | Year: 2014
This PI team is working on two complementary fronts to increase the adoption of a new randomization-based curricula for introductory statistics that emphasizes: i) the core logic of inference using randomization-based methods alongside an intuitive, cyclical, active-learning pedagogy, and ii) the overall process of statistical investigations, from asking questions and collecting data through making inferences and drawing conclusions. The first front involves: a) conducting a series of twelve 1-4 day professional development workshops, and b) developing and supporting an online learning community to provide on-going support beyond the workshops. An important aspect of the intellectual merit of the project lies in the second front which involves the evaluation of widespread transferability of the model curriculum and research to deepen understanding of students attitudes, conceptual understanding, and learning trajectories within the curriculum. Together with the workshop participants, developers, and other faculty, the team is gathering a large and diverse set of attitudinal and conceptual assessment data from over 3000 students at a variety of institutions. In-depth qualitative and quantitative assessments of students developmental learning trajectories on key concepts are being carried out. The project is exercising broader impacts not only through its planned workshops, but also through coordination of its efforts through the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE), which serves as the primary hub of activity for transformational efforts in statistics education.
Agency: NSF | Branch: Standard Grant | Program: | Phase: PLANETARY ASTRONOMY | Award Amount: 55.69K | Year: 2013
This collaborative project is a theoretical effort to model cloudy atmospheres of extrasolar planets. The models will be constrained by direct images of exoplanets produced by the Gemini Planet Imager (GPI) and other surveys. The researchers will focus on non-equilibrium chemistry, cloud physics, atmospheric structure and predict emission spectra of the planets. They will also use the direct imaging data to determine atmospheric effective temperature, surface gravity and composition.
Broader impacts include contributions to university public web pages on science topics, videos called Science Bulletin Features produced by the American Museum of Natural History, and mentoring and supervising a female graduate student in her Ph.D. dissertation research.
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 181.48K | Year: 2012
The algebra-based introductory statistics course has seen tremendous growth in enrollments over the last two decades using a consensus curriculum and sequencing of topics. However, research has also shown students typically leave these courses with a shallow understanding of key inferential ideas. Recently, many statistics educators have proposed moving from this traditional curriculum to one centered on computer-intensive, randomization-based inference methods. Two advantages of this approach are: (1) randomization methods enable students to focus on the core logic of inference, and (2) efficiency in presentation allows students to gain experience in computer-intensive and multivariable methods that are being increasingly used by applied researchers. This project is providing instructors with a fully integrated set of curriculum materials with which to teach a substantially different curriculum that introduces statistical inference from the start. The materials are undergoing class-testing at numerous institutions and being disseminated through publication as a textbook, workshops, and presentations. The accompanying evaluation component is providing information about potential gains in student understanding of core concepts of inference and documentation of how students develop skills of inferential reasoning. These curricular materials and assessment findings have the potential for effecting a substantial change in the content and focus of introductory statistics courses across the country.
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 248.65K | Year: 2013
Recent breakthroughs in genetic sequencing technology have set the stage for an unprecedented wide understanding of all microbial life. Previously, automated methods for the creation of genome-scale metabolic models (MMs) have been developed and applied by this group. These methods have since been applied to thousands of microbial genomes in freely available online software systems. While the MMs are yielding unprecedented insights into microbial metabolism, the next great challenge is to capture gene regulatory information in order to more accurately model the metabolic response of an organism to its environment. Anticipating this need, ongoing efforts by the group have set the stage for integrating a wide range of alternative data sources with the thousands of MMs. The group is now uniquely positioned to develop enhanced MMs through the integration of regulatory information into the models, yielding integrated metabolic, regulatory models (iMRMs). To date, little methodological effort has been directed toward the wide-scale development of iMRMs due, in part, to the lack of sufficient and integrated data for most organisms. This project will (1) develop new and improved iMRMs by addressing methodological weaknesses in current approaches, (2) develop methods to utilize iMRMs to predict conditions for wet-lab experiments to generate and test novel biological hypotheses, (3) develop novel approaches to use thousands of models to better understand metabolic and regulatory diversity, and (4) fully incorporate undergraduate and high school students in all aspects of the research. Thus, the project will substantially advance the capacity to construct integrated metabolic regulatory models through the development and evaluation of methods for the incorporation of regulatory data, produce tools for researchers to assess the diversity of existing gene expression data sets for their organisms of interest, validate proposed methods via targeted wet lab experiments, and address fundamental questions about metabolic and regulatory diversity across the microbial tree of life.
All methodological advancements will be integrated into an open-source software environment for modeling microbial life. At least 21 undergraduate and at least 60 high school students will be integrally involved in the research, providing them with training, experience and exposure to the interdisciplinary field of quantitative approaches for predictive systems biology.
Agency: NSF | Branch: Standard Grant | Program: | Phase: RSCH EXPER FOR UNDERGRAD SITES | Award Amount: 355.30K | Year: 2016
This project is funded from the Research Experiences for Undergraduates (REU) Sites program in the SBE Directorate, with joint support and funding from the NSF Office of International Science and Engineering (OISE). As an REU Site with international activities, it has both scientific and societal benefits, and it integrates research and education at multiple levels. The research in this program involves mental health, from a social/behavioral science perspective. Long-term effects of deep-rooted tensions in any country and within any population can include political upheaval, socio-economic disadvantages, ethnic discord and rapid change from one economic system to another; all these factors can have an effect on the rates of mental illness in that population. This REU Sites research program directly impacts a group of 27 undergraduate students over a three year period by broadening students global awareness and cross-cultural competence through a meaningful, interdisciplinary research experience focusing on a case study for elevated levels of mental illness in a country that has been going through multiple transitions. The case study is Ukraine in post-Soviet era. As part of this REU site, a diverse group of undergraduate students are involved in an ongoing research project exploring the mental health of Ukrainian citizens. In this REU site the PI-team recruits students with an emphasis on the participation of students participants from under-represented groups and institutions where research opportunities are limited. These students will further broaden the impact of their research experience by presenting to high school students and students at their home institutions.
This REU site is focused on a topic of research that is of great interest in the fields of sociology and social psychology. The program incorporates an on-site collaborative research and cultural immersion experience for students in Ukraine, working directly with collaborators at the Kiev International Institute of Sociology (a national research firm in Ukraine). The project provides strong mentorship and development of undergraduate student researchers by an interdisciplinary team of four experienced faculty members, in conjunction with a team of worldwide experts on Ukraine mental health and, and it provides some of the only nationally representative information on mental health risk factors and impacts in Ukraine. The dataset students will be able to use in this project is innovative and unique in the fields of psychology and global health studies. Analyzing these types of global data as a means of training students for future work in psychology and/or health studies means that the work itself has intellectual merit, but that inasmuch as this affects future generations of scholars, it also has long-term impact on the fields. Making American students aware of the cultural biases they bring to the table when analyzing global data is crucial for producing good future science. This project is co-funded by the NSF Office of International Science and Engineering.