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Needham, MA, United States

The Franklin W. Olin College of Engineering is a private undergraduate engineering college located in Needham, Massachusetts , adjacent to Babson College. Olin College is noted in the engineering community for its youth, small size, project-based curriculum, and large endowment funded primarily by the F. W. Olin Foundation. The College currently awards the half-tuition Olin Scholarship to each admitted student.The college was accredited by the regional accreditation board NEASC on December 6, 2006. Olin's degree programs in Electrical/Computer Engineering, Mechanical Engineering, and Engineering received accreditation from the Engineering Accreditation Commission of Accreditation Board for Engineering and Technology on August 31, 2007. Wikipedia.

Bazant M.Z.,Massachusetts Institute of Technology | Storey B.D.,Franklin W. Olin College Of Engineering | Kornyshev A.A.,Imperial College London
Physical Review Letters | Year: 2011

We develop a simple Landau-Ginzburg-type continuum theory of solvent-free ionic liquids and use it to predict the structure of the electrical double layer. The model captures overscreening from short-range correlations, dominant at small voltages, and steric constraints of finite ion sizes, which prevail at large voltages. Increasing the voltage gradually suppresses overscreening in favor of the crowding of counterions in a condensed inner layer near the electrode. This prediction, the ion profiles, and the capacitance-voltage dependence are consistent with recent computer simulations and experiments on room-temperature ionic liquids, using a correlation length of order the ion size. © 2011 American Physical Society.

Storey B.D.,Franklin W. Olin College Of Engineering | Bazant M.Z.,Massachusetts Institute of Technology
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2012

The classical theory of electrokinetic phenomena is based on the mean-field approximation that the electric field acting on an individual ion is self-consistently determined by the local mean charge density. This paper considers situations, such as concentrated electrolytes, multivalent electrolytes, or solvent-free ionic liquids, where the mean-field approximation breaks down. A fourth-order modified Poisson equation is developed that captures the essential features in a simple continuum framework. The model is derived as a gradient approximation for nonlocal electrostatics of interacting effective charges, where the permittivity becomes a differential operator, scaled by a correlation length. The theory is able to capture subtle aspects of molecular simulations and allows for simple calculations of electrokinetic flows in correlated ionic fluids. Charge-density oscillations tend to reduce electro-osmotic flow and streaming current, and overscreening of surface charge can lead to flow reversal. These effects also help to explain the suppression of induced-charge electrokinetic phenomena at high salt concentrations. © 2012 American Physical Society.

Agency: NSF | Branch: Standard Grant | Program: | Phase: TUES-Type 2 Project | Award Amount: 479.95K | Year: 2013

Building on prior work in motivation, this project is collecting and analyzing quantitative and qualitative data to improve the capability to characterize and explain key characteristics of student motivation in diverse undergraduate courses required for engineering education. This project is engaging instructors in the process of interpreting student motivation data, coupling these research data to motivation theory and course design, and developing course revisions aimed at enhancing STEM students intrinsic drive.

Intellectual Merit
This research rests on prior research that shows that instructors can directly influence student motivation, particularly intrinsic motivation, through their course design decisions. To capitalize on the potential of this relationship, instructors need both a more nuanced understanding of the types of student motivations for learning and access to clearer methods for translating theory and empirical data to course-level insights. This project is measuring individual student responses to diverse STEM environments, pedagogies, and assignments. The temporal evolution of these responses is a focal point in the development of transferable research and generalizable theories for STEM student motivational drive.

The analysis of motivation data in more nuanced ways examines general trends in motivation by course activity, year of study, and gender. Motivation is dynamic and susceptible to frequent and sometimes rapid change. The analysis uses group-based clustering techniques to discover the strength, persistence, and distribution of different types of motivational responses. It employs qualitative analyses to explain the relationships between motivation and the learning environment and elucidate gendered differences in motivation. Using both variable- and cluster-based analyses in multiple course analyses has promise in developing better understanding of the impact of instructional design on effective practice.

The National Academy of Engineering exhorts us to prepare STEM graduates with the tools needed for the world as it will be, not as it is today. Among these tools are creativity, critical thinking, resiliency, flexibility, and self-regulation. Educational research suggests that improved understanding of learner motivation is important to facilitate a systemic shift toward these high-level outcomes. However, a large gap remains between the research-based understanding of student motivation, and the application of those research insights to day-to-day classroom practice.

The output from this project will have an immediate impact on over 20 STEM instructors at the 8 participating institutions, by highlighting activities that prompt different motivational responses and motivational shifts, explaining motivation-environment interactions, and by enabling instructors to use research data to make informed and strategic choices to better encourage self-determined behaviors. The project expands the pool of STEM faculty who can make informed, data-driven decisions by engaging early-career faculty and those with limited prior involvement in STEM educational reform.

Agency: NSF | Branch: Standard Grant | Program: | Phase: IUSE | Award Amount: 63.56K | Year: 2015

Computation in all its definitions (Computer Science, Computing, Computational Thinking, etc.) is becoming increasingly significant in STEM and non-STEM disciplines. Historically, Mathematics has been the discipline seen as required by all other disciplines. Computer Science faculty are wrestling with determining whether there is a single approach to infusing computation in other disciplines or whether there are many approaches. Coupled with the increased computational ability of students in other disciplines, it is known that interdisciplinary courses are more appealing to underrepresented groups. Ideally, the Computer Science community would be provided with a set of validated approaches to interdisciplinary education. In order to reach this goal, the community must investigate the educational value of various approaches. This workshop seeks to begin cataloging experiences to attain that goal.

In this collaborative proposal a number of PIs from different college level institutions (research university, technology focused university, four-year engineering college, and four-year liberal arts college) will cooperate on holding a workshop where a number of different approaches to cross-disciplinary education will be investigated. This workshop will gather a number of faculty who have attempted such courses. The outcome will be a report that outlines approaches to computational interdisciplinary courses. This report will be made widely available.

Agency: NSF | Branch: Continuing grant | Program: | Phase: | Award Amount: 268.47K | Year: 2012

In this project, the PI will study the group behavior of photosynthetic bacteria that are growing in biofilms and in dense populations. The photosynthetic bacteria that are the subjects of this study, the anoxygenic phototroph Rhodopseudomonas palustris and the cyanobacterium Synechocystis sp. PCC6803, collectively carry out all major modes of metabolism that exist in the bacterial world. The PI will study the effects of different growth pressures on the pattern formation of these bacteria. The PI will grow and analyze the architecture of biofilms that are formed by photosynthetic bacteria which are growing in different metabolic modes. Mathematical models will be developed and compared to experiment to understand the physical principles that underlie the observed growth patterns. Experiments will also be performed to analyze in detail the collective motion of photosynthetic bacteria that are growing at high cell population densities, with system modifications inspired by photosynthetic biofilms. The research will explore a new range of parameter space for biologic pattern formation and collective bacterial motion, providing experimental evidence with which theoretical and simulational models may be compared. This research will be undertaken in an undergraduate-only institution and involves interdisciplinary faculty and student collaborations in applied physics and microbiology. Undergraduate students will be trained in techniques at the interface of these fields, will be co-authors on publications, and students will be expected to present results of this research at local and national meetings. The techniques and finding from this research will be used in the classroom in teaching of biology and physics, and the techniques developed and data obtained from this research will stimulate the development of future interdisciplinary courses.

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