Community Service and Critical Thinking: An Exploratory Analysis of Collegiate Influences

Interest in encouraging undergraduates to become involved in community service has grown rapidly over the past several years. In addition to the formation of groups such as the Campus Compact, this interest can be seen in the curricula of numerous colleges which have instituted community services requirements for graduation. Interest in critical thinking has increased as well, with widespread agreement among educators that critical thinking should be an important, if not central, goal of education. Although critical thinking has long been valued by educators at all (Siegel, 1980), the importance placed upon the development of critical thinking has recently been especially strong in colleges and universities and other institutions serving adult learners (Brookfield, 1987; Paul, 1985). Despite the centrality of critical thinking skills, a great many views exist as to how to best define (Ennis, 1986; Sternberg, 1985a) and develop (Sternberg, 1985b) critical thinking

Discovering Blind Spots in Reinforcement Learning

Agents trained in simulation may make errors in the real world due to mismatches between training and execution environments. These mistakes can be dangerous and difficult to discover because the agent cannot predict them a priori. We propose using oracle feedback to learn a predictive model of these blind spots to reduce costly errors in real-world applications. We focus on blind spots in reinforcement learning (RL) that occur due to incomplete state representation: The agent does not have the appropriate features to represent the true state of the world and thus cannot distinguish among numerous states. We formalize the problem of discovering blind spots in RL as a noisy supervised learning problem with class imbalance. We learn models to predict blind spots in unseen regions of the state space by combining techniques for label aggregation, calibration, and supervised learning. The models take into consideration noise emerging from different forms of oracle feedback, including demonstrations and corrections. We evaluate our approach on two domains and show that it achieves higher predictive performance than baseline methods, and that the learned model can be used to selectively query an oracle at execution time to prevent errors. We also empirically analyze the biases of various feedback types and how they influence the discovery of blind spots.Comment: To appear at AAMAS 201

Seeing the vibrational breathing of a single molecule through time-resolved coherent anti-Stokes Raman scattering

The motion of chemical bonds within molecules can be observed in real time, in the form of vibrational wavepackets prepared and interrogated through ultrafast nonlinear spectroscopy. Such nonlinear optical measurements are commonly performed on large ensembles of molecules, and as such, are limited to the extent that ensemble coherence can be maintained. Here, we describe vibrational wavepacket motion on single molecules, recorded through time-resolved, surface-enhanced, coherent anti-Stokes Raman scattering. The required sensitivity to detect the motion of a single molecule, under ambient conditions, is achieved by equipping the molecule with a dipolar nano-antenna (a gold dumbbell). In contrast with measurements in ensembles, the vibrational coherence on a single molecule does not dephase. It develops phase fluctuations with characteristic statistics. We present the time evolution of discretely sampled statistical states, and highlight the unique information content in the characteristic, early-time probability distribution function of the signal.Comment: 17 pages, 5 figure

Working with Low Survey Response Rates: The Efficacy of Weighting Adjustments

National data show a continuing decline in the willingness of people to respond to surveys. This trend is troubling given the central role that survey research plays in collecting data for institutional research purposes. This paper examines the effectiveness of a weighting procedure described by Astin and Molm for adjusting survey results to correct for nonresponse bias. Using data from a Cooperative Institutional Research Program (CIRP) follow-up survey, the results indicate that the weighting procedure is highly effective at reducing nonresponse bias in univariate distributions. The effectiveness of the weighting procedure in adjusting correlation and regression analyses is less clear. This may be due in part to the observation that even when individual variables are noticeably biased, their relationships with each other tend not to be.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43621/1/11162_2004_Article_424011.pd

Is Modeling of Freshman Engineering Success Different from Modeling of Non‐Engineering Success?

The engineering community has recognized the need for a higher retention rate in freshman engineering. If we are to increase the freshman retention rate, we need to better understand the characteristics of academic success for engineering students. One approach is to compare academic performance of engineering students to that of non‐engineering students. This study explores the differences in predicting academic success (defined as the first year GPA) for freshman engineering students compared to three non‐engineering student sectors (Pre‐Med, STEM, and non‐STEM disciplines) within a university. Academic success is predicted with pre‐college variables from the UCLA/CIRP survey using factor analysis and regression analysis. Except for the factor related to the high school GPA and rank, the predictors for each student sector were discipline specific. Predictors unique to the engineering sector included the factors related to quantitative skills (ACT Math and Science test scores and placement test scores) and confidence in quantitative skills.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95487/1/j.2168-9830.2008.tb00993.x.pd

College impact, student impact: A reconsideration of the role of students within American higher education

American college students tend to be viewed in terms of inputs and outcomes, due in part to the assessment movement and long-standing interest in college impact. A more complete view is one in which the relationship between students and the college environment is both reciprocal and dynamic. This ecological perspective portrays students as actively shaping their educational environments, with these environments simultaneously providing the potential for transforming the individual. Data from the Cooperative Institutional Research Program (CIRP) are used to explore the ecological perspective.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42837/1/10734_2005_Article_BF01384097.pd

Dismantling the Walls: Peer-Facilitated Inter-Race/Ethnic Dialogue Processes and Experiences

Also PCMA Working Paper #49.http://deepblue.lib.umich.edu/bitstream/2027.42/51296/1/532.pd