Emulating the Wright State Model for Engineering Mathematics Education: Improving First-Year Engineering Student Retention

In 2004, Wright State University developed an innovative mathematics course for first-year engineering undergraduates in order to increase student retention, motivation and academic success. To date, the Wright State model has had a positive impact on student retention, motivation and academic success by increasing graduation rates and GPAs among participants. During the fall of 2014 and 2015, one large public university in the Midwest with more selective admission criteria decided to pilot a course based on the Wright State Model for Engineering Mathematics Education. Using the Wright State model, a mathematics for engineering course was offered to prospective students so they could subsequently begin engineering classes without a traditional calculus prerequisite. Each semester, a cohort of 31 first-year engineering students enrolled in the course. Instructors distributed surveys to students at the beginning and end of each term. In addition, university administrators tracked student grades in subsequent math and engineering courses. This paper will outline the details of the course as well as the academic performance and retention of these students. Preliminary findings suggest first to second year retention is higher with students who have taken the mathematics for engineering course. First-year students who take the course also earn higher grades in algebra, trigonometry, and introductory engineering courses, but not in Calculus I

Use of outcomes to evaluate surveillance systems for bioterrorist attacks

<p>Abstract</p> <p>Background</p> <p>Syndromic surveillance systems can potentially be used to detect a bioterrorist attack earlier than traditional surveillance, by virtue of their near real-time analysis of relevant data. Receiver operator characteristic (ROC) curve analysis using the area under the curve (AUC) as a comparison metric has been recommended as a practical evaluation tool for syndromic surveillance systems, yet traditional ROC curves do not account for timeliness of detection or subsequent time-dependent health outcomes.</p> <p>Methods</p> <p>Using a decision-analytic approach, we predicted outcomes, measured in lives, quality adjusted life years (QALYs), and costs, for a series of simulated bioterrorist attacks. We then evaluated seven detection algorithms applied to syndromic surveillance data using outcomes-weighted ROC curves compared to simple ROC curves and timeliness-weighted ROC curves. We performed sensitivity analyses by varying the model inputs between best and worst case scenarios and by applying different methods of AUC calculation.</p> <p>Results</p> <p>The decision analytic model results indicate that if a surveillance system was successful in detecting an attack, and measures were immediately taken to deliver treatment to the population, the lives, QALYs and dollars lost could be reduced considerably. The ROC curve analysis shows that the incorporation of outcomes into the evaluation metric has an important effect on the apparent performance of the surveillance systems. The relative order of performance is also heavily dependent on the choice of AUC calculation method.</p> <p>Conclusions</p> <p>This study demonstrates the importance of accounting for mortality, morbidity and costs in the evaluation of syndromic surveillance systems. Incorporating these outcomes into the ROC curve analysis allows for more accurate identification of the optimal method for signaling a possible bioterrorist attack. In addition, the parameters used to construct an ROC curve should be given careful consideration.</p

The Relationship Between Classroom Assessment Practices and Student Motivation and Engagement: A Literature Review

Assessment is becoming increasingly important in classrooms as school systems respond to federal and state testing mandates. The increasing emphasis on assessment surely impacts student outcomes such as engagement and motivation, and ultimately achievement. While it is clear that classroom assessment is receiving more attention as a critical component of teaching that directly affects student learning, there is still a lack of systematic research that addresses many classroom assessment issues. There is some evidence that effective formative assessment enhances achievement (Black & William, 1998) and that curtain grading practices result in greater student motivation and achievement (Brookhart, 2004b). However, researchers have not sufficiently investigated how classroom assessment and grading practices should be categorized, and have not demonstrated strong relationships between these practices and student self-efficacy and motivation at different grade levels

The Relationship between Classroom Assessment Practices and Student Motivation and Engagement

Assessment is becoming increasingly important in classrooms as school systems respond to federal and state testing mandates. The increasing emphasis on assessment surely impacts student outcomes such as engagement and motivation, and ultimately achievement. While it is clear that classroom assessment is receiving more attention as a critical component of teaching that directly affects student learning, there is still a lack of systematic research that addresses many classroom assessment issues. There is some evidence that effective formative assessment enhances achievement (Black & Williams 1998), and that certain grading practices result in greater student motivation and achievement (Brookhart, 2004b). However, researchers have not sufficiently investigated how classroom assessment and grading practices should be categorized, and have not demonstrated strong relationships between these practices and student self-efficacy and motivation at different grade levels

The groupoid approach to Leavitt path algebras

When the theory of Leavitt path algebras was already quite advanced, it was discovered that some of the more difficult questions were susceptible to a new approach using topological groupoids. The main result that makes this possible is that the Leavitt path algebra of a graph is graded isomorphic to the Steinberg algebra of the graph’s boundary path groupoid. This expository paper has three parts: Part 1 is on the Steinberg algebra of a groupoid, Part 2 is on the path space and boundary path groupoid of a graph, and Part 3 is on the Leavitt path algebra of a graph. It is a self-contained reference on these topics, intended to be useful to beginners and experts alike. While revisiting the fundamentals, we prove some results in greater generality than can be found elsewhere, including the uniqueness theorems for Leavitt path algebras

The impact of exposure misclassification on associations between prepregnancy body mass index and adverse pregnancy outcomes

Prepregnancy body mass index (BMI) is a widely used marker of maternal nutritional status that relies on maternal self-report of prepregnancy weight and height. Pregravid BMI has been associated with adverse health outcomes for the mother and infant, but the impact of BMI misclassification on measures of effect has not been quantified. The authors applied published probabilistic bias analysis methods to quantify the impact of exposure misclassification bias on well-established associations between self-reported prepregnancy BMI category and five pregnancy outcomes (small- and large-for gestational age birth (SGA; LGA), spontaneous preterm birth (sPTB), gestational diabetes (GDM), and preeclampsia) derived from a hospital-based delivery database in Pittsburgh, PA (2003-2005; n=18 362). The bias analysis method recreates the data that would have been observed had BMI been correctly classified, assuming given classification parameters. The point estimates derived from the bias analysis account for random error as well as systematic error caused by exposure misclassification bias and additional uncertainty contributed by classification errors. In conventional multivariable logistic regression models, underweight women were at increased risk of SGA and sPTB, and reduced risk of LGA, while overweight, obese, and severely obese women had elevated risks of LGA, GDM, and preeclampsia compared with normal-weight women. After applying the probabilistic bias analysis method, adjusted point estimates were attenuated, indicating the conventional estimates were biased away from the null. However, the majority of relations remained readily apparent. This analysis suggests that in this population, associations between self-reported prepregnancy BMI and pregnancy outcomes are slightly overestimated

The impact of setting a pregnancy weight gain goal on total weight gain

Background: Expert groups recommend that women set a pregnancy weight gain goal with their care provider to optimise weight gain. Objective: Our aim was to describe the concordance between first-trimester personal and provider pregnancy weight gain goals with the Institute of Medicine (IOM) recommendations and to determine the association between these goals and total weight gain. Methods: We used data from 9353 women in the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be. In the first trimester, women reported their personal pregnancy weight gain goal and their provider weight gain goal, and we categorised personal and provider weight gain goals and total weight gain according to IOM recommendations. We used log-binomial or linear regression models to relate goals to total weight gain, adjusting for confounders including race/ethnicity, maternal age, education, smoking, marital status and planned pregnancy. Results: Approximately 37% of women reported no weight gain goals, while 24% had personal and provider goals, 31% had only a personal goal, and 8% had only a provider goal. Personal and provider goals were outside the recommended ranges in 12%-23% of normal-weight women, 31%-41% of overweight women and 47%-63% of women with obesity. Women with both personal and provider pregnancy weight gain goals were 6%-14% more likely than their counterparts to have a goal within IOM-recommended ranges. Having any goal or a goal within the IOM-recommended ranges was unrelated to pregnancy weight gain. Excessive weight gain occurred in approximately half of normal-weight or obese women and three-quarters of overweight women, regardless of goal setting group. Conclusions: These findings do not support the effectiveness of early-pregnancy personal or provider gestational weight gain goal setting alone in optimising weight gain. Multifaceted interventions that address a number of mediators of goal setting success may assist women in achieving weight gain consistent with their goals

Multiplicity Studies and Effective Energy in ALICE at the LHC

In this work we explore the possibility to perform ``effective energy'' studies in very high energy collisions at the CERN Large Hadron Collider (LHC). In particular, we focus on the possibility to measure in $pp$ collisions the average charged multiplicity as a function of the effective energy with the ALICE experiment, using its capability to measure the energy of the leading baryons with the Zero Degree Calorimeters. Analyses of this kind have been done at lower centre--of--mass energies and have shown that, once the appropriate kinematic variables are chosen, particle production is characterized by universal properties: no matter the nature of the interacting particles, the final states have identical features. Assuming that this universality picture can be extended to {\it ion--ion} collisions, as suggested by recent results from RHIC experiments, a novel approach based on the scaling hypothesis for limiting fragmentation has been used to derive the expected charged event multiplicity in $AA$ interactions at LHC. This leads to scenarios where the multiplicity is significantly lower compared to most of the predictions from the models currently used to describe high energy $AA$ collisions. A mean charged multiplicity of about 1000-2000 per rapidity unit (at $\eta \sim 0$) is expected for the most central $Pb-Pb$ collisions at $\sqrt{s_{NN}} = 5.5 TeV$.Comment: 12 pages, 19 figures. In memory of A. Smirnitski

\'Etale groupoids and Steinberg algebras, a concise introduction

We give a concise introduction to (discrete) algebras arising from \'etale groupoids, (aka Steinberg algebras) and describe their close relationship with groupoid C*-algebras. Their connection to partial group rings via inverse semigroups also explored

Impacts of meeting minimum access on critical earth systems amidst the Great Inequality

The Sustainable Development Goals aim to improve access to resources and services, reduce environmental degradation, eradicate poverty and reduce inequality. However, the magnitude of the environmental burden that would arise from meeting the needs of the poorest is under debate—especially when compared to much larger burdens from the rich. We show that the ‘Great Acceleration’ of human impacts was characterized by a ‘Great Inequality’ in using and damaging the environment. We then operationalize ‘just access’ to minimum energy, water, food and infrastructure. We show that achieving just access in 2018, with existing inequalities, technologies and behaviours, would have produced 2–26% additional impacts on the Earth’s natural systems of climate, water, land and nutrients—thus further crossing planetary boundaries. These hypothetical impacts, caused by about a third of humanity, equalled those caused by the wealthiest 1–4%. Technological and behavioural changes thus far, while important, did not deliver just access within a stable Earth system. Achieving these goals therefore calls for a radical redistribution of resources