Relationships Between Achievement and Selective Variables in a Chemistry Course for Nonmajors

The main purpose of this study was to investigate the relationships between students' approaches to studying, prior knowledge, logical thinking ability, and gender and their performance in a nonmajors' college freshman chemistry course. Subjects for this study were 220 students (128 females and 92 males) enrolled in the second semester of a freshman chemistry course for nonmajors at a private university in New York State. Instruments used in this study included seven subscales of the Approaches to Studying Inventory and the Test of Logical Thinking (TOLT). The students' grades on an hour-long exam early in the semester were used as measures of the students' prior knowledge, while the semester cumulative final examination scores were used as measures of achievement in chemistry. Students in this study had slightly higher scores on reproducing orientation than on meaning orientation, a pattern that confirms Entwistle and Ramsden's (1983) findings with a similar group of nonmajors. The results of a stepwise multiple regression showed that prior knowledge, TOLT scores, and meaning orientation accounted for 32% of the variance on the final examination scores.     

Technological Tools in the Introductory Statistics Classroom: Effects on Student Understanding of Inferential Statistics

While technology has become an integral part of introductory statistics courses, the programs typically employed are professional packages designed primarily for data analysis rather than for learning. Findings from several studies suggest that use of such software in the introductory statistics classroom may not be very effective in helping students to build intuitions about the fundamental statistical ideas of sampling distribution and inferential statistics. The paper describes an instructional experiment which explored the capabilities of Fathom, one of several recently-developed packages explicitly designed to enhance learning. Findings from the study indicate that use of Fathom led students to the construction of a fairly coherent mental model of sampling distributions and other key concepts related to statistical inference. The insights gained point to a number of critical ingredients that statistics educators should consider when choosing statistical software. They also provide suggestions about how to approach the particularly challenging topic of statistical inference. This revised version was published online in July 2006 with corrections to the Cover Date.     

Collaborative Workshops and Student Academic Performance in Introductory College Mathematics Courses: A Study of a Treisman Model Math Excel Program

High failure rates in introductory college mathematics courses, particularly among underrepresented groups of students, have been of concern for many years. One approach to the problem experiencing some success has been Treisman's Emerging Scholars workshop model. The model involves supplemental workshops in which students solve problems in collaborative learning groups. This study reports on the effectiveness of Math Excel, an implementation of the Treisman model for introductory mathematics courses (college algebra, precalculus, differential calculus, and integral calculus) at Oregon State University over five academic terms. Regression analyses revealed a significant effect on achievement (.671 grade points on a 4‐point scale) favoring Math Excel students. Even after adjusting for prior mathematics achievement using linear regression with SAT‐M as predictor, Math Excel groups' grade averages were over half a grade point better than predicted (significant at the .001 level). This study provides supporting evidence that programs like Math Excel can help students in making a successful transition to college mathematics study.     

在微积分教学中如何处理好数学与物理相互渗透

通过一些具体例子,讨论在微积分教学过程中如何体现物理与数学的相互渗透.从而促进学生对微积分基本思想的深入理解.     

The S-Net System for Internet Packet Streams: Strategies for Stream Analysis and System Architecture

The traffic on an Internet link is a packet stream: packets of varying sizes arriving for transmission on the link. Each packet has an arrival time, and contained within the packet are headers that carry many critical variables. Packet traces, which consist of captured headers and measurements of the arrival times, convey substantial information about the Internet—security, usage, network performance, and the performance of engineering protocols. This article discusses strategies for the analysis of very large databases of packet traces, and the architecture of a software system that facilitates the use of these strategies. The system has a pipeline: (1) raw packet traces; (2) a database with objects tailored to ensuing analyses; and (3) an environment with tools for data analysis: statistical methods, model fitting, and visualization. The pipeline addresses the full set of tasks in the study of packet streams, from the initial processing of raw packet traces to the final output, often a visual display. S-Net—an extensible, open-source software implementation of this architecture—is based on the R implementation of the S language for graphics and data analysis, and has been developed on Linux.     

Growth Estimates for the Solutions of the Vlasov-Poisson System in the Plasma Physics Case

In [3] new a—priori—estimates for solutions of the Vlasov-Poisson system in the plasma physics case were obtained. We show that these lead to improved estimates on the possible growth of the solutions.     

Gender Differences in Learning Constructs,Shifts in Learning Constructs,and Their Relationship to Course Achievement in a Structured Inquiry,Yearlong College Physics Course for Life Science Majors

This study investigated differences and shifts in learning and motivation constructs among male and female students in a nonmajors, yearlong structured inquiry college physics course and examined how these variables were related to physics understanding and course achievement. Tests and questionnaires measured students' learning approaches, motivational goals, self‐efficacy, epistemological beliefs, scientific reasoning abilities, and understanding of central physics concepts at the beginning and end of the course. Course achievement scores were also obtained. The findings showed that male students had significantly higher self‐efficacy, performance goals, and physics understanding compared to females, which persisted throughout the course. Differential shifts were found in students' meaningful learning approaches, with females tending to use less meaningful learning from beginning to end of the course; and males using more meaningful learning over this time period. For both males and females, self‐efficacy significantly predicted physics understanding and course achievement. For females, higher reasoning ability was also a significant predictor of understanding and achievement; whereas for males, learning goals and rote learning were significant predictors, but in a negative direction. The findings reveal that different variables of learning and motivation may be important for females' success in inquiry physics compared to males. Instructors should be cognizant of those needs in order to best help all students learn and achieve in college physics.     

Deep Reinforcement Learning for Market Making in Corporate Bonds: Beating the Curse of Dimensionality

ABSTRACT

In corporate bond markets, which are mainly OTC markets, market makers play a central role by providing bid and ask prices for bonds to asset managers. Determining the optimal bid and ask quotes that a market maker should set for a given universe of bonds is a complex task. The existing models, mostly inspired by the Avellaneda-Stoikov model, describe the complex optimization problem faced by market makers: proposing bid and ask prices for making money out of the difference between them while mitigating the market risk associated with holding inventory. While most of the models only tackle one-asset market making, they can often be generalized to a multi-asset framework. However, the problem of solving the equations characterizing the optimal bid and ask quotes numerically is seldom tackled in the literature, especially in high dimension. In this paper, we propose a numerical method for approximating the optimal bid and ask quotes over a large universe of bonds in a model à la Avellaneda–Stoikov. As classical finite difference methods cannot be used in high dimension, we present a discrete-time method inspired by reinforcement learning techniques, namely, a model-based deep actor-critic algorithm.     

Optimal Harvesting and Stability for a Predator-prey System with Stage Structure

The dynamics of a predator-prey system, where prey population has two stages, an immature stage and a mature stage with harvesting, the growth of predator population is of Lotka-Volterra nature, are modelled by a system of retarded functional differential equations. We obtain conditions for global asymptotic stability of three nonnegative equilibria and a threshold of harvesting for the mature prey population. The effect of delay on the population at positive equilibrium and the optimal harvesting of the mature prey population are also considered.     

Global Stability of a Predator-Prey System with Stage Structure for the Predator

In this paper,some feasibly sufficient conditions are obtained for the global asymptotic stability of a positive steady state of a predator-prey system with stage structure for the predator by using the theory of competitive systems,compound matrices and stability of periodic orbits,and then the work of Wang [4] is improved.     

认知结构教学论在理工科基础课程教材改革中的探索

在认知结构教学论研究和实践的基础上,根据认知结构教学论的核心思想和理工科基础课程的特点,对传统理工科基础课程教材形式进行一次富有挑战性的、深层次的创新与探索,对教学内容进行结构优化,提出一种适用于大多数理工科基础课程教材的体例模板,并以"离散数学"课程为例进行示范性的说明.     

Dynamics of a Delayed Predator-prey System with Stage Structure for Predator and Prey

In this paper, a predator-prey system with two discrete delays and stage structure for both the predator and the prey is investigated. The dynamical behaviors such as local stability and local Hopf bifurcation are analyzed by regarding the possible combinations of the two delays as bifurcating parameter. Some explicit formulae determining the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions are derived by using the normal form method and the center manifold theory. Finally, numerical simulations are presented to support the theoretical analysis.     

一类具有阶段结构和时滞的捕食系统的持续生存和稳定性

我们提出和研究一类带有阶段结构和时滞的捕食模型,得到了种群持续生存的充分条件.研究了阶段结构和时滞对系统稳定性的影响,获得了系统发生Hopf分支和稳定性的条件以及轨道渐进稳定的周期解的存在性.     

地方应用型本科院校数学与应用数学专业课程体系的改革与实践——以太原工业学院为例

以太原工业学院为例,分析了数学与应用数学专业培养应用型人才所面临的挑战.结合该校地方性和应用型的特点,基于岗位需求为导向,围绕"毕业生未来就业岗位—培养目标—能力与素质要求—课程设置"这条主线完成了金融数学和软件开发两个方向的课程设置,以此建立"模块化教学,分流培养"的培养体系,为应用型本科院校数学与应用数学专业课程体系设置提供参考.     

电网安全调度中输电阻塞管理的演化策略

输电阻塞是电力系统运行中的常见问题 .本文建立了用于电网安全调度中输电阻塞管理的数学模型——带线性约束的多目标模糊优化问题模型 ,给出了求解该模型的演化策略 .实际的计算结果表明 ,演化策略解决输电阻塞问题是有效的 .     

半导体物理中的一个两点边值问题

本文研究了半导体流的表面张力进行区域提纯问题中提出的两点边值问题解的存在性 ,我们用上、下解方法和 Schauder不动点定理证明了如果 Q=2 A3 Re,其中 A是表面速率 ,Re是 Reynolds数 ,则当 0 Q 1 3.2 1时 ,该问题有解 ,对最近的结果 ( 0 Q 1 2 .6 8时 ,此问题的解存在 )进行了重要的改进