长沙建设国家中心城市的对策研究

建设国家中心城市是长沙市近年的奋斗目标.长沙市怎样建设国家中心城市,可以从与国内其他国家中心城市的全面比照当中得到建设方案.一是从经济实力、产业结构、科教实力、金融行业发展、对外开放等代表城市综合实力的5个方面,二是从引领和辐射功能、集聚功能、物流枢纽功能等代表城市功能的3个方面,对长沙与国内5个国家中心城市(天津、重庆、成都、武汉、郑州)进行对比研究.通过对比,从国内5个国家中心城市的城市功能差别当中找准长沙的城市功能定位,从长沙市城市综合实力的差距和优劣势当中发现长沙建设国家中心城市所要解决的问题,为此提出长沙建设国家中心城市的建设对策.     

Geometric composite indicators with compromise Benefit-of-the-Doubt weights

This paper builds on Van Puyenbroeck and Rogge's (2017) ‘indirect’ multiplicative Benefit-of-the-Doubt (BoD) index number framework, in which the linear, data-driven BoD-model is used to estimate the importance of various sub-indicators within a geometric composite index (CI). We present an integrated framework that combines optimistic and pessimistic BoD-based weighting that enables to (1) establish the degree of unbalance in countries’ policy portfolio mix, (2) identify multiple underlying factors to explain inter-temporal evolution, and (3) explain for differences in country policy performances under the different weighting schemes following a multiplicative Bortkiewicz decomposition. In doing so, we use alternative optimistic and pessimistic BoD-models as existing models suffer from potential drawbacks in the identification of a country's comparative strengths and weaknesses. We illustrate our results with social inclusion data for the EU-countries for the period 2008-2013.     

“LeActiveMath”—a new innovative European elearning system for calculus contents

This contribution gives, an overview of the project “LeActiveMath”. Within this project a new mathematics learning software has been developed. LeActiveMath is an innovative eLearning system for high school and college or university level classrooms which can also be used in informal contexts for self-learning, since it is adaptive to the learner and his or her learning context in many respects. Topics cover elements of basic knowledge like ‘linear equations’ as well as more sophisticated contents like ‘differential calculus’. This article describes some of the innovative components of the software that are meant to support the students' self-regulated learning. We conclude by reporting on the first evaluations in math classorooms in fall 2005.     

城市“精明增长”的数学模型研究

城市"精明增长"是为了管理城市蔓延的恶性增长状态,以建设经济繁荣、社会公平、环境可持续发展的城市为目标。在考虑城市的经济、社会、环境和人口为衡量精明增长的主要指标的情况下,为了研究城市的可持续发展,建立微分方程模型,以实际数据为依据,来研究各指标对城市精明增长的影响和对未来城市可持续发展的调控作用。     

On the importance of mathematical play

A number of existing theories and proposals for the meaning and characteristics of ‘play’ are considered before the authors suggest six characteristics of mathematical play, including the idea that it is not confined to childhood. Previous studies provide evidence for relating play to cognitive gain while the place of mathematical play in research activities is illustrated by describing a mathematician's approach to a number investigation from the classroom-The Six Circles. The problem-solving process for the Six Circles and observations of students solving calculator and integration problems are analysed in relation to theories of play and cognitive gain and also considered from the perspective of the students' experience. Piaget's theory for the assimilation and accommodation of new information and Davis's view of play as ‘space to support learning’ are reflected in the authors' rationale for suggesting that open questions and mathematical play provide opportunities for students to develop their own conjectures, with no threat of failure, and provide a foundation for mathematical learning. Some difficulties of implementing a ‘play’ approach in the classroom are discussed and further research questions proposed.     

Peer Interaction in Science Concept Development and Problem Solving

Cooperative learning is commonly advocated as an effective instructional strategy in classrooms. Years of research support this recommendation. Recently, however, cognitive researchers and theorists suggest that peer group work may possibly enhance concept development and problem solving. The effectiveness of group work, including peer tutoring, cooperative learning, and peer collaboration, may be explained using several theoretical perspectives. Piaget theorized that the importance of peers comes from their ability to share ideas and initiate the equilibration process in individuals. Vygotsky argued that learning takes place in social contexts only to be internalized at a later time. He proposed a “zone of proximal development” to describe the difference between a student's ability to solve a problem alone and with the help of a more knowledgeable person. Researchers focusing on both theoretical positions argue that results support both theories. Additionally, researchers suggest that peer collaboration may enhance concept development and problem solving ability. Recommendations are made for incorporating effective peer learning strategies into instruction.     

Structural Electricity Models and Asymptotically Normal Estimators to Quantify Parameter Risk

ABSTRACT

We estimate a structural electricity (multi-commodity) model based on historical spot and futures data (fuels and power prices, respectively) and quantify the inherent parameter risk using an average value at risk approach (‘expected shortfall’). The mathematical proofs use the theory of asymptotic statistics to derive a parameter risk measure. We use far in-the-money options to derive a confidence level and use it as a prudent present value adjustment when pricing a virtual power plant. Finally, we conduct a present value benchmarking to compare the approach of temperature-driven demand (based on load data) to an ‘implied demand approach’ (demand implied from observable power futures prices). We observe that the implied demand approach can easily capture observed electricity price volatility whereas the estimation against observable load data will lead to a gap, because – amongst others – the interplay of demand and supply is not captured in the data (i.e., unexpected mismatches).     

Application of network theory and AHP in urban transportation to minimize earthquake damages

Network theory and Saaty's analytic heirarchy process (AHP) are considered to be effective methods for estimating a city's traffic pattern during the emergency period of an earthquake, and for evaluating the urban transportation network of that city. A graph is created in which the nodes are land uses (or a group of land uses), crossroads or junctions represent the city, and the arcs are the streets. AHP is used to determine the priority of trips, and shortest path techniques identify the fastest routes for daily trips, and the safest ones during earthquakes. A pareto diagram then shows those streets that play an important role in satisfying both criteria. On the basis of the trip patterns obtained, the accessibility of a city may be estimated. This methodology helps to identify the weak points of the transportation network after an earthquake. However, it can also be used to analyse plans for the expansion of existing cities. The methodology was employed in the city of Rasht after the devastating earthquake in northern Iran in 1990.     

Effect of self-constructed concept map with peer feedback on chemistry learning outcome

Concept mapping remains widely used in education. However, little is known about how self-constructed concept maps and peer feedback can improve student learning outcomes in chemistry. We investigated the effects of peer feedback on concept mapping and how it improves students' learning performance in a large second-semester, introductory chemistry course. Three hundred and twenty students were randomly assigned to one of two concept mapping conditions: self-constructed concept map with peer feedback and self-constructed concept map without peer feedback. Each group constructed concept maps that depicted the relationship between concepts on the topic of intermolecular force. The results showed that students in the self-constructed concept map with peer feedback condition outperformed students in the no peer feedback condition in chemistry learning outcome. Overall, this study demonstrates that peer feedback enhances the effectiveness of learning with generative concept maps. The implications and future directions are discussed.     

Can peer assisted learning be effective in undergraduate mathematics?

We report the implementation and evaluation of a ‘peer assisted learning’ (PAL) scheme designed to reduce the so-called ‘cooling off’ phenomenon in undergraduate mathematics. ‘Cooling off’ occurs when mathematics undergraduates lose motivation and interest in their studies, despite having previously actively chosen to study it at higher levels. We found that, despite concerns about the novel didactic contract inherent in PAL schemes, a majority of students chose to engage with the scheme, and that the student leaders of the PAL sessions were generally capable of implementing a student-centred pedagogy. Furthermore, we found that students who attended the PAL sessions had higher achievement in their final examinations, even after controlling for their lecture attendance and prior attainment. We conclude by arguing that PAL may provide a useful mechanism for reducing the prevalence of the ‘cooling off’ phenomenon in some – but not all – groups of mathematics students.     

Developing professional judgement with the aid of a ‘low-profile’ group support system

This paper reports positive results from an application of one type of group support system (GSS) to a training application. Reviews of the findings of other trials of GSS have been mixed, and inconclusive. We describe the results of a series of seven training sessions in a field-based application of group process support. The subjects were professionals working in various agencies concerned with the welfare of older people. A ‘low-profile’ type of group support system, based on wireless handsets, was used. This design enabled responses from each participant to be input and displayed anonymously. Each session was aimed at stimulating a dialogue focused on the reasons for differences of judgement, as displayed on a single projected feedback screen. Changes of individual judgements were recorded for subsequent analysis and comparison with already known ‘expert judgements’. Frequent changes of judgement were recorded. A significant proportion of these were related to an improvement, which could not be explained as simply the result of conforming behaviour. We propose that the mode of operation and design of a ‘low-profile’ GSS have the potential to create a learning environment by reducing personal anxieties while encouraging group-based learning with focussed conversation. We conclude that this type of GSS design is particularly suited to ‘selective’-type tasks in groups.     

长吉图地区城镇体系的分形研究

长吉图开发开放先导区是吉林省发展的又一契机,是国家批准实验的新区,经济区和实验区当中唯一给予我国延边开发开放的重要区域地位,并赋予了先行先试权.运用分形理论对长吉图地区15个城镇自2002年-2010年九年间的城镇规模体系进行了系统定量的分形研究.作出了长吉图地区首位度和序位—规模双对数坐标图,用首位度,4城市指数,11城市指数,q值,D值进行分析研究,得出长吉图开发开放先导区城镇规模分形特征:1)长吉图地区城镇规模属于分形结构;2)城镇规模分布比较集中,中小城市不够发育,严重缺少过渡城市;3)首位分布有明显趋势,首位城市发展速度快于中小城市,城市规模出现发展不均衡.明确长吉图城镇体系在发展中的问题,据此提出城镇规模优化的合理性建议.     

Emergent learning behaviour in a simulated organization faced with tasks requiring team effort

We conceptualize organizational learning as a result of the collective learning behaviour of knowledge agents in an organization. Each agent provides a range of attributes that may be required to perform organizational tasks. We devised a computational model consisting of three processes to simulate an organization's response to performing repeated tasks: (1) Expert Selection Process for selecting the winner knowledge agent or lead agent; (2) Plan Formation Process for deciding what additional attributes are needed, but not possessed by the winner expert agent, and iteratively selecting further agents with the needed attributes until the task can be accomplished by the combined attributes of the ‘coalition of agents’ so formed; and (3) Capital Modification Process for rewarding participating agents according to the success of their combined organizational performance. We observed the simulated results for different combinations of three levels of task difficulty (requiring, respectively, 5, 10 and, 15 different attributes, each at a sufficient level in the coalition or team to complete the task), and three levels of selection, during plan formation, for knowledge agent performance (the extent to which selection favours knowledge agents with much capital or large strength versus knowledge agents without much capital or large strength). The simulated organization exhibited aspects of both single loop and double loop learning, in repeatedly performing the same task, and ‘learning to perform the task’ with the smallest possible team.     

A case study of pedagogy of mathematics support tutors without a background in mathematics education

This study investigates the pedagogical skills and knowledge of three tertiary-level mathematics support tutors in a large group classroom setting. This is achieved through the use of video analysis and a theoretical framework comprising Rowland's Knowledge Quartet and general pedagogical knowledge. The study reports on the findings in relation to these tutors’ provision of mathematics support to first and second year undergraduate engineering students and second year undergraduate science students. It was found that tutors are lacking in various pedagogical skills which are needed for high-quality learning amongst service mathematics students (e.g. engineering/science/technology students), a demographic which have low levels of mathematics upon entering university. Tutors teach their support classes in a very fast didactic way with minimal opportunities for students to ask questions or to attempt problems. It was also found that this teaching method is even more so exaggerated in mandatory departmental mathematics tutorials that students take as part of their mathematics studies at tertiary level. The implications of the findings on mathematics tutor training at tertiary level are also discussed.     

The role of informal learning spaces in enhancing student engagement with mathematical sciences

By helping create a shared, supportive, learning community, the creative use of custom-designed spaces outside the classroom has a major impact on student engagement. The intention is to create spaces that promote peer interaction within and across year groups, encourage closer working relationships between staff and students and support specific coursework activities – particularly group work. Such spaces make better use of time since students are motivated to stay and work during long gaps in their timetable, can provide a sense of ‘home’ within the institution and can lead to a cohesive community of practice. In this paper, we describe how this has been achieved and currently delivered in Mathematics at Sheffield Hallam University and provide some detailed analysis of the student usage of the space.     

Re-sourcing teachers’ work and interactions: a collective perspective on resources, their use and transformation

This paper reviews the literature on the theme of mathematics teachers’ work and interactions with resources, taking a particular perspective, the so-called ‘collective perspective’ on resources, their use and transformation. The review is presented under three headings: (1) theoretical frameworks commonly used in this area of research; (2) teachers’ interactions with resources in terms of their design and use; and (3) teachers’ interactions with resources in terms of teacher learning and professional development. From the literature, and the collection of papers in this issue, we argue that the collective dimensions play an important role in mathematics teachers’ work with resources and in their professional learning/development. Further empirical investigations are likely to be needed on: how teachers may work in collectives and with resources, and in which ways ‘productive’ collectives may form and work together; which roles particular resources can play in these delicate constellations and how particular resources may support teachers in their work and learning; and which kinds of resources offer opportunities for community building.     

Capitalizing on Emerging Technologies: A Case Study of Classroom Blogging

The challenge many teachers face is how to incorporate new technology into their classrooms that strengthens classroom learning by capitalizing on students’ media literacies. Blogs, a new and innovative technological tool, can be used in math and science classrooms to support student learning by capitalizing on students’ interests and familiarity with on‐line communication. This study explores the emerging blogging practices of one high school mathematics teacher and his class to explore issues of intent, use, and perceived value. Data sources for this case included one year's worth of blog content, an interview with the facilitating teacher, and students ‘perceptions of classroom blogging practices. Findings indicate that (1) teachers’ intentions focused on creating additional forms of participation as well as increasing student exposure time with content; (2) blogs were used in a wide variety of ways that likely afforded particular benefits; and (3) both teacher and students perceived the greater investment to be worthwhile. The findings are used to critically consider claims made in the literature about the potential of blogging to effectively support classroom learning.     

Weight assurance region in two-stage additive efficiency decomposition DEA model: an application to school data

In this paper we use the additive efficiency decomposition approach in two-stage data envelopment analysis. Initially, we evaluate the variable returns to scale version and face a structural difficulty of the model. In an extreme case, weights ξ₁ or ξ₂, which represent the relative importance of the performance of the first and second stages, respectively, become zero for a number of decision making units (DMUs). As a result, individual stage efficiencies for these DMUs are undefined. We propose a weight assurance region model to restrict ξ₁ and ξ₂, which ensures that both weights are always positive, and therefore individual stage efficiency is always defined. Furthermore, the proposed model is appropriate for policy making in the presence of a priori information about the relative importance of each stage in the overall process. We employ the new model to evaluate the efficiency of secondary education in 65 countries and construct an overall ‘school efficiency’ index. In the first stage we measure the ‘learning environment efficiency’ and in the second we measure the ‘student’s performance efficiency’.     

Fractal-based exponential distribution of urban density and self-affine fractal forms of cities

Urban population density always follows the exponential distribution and can be described with Clark’s model. Because of this, the spatial distribution of urban population used to be regarded as non-fractal pattern. However, Clark’s model differs from the exponential function in mathematics because that urban population is distributed on the fractal support of landform and land-use form. By using mathematical transform and empirical evidence, we argue that there are self-affine scaling relations and local power laws behind the exponential distribution of urban density. The scale parameter of Clark’s model indicating the characteristic radius of cities is not a real constant, but depends on the urban field we defined. So the exponential model suggests local fractal structure with two kinds of fractal parameters. The parameters can be used to characterize urban space filling, spatial correlation, self-affine properties, and self-organized evolution. The case study of the city of Hangzhou, China, is employed to verify the theoretical inference. Based on the empirical analysis, a three-ring model of cities is presented and a city is conceptually divided into three layers from core to periphery. The scaling region and non-scaling region appear alternately in the city. This model may be helpful for future urban studies and city planning.     

Data mining feature selection for credit scoring models

The features used may have an important effect on the performance of credit scoring models. The process of choosing the best set of features for credit scoring models is usually unsystematic and dominated by somewhat arbitrary trial. This paper presents an empirical study of four machine learning feature selection methods. These methods provide an automatic data mining technique for reducing the feature space. The study illustrates how four feature selection methods—‘ReliefF’, ‘Correlation-based’, ‘Consistency-based’ and ‘Wrapper’ algorithms help to improve three aspects of the performance of scoring models: model simplicity, model speed and model accuracy. The experiments are conducted on real data sets using four classification algorithms—‘model tree (M5)’, ‘neural network (multi-layer perceptron with back-propagation)’, ‘logistic regression’, and ‘k-nearest-neighbours’.