Constructing fair sports league schedules with regard to strength groups

A single round robin tournament (SRRT) consists of n teams and a set of periods. Matches between the teams have to be scheduled such that each team plays against each other team exactly once and each team plays at most once per period. In order to establish fairness among teams, we consider a partition of the teams into strength groups. Then, the goal is to avoid matches where a team plays against extremely weak or extremely strong teams in consecutive periods. In this paper, we pick up two concepts ensuring different degrees of fairness and address several questions which remained open so far.     

Who You Know vs. What You Know: The Impact of Social Position and Knowledge on Team Performance

Organizational behavior theories generally agree that human capital is critical to teams and organizations, but little guidance exists on the extent to which such theories accurately explain the relative contributions of individual actors to overall performance. Using newly created network measures and simulations based on data obtained from a software development firm, we investigate the relative effectiveness of social network theory and resource dependency theory as predictors of individuals' contributions to team performance. Our results indicate that individual impacts on team performance are more closely associated with knowledge and task dimensions than with social network structure. Furthermore, given that knowledge may be assessed a priori, these factors provide useful guidance for structuring teams and predicting team performance.     

Combinatorial properties of strength groups in round robin tournaments

A single round robin tournament (RRT) consists of a set T of n teams (n even) and a set P of n − 1 periods. The teams have to be scheduled such that each team plays exactly once against each other team and such that each team plays exactly once per period. In order to establish fairness among teams we consider a partition of teams into strength groups. Then, the goal is to avoid a team playing against extremely weak or extremely strong teams in consecutive periods. We propose two concepts ensuring different degrees of fairness. One question arising here is whether a single RRT exists for a given number of teams n and a given partition of the set of teams into strength groups or not. In this paper we examine this question. Furthermore, we analyse the computational complexity of cost minimization problems in the presence of strength group requirements.     

Comparing theoretical frameworks enacted in experimental research: TELMA experience

In the context of the Kaleidoscope Network of Excellence, six European research teams developed a methodology for integrating their research approaches. In this paper, we present the methodology based on a cross-experimentation, showing how it gave insight to the understanding of each team’s research and on the relationship between theoretical frameworks and experimental research.     

Modelling Teams and Workgroups in Manufacturing

One of the major features of Japanese manufacturing techniques is the extensive use of teams, i.e., workers who as a group work together to produce sub-assemblies or finished products, or, alternatively, work together to accomplish a project. Many naive promoters of the team concept assume that the team members work together on the same tasks and activities and somehow accomplish them faster and better. However, observation of actual teams indicate that, unless a team member is new and quite inexperienced, teams split the required tasks or activities up so that each member has a unique task and most of the time members work independently. This paper develops models that try to describe the features of division of labour in teams and the way in which differences in capability between different team members impact performance. The models suggest that the advantage of teams probably lies primarily in the structure that enables faster/better workers to help out others.     

Toward a situation model in a cognitive architecture

The ability to coherently represent information that is situationally relevant is vitally important to perform any complex task, especially when that task involves coordinating with team members. This paper introduces an approach to dynamically represent situation information within the ACT-R cognitive architecture in the context of a synthetic teammate project. The situation model represents the synthetic teammate’s mental model of the objects, events, actions, and relationships encountered in a complex task simulation. The situation model grounds textual information from the language analysis component into knowledge usable by the agent-environment interaction component. The situation model is a key component of the synthetic teammate as it provides the primary interface between arguably distinct cognitive processes modeled within the synthetic teammate (e.g., language processing and interactions with the task environment). This work has provided some evidence that reasoning about complex situations requires more than simple mental representations and requires mental processes involving multiple steps. Additionally, the work has revealed an initial method for reasoning across the various dimensions of situations. One purpose of the research is to demonstrate that this approach to implementing a situation model provides a robust capability to handle tasks in which an agent must construct a mental model from textual information, reason about complex relationships between objects, events, and actions in its environment, and appropriately communicate with task participants using natural language. In this paper we describe an approach for modeling situationally relevant information, provide a detailed example, discuss challenges faced, and present research plans for the situation model.     

Mathematical Analysis of a Soccer Game. Part I: Individual and Collective Behaviors

Detailed time series analysis of a soccer match is given based on the detailed data of the 2D motions of all 22 players and of the ball for the match. The whole analysis includes two parts. In Part I, the individual and collective behaviors of the players of the two teams as well as the motion of the ball are presented as various time series. Geometrical centers, radii, expansion speeds, possession functions of the two teams are defined and calculated as functions of time. Major ranges of all players as well as of different groups of players (defenders, midfielders, forwards) of the two teams during the entire first half, the attacking phase of team A and the attacking phase of team B are calculated, respectively, showing the structures of the two teams during different phases. Distance coverage of each player and the mean distances covered by different groups of players (defenders, midfielders, forwards) during different phases are calculated. The time portions of possession of the ball by each team and the time portions of different phases are also calculated. In Part II, energy and spectral analysis and various correlations will be derived. The relation between various parameters and potential indicators will be discussed. The major purpose of the present study is to offer some general mathematical tools for the detailed analysis and to reveal some general features of soccer match when the detailed 2D data are available. The results would offer the raw materials for various potential indicators which may eventually be used in the coaching process to enhance the performance and in the prediction of the results of soccer matches.     

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 cognitive model of spatial path-planning

Planning a path to a destination, given a number of options and obstacles, is a common task. We suggest a two-component cognitive model that combines retrieval of knowledge about the environment with search guided by visual perception. In the first component, subsymbolic information, acquired during navigation, aids in the retrieval of declarative information representing possible paths to take. In the second component, visual information directs the search, which in turn creates knowledge for the first component. The model is implemented using the ACT-R cognitive architecture and makes realistic assumptions about memory access and shifts in visual attention. We present simulation results for memory-based high-level navigation in grid and tree structures, and visual navigation in mazes, varying relevant cognitive (retrieval noise and visual finsts) and environmental (maze and path size) parameters. The visual component is evaluated with data from a multi-robot control experiment, where subjects planned paths for robots to explore a building. We describe a method to compare trajectories without referring to aligned points in the itinerary. The evaluation shows that the model provides a good fit, but also that planning strategies may vary with task loads.     

Student and Teacher Perspectives Across Mathematics and Science Classrooms: The Importance of Engaging Contexts

Substantial recent focus has been placed upon the competitiveness of American students in increasingly global economies and entrepreneurial enterprises. As concerns center on students’ educational preparedness and their efforts at continued learning, researchers acknowledge the importance of student engagement with school. In order to foster engaged learners, teachers must be able to determine and monitor their students’ levels of engagement. The current study examined the alignment of perceptions of engagement by students, teachers, and outside observers across middle and high school mathematics and science classrooms. Results indicated significant teacher‐student differences in perceptions of student cognitive engagement across mathematics and science classrooms with teachers consistently perceiving higher levels than students. Moreover, most effect sizes were moderate to large. A subsequent multi‐level analysis indicated that while teacher perceptions of student cognitive engagement were somewhat predictive of student reported cognitive engagement, academic engagement ratings by outside observers were not.     

Adapting to the Changing Environment: A Theoretical Comparison of Decision Making Proficiency of Lean and Mass Organization Systems

In this paper weexamine the adaptability of the Japanese style leanorganization system and the traditional American style mass organizationsystem under changing environments. From an organizational designperspective, key structural aspects of the two organizations are modeled ina problem solving context using computational methods. Organizational-levelperformance in terms of decision making accuracy and severity of errors ismeasured as an indicator of organizational adaptability under conditionswhere the task environment shifts between predictable to unpredictable orvise versa. Our study shows that both organizations have their respectiveadvantages under different task environments and that they adapt toenvironmental shifts in different forms. Specifically, when the timepressure is high the lean organization system's performance isvirtually identical to the mass organization system, even though the leanorganization systemÆs members are more proactive. When the timepressure is low, the mass organization system shows a much fasteradaptability when the environment shifts to a predictable one but it is alsomore vulnerable when the environment shifts to an unpredictable one. Incontrast, the lean organization systemÆs response to the changingenvironment is characterized by its slower adaptability. When theenvironment shifts to an unpredictable one, the lean organization systemshows a gradual improvement till reaching a high level. When the environmentshifts to a predictable one, however, the lean organization system shows agradual decrease of performance. Our study further shows that the leanorganization system, with its strong team decision making emphasis, can bemore successful in avoiding severe errors when compared with the massorganization system, even under a predictable task environment.     

Preservice teachers’ mathematics task modification for emergent bilinguals

Implementing mathematically challenging tasks is difficult for teachers when working with emergent bilinguals because cognitively demanding tasks in mathematics commonly have high language demand. Currently, inadequate teacher preparation for teaching emergent bilinguals is becoming a significant concern in the United States as this population of students is rapidly growing. This study investigated how two mathematics preservice teachers (PSTs) support middle school emergent bilinguals to understand cognitively demanding mathematical problems through task modification. Fieldwork with a concurrent intervention was designed for the PSTs to work with emergent bilinguals in a one‐on‐one setting. The PSTs modified cognitively demanding mathematics tasks and designed a lesson for the emergent bilinguals based on the modified tasks. The results revealed that the task modification made by the PSTs tended to shift from reducing cognitive demands in mathematics and language to maintaining the demands through learning strategies of contextual support.     

关于科研事业单位知识型团队绩效评价的实证分析——基于胜任力模型

我国科研事业单位普遍面临绩效考核困境,不能满足知识经济背景下知识型团队的管理要求。胜任力模型可以有效地对知识型团队成员进行选拔、配置与管理,是团队取得高绩效的关键。本研究采用问卷调查结合行为事件访谈的方法,筛选科研事业单位知识型团队的胜任力特征,并采用主成分分析方法,从7个维度构建了知识型团队胜任力模型。在此基础上,采用层次分析法,对团队业绩、胜任力、行为指标进行两两比较,确认其相对重要性,进一步构建了绩效评价体系。结果发现,在科研事业单位知识型团队中,成员个人能力的提升、团队信息共享和效率以及团队管理者的能力是最重要的团队胜任力特征,而外部支持和人际关系相对次要。胜任力指标在绩效评价体系中占有重要的地位。而团队行为对团队绩效的影响也不可忽视。     

A ��task-centric approach�� to professional development: enhancing and sustaining mathematics teachers�� ability to implement cognitively challenging mathematical tasks

In this article, we describe a task-centric approach to professional development for mathematics teachers in which teachers?? learning experiences are focused on the selection and implementation of cognitively challenging mathematical tasks. We examined teachers?? selection and implementation of cognitively challenging tasks at three points in time: before and after their participation in the professional development initiative and during a follow-up data collection 2?years later. Data included instructional tasks, samples of student work, and classroom observations, and were compared between the time points to identify changes in teachers?? task selection and implementation and to determine whether these changes were sustained over time. Results indicate that teachers increased and sustained their ability to select high-level instructional tasks and to maintain the level of cognitive demand during instruction. All teachers, however, did not exhibit this pattern. Portraits of teachers who continued to select and enact tasks at a high level are contrasted with those who did not, and factors are identified to account for teachers?? current practices.     

Running to keep up with the lecturer or gradual de-ritualization? Biology students’ engagement with construction and data interpretation graphing routines in mathematical modelling tasks

Through a commognitive lens, we examine twelve first-semester biology students’. engagement with graphing routines as they work in groups, during four sessions of Mathematical Modelling (MM). We trace the students’ meta-level learning, particularly as they fluctuate between deploying graphs for mere illustration of data and as sense-making tools. We account for student activity in relation to precedent events in their experiences of graphing and as fluid, if not always productive, interplay between ritualised and exploratory engagement with graph construction and interpretation routines. The students’ construal of the task situations is marked by efforts to keep up with lecturer expectations which allow for changing degrees of student agency but do not factor in the influence of precedent events. Our analysis has pedagogical implications for the way MM problems are formulated and also foregrounds the capacity of the commognitive framework to trace de-ritualization and meta-level learning in students’ MM activity.     

组织气氛对团队有效性影响机制的实证分析

本研究以10家高科技组织中的48个工作团队作为研究对象,通过文献研究、问卷调查,利用SPSS11.0软件进行多元回归统计分析,研究了组织气氛中的创新、公平、支持、人际关系和员工身份认同等五个维度对团队有效性的影响作用,研究结果表明不同的组织气氛维度对团队的绩效、团队工作成员的满意度以及团队承诺具有不同的影响,同时,团队组织气氛通过团队群体效能感这个中介变量对团队的有效性产生影响作用。     

Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA

This paper evaluates the efficiency of National Basketball Association (NBA) teams under a two-stage DEA framework. Applying the additive efficiency approach, we decompose overall team efficiency into first-stage wage efficiency and second-stage on-court efficiency and find out the individual endogenous weights for each stage. The empirical results show that NBA teams present a better performance on wage efficiency than for on-court efficiency, as on-court efficiency is influenced by many uncontrollable factors. Moreover, NBA teams, on average, tend to possess a higher weight on the first stage, suggesting that teams’ managers can enhance organizational efficiency more efficaciously by prudentially recruiting players.     

Patrol scheduling in urban rail network

This paper presents the problem of scheduling security teams to patrol a mass rapid transit rail network of a large urban city. The main objective of patrol scheduling is to deploy security teams to stations of the network at varying time periods subject to rostering as well as security-related constraints. We present several mathematical programming models for different variants of this problem. To generate randomized schedules on a regular basis, we propose injecting randomness by varying the start time and break time for each team as well as varying the visit frequency and visit time for each station according to their reported vulnerability. Finally, we present results for the case of Singapore mass rapid transit rail network and synthetic instances.     

Human Cognitive Closure and Mysterianism: Reply to Kriegel

In this paper, I respond to Kriegel’s criticism of McGinn’s mysterianism (the thesis that humans are cognitively closed with respect to the solution of the mind-body problem). Kriegel objects to a particular argument for the possibility of human cognitive closure and also gives a direct argument against mysterianism. I intend to show that neither the objection nor the argument is convincing.