Fuzzy computation of teaching performance based on data envelopment analysis method

Data Envelopment Analysis (DEA) is a system analysis method. It is suitable for evaluating the relative efficiency of Decision Making Units (DMU) with multiple input and output indicators, which is subject to no dimensional form of data and does not need to set the parameters. Subordinate colleges are an integral part of a university, and the university’s comprehensive competitiveness can be improved only when each college reaches the optimal state of teaching performance. From the perspective of faculty structure, this paper constructs the evaluation system for the teaching performance of subordinate colleges. In the evaluation system, there are two fuzzy variables, employment quality and quality of enrollment of graduates, so the fuzzy DEA method is adopted. The introduction of fuzzy theory can well solve the problem of fuzzy numbers in input or output. The commonly used fuzzy numbers include triangular fuzzy numbers and trapezoid fuzzy numbers. The triangular one is used in this paper. The research results will help the university strengthen the understanding of subordinate colleges, which is of practical significance to improve the university’s comprehensive competitiveness.     

What can regular and timely student feedback tell us about the teaching and learning processes?

Most studies on the evaluation of teaching focus on the input (teacher traits) or the output (student-generated products) of the teaching and learning processes. This article is based on a case study that examines the three components of teaching and learning: input, output and process. It presents a framework for collecting quantitative and qualitative data on the quality of instruction, assessment and feedback, and learning environment in college composition courses to complement the feedback provided by the end-of-course student evaluations of teaching for the purpose of monitoring, guiding, and improving instruction.     

内部分配改革的职务评价技术探新

建立工资标准系统的关键是确定职务工资率。职务间可比价值成分变异越大,对确定职务工资率的贡献也越大。根据以上研究设想采用方差分析方法进行职务评价。评价步骤包括：职务描述;对职务要素作主成分分析;对职务样本作聚类分析和判别分析;通过方差分析为可比价值各成分建构权重系数ωｉ。ωｉ‘满足：（１）ωｉ≥０;（２）Σωｉ＝１;（３）ωｉ,间可直接比较;（４）ωｉ的大小与对应的可比价值成分变异一致。最后将职务评价值线性变换为工资率。在线性方程中配一个常数。和调节系数α以适合组织的管理约束条件。配合两个企业内部分配改革的研究结果显示了方差分析法的有效性和实用性。     

APL functions for interactive data analysis: Principal components analysis

APL functions to support principal components analysis are presented: a general-purpose function to obtain eigen values and eigen vectors, a more specialized function to convert these into the results commonly given by principal components analysis, and a user interface function that accesses filed data, offers flexibility in data selection, and produces labeled output. A brief introduction to the logic and uses of principal components analysis is included. General-purpose support functions to simplify file use and to increase the range of options available to the user are also provided.     

Publish Yet Perish: On the Pitfalls of Philosophy of Education in an Age of Impact Factors

In many countries publications in Web of Knowledge journals are dominant in the evaluation of educational research. For various purposes comparisons are made between the output of philosophers of education in these journals and the publications of their colleagues in educational research generally, sometimes also including psychologists and/or social scientists. Taking its starting-point from Hayden’s article in this journal (Stud Philos Educ 31:1–27, 2012), this paper discusses the situation of educational research in three countries: The Netherlands, South Africa and Norway. In this paper an alternative for comparing research output is offered by invoking comparisons with colleagues at the international level from within the same sub-discipline. It is argued that if one would do so a different picture would emerge, even if one were to limit oneself to particular kinds of publications. The case is then made that if comparisons are regarded as a necessary part of the evaluation of an individual scholar (for appointment, promotion, tenure, and/or funding application purposes), it would be more fair to use a proxy system which is sub-discipline specific, or minimally contains some kind of correction factor in relation to the over-all quality assessment device. Debates about the relevance or irrelevance of philosophy of education in the context of educational sciences are now obscured, even poisoned by focusing almost exclusively on a particular kind of publication output. As the ‘reward’ system that is developed accordingly is possibly the most important driver of educational research, it puts the sub-discipline unduly under pressure to the extent that it possibly cannot survive.     

A sensorimotor theory of temporal tracking and beat induction

In this paper, we develop a theory of the neurobiological basis of temporal tracking and beat induction as a form of sensory-guided action. We propose three principal components for the neurological architecture of temporal tracking: (1) the central auditory system, which represents the temporal information in the input signal in the form of a modulation power spectrum; (2) the musculoskeletal system, which carries out the action and (3) a controller, in the form of a parieto-cerebellar-frontal loop, which carries out the synchronisation between input and output by means of an internal model of the musculoskeletal dynamics. The theory is implemented in the form of a computational algorithm which takes sound samples as input and synchronises a simple linear mass-spring-damper system to simulate audio-motor synchronisation. The model may be applied to both the tracking of isochronous click sequences and beat induction in rhythmic music or speech, and also accounts for the approximate Weberian property of timing.     

Assessing the stability of principal components using regression

This paper presents an analysis, based on simulation, of the stability of principal components. Stability is measured by the expectation of the absolute inner product of the sample principal component with the corresponding population component. A multiple regression model to predict stability is devised, calibrated, and tested using simulated Normal data. Results show that the model can provide useful predictions of individual principal component stability when working with correlation matrices. Further, the predictive validity of the model is tested against data simulated from three non-Normal distributions. The model predicted very well even when the data departed from normality, thus giving robustness to the proposed measure. Used in conjunction with other existing rules this measure will help the user in determining interpretability of principal components.The authors would like to thank the four anonymous reviewers and the two editors for their valuable comments. Atanu R. Sinha gratefully acknowledges the research support received from the Marketing Studies Center, AGSM, UCLA. Send requests for reprints to Atanu R. Sinha, B418 Gold Hall, 110 Westwood Plaza, Los Angeles, CA 90095.     

On-line Apple II for the recording and analysis of complex motor movements

The system described here was prompted by the need for a method of separately recording various components of a complex motor act. The task involved vertical, horizontal, and turn components. Our particular interest was the relation between integration of components and level of skill demonstrated. The peripheral equipment provides a separate analogue output for each component and plugs directly into the Apple’s game-paddle input. Trial data are stored directly on disk and can be retrieved for subsequent graphical plotting and analysis. The Apple II accommodates up to four inputs and returns results for movements as fast as .05 sec. The programming system can be used, without modification, for a wide variety of motor tasks. No additional interface or clock is required.     

Methodological considerations in the evaluation of differential components of supplementary education programs

Details procedures to be followed in analyzing multiple program options and time allocation for significant effects. A multiple-option supplementary education program was evaluated by the application of multiple regression analysis as a general data analytic system. One analysis reports the relative merits of supplementary education components when more than one type of program was operated by the same school system and when the criteria for evaluation were end-of-year achievement tests. A second evaluation demonstrates that an analysis of program input variables such as aide time allocation did produce significant improvement in achievement when an analysis of the differential effect of the input variables was considered. An incidental outcome of this study was that significant improvement in reading and mathematics achievement for children in supplementary education programs was more likely to occur with second- and third-grade pupils than with thise at later grade levels.     

A factor simplicity index

We propose an index for assessing the degree of factor simplicity in the context of principal components and exploratory factor analysis. The new index, which is called Loading Simplicity, is based on the idea that the communality of each variable should be related to few components, or factors, so that the loadings in each variable are either zero or as far from zero as possible. This index does not depend on the scale of the factors, and its maximum and minimum are only related to the degree of simplicity in the loading matrix. The aim of the index is to enable the degree of simplicity in loading matrices to be compared.The author would like to thank the review team for their insights and recommendations. This work was supported by a grant SEC2001-3821-C05-C02 from the Spanish Ministry of Science and Technology.     

对我国综合医院绩效评价指标体系的研究

通过对卫生部属（管）综合医院的调查,根据世界卫生组织的医院绩效评估框架,利用聚类分析手段筛选并建立了医院绩效评估指标体系。指标体系包括四大类,即技术、配置、质量和经营四个效率共22个指标,同时运用秩和比法对卫生部属（管）八所医院绩效进行综合评价与分析。     

Convergent methods in psychomusical research based on integrated,interactive computer control

Much of what we learn from an experiment depends on what we ask of the subjects and how we ask it. Most music perception and cognition research is implemented using a single methodology. Recently, questions have been raised about the validity and generalizability of such a limited approach, particularly regarding such complicated theoretical constructs as musical tonality. We propose that a useful technique is to converge on the answer to experimental questions by applying multiple methods, in essence, simultaneously investigating the central research question as well as ancillary questions of method. Such an approach is facilitated by a computer hardware and software system that integrates experimental design, data collection, data analysis, and data dissemination, linking off-the-shelf components through standard file formats and data-exchange protocols. The list-based system, using an IBM-type PC running Windows 3.0, handles real-time natural sound sampling and playback, signal synthesis and analysis, MIDI input and output, digitized picture display, and various subject-response mechanisms. On the basis of graphical icons, the integrated system can be used to build custom experimental designs. Examples of convergent psychomusical experiments that were designed, implemented, and analyzed using the system are discussed.     

Determining the number of components from the matrix of partial correlations

A common problem for both principal component analysis and image component analysis is determining how many components to retain. A number of solutions have been proposed, none of which is totally satisfactory. An alternative solution which employs a matrix of partial correlations is considered. No components are extracted after the average squared partial correlation reaches a minimum. This approach gives an exact stopping point, has a direct operational interpretation, and can be applied to any type of component analysis. The method is most appropriate when component analysis is employed as an alternative to, or a first-stage solution for, factor analysis.     

A microcomputer system for controlling classical conditioning experiments

A microcomputer-based laboratory system for controlling stimulus presentations and data acquisition in classical conditioning experiments is described. The system comprises an Intel 386/486-based microcomputer and a commercially obtained low-cost counter/timer board with input/output lines for stimulus timing and external device control. A simple, yet versatile custom-designed structured programming language is provided for performing an unlimited number of stimulus configurations and their sequences. In electrophysiological studies, the system can be flexibly connected to computer-controlled signal conditioning systems for the amplification and filtering of multiunit and evoked field potential responses and to high-speed data acquisition systems for sampling and analyzing the responses. The costs of reserving an entire microcomputer for experiment control are well compensated for by the simplicity and efficiency of programming and transportability of the control protocols between different setups and laboratories. Furthermore, a data acquisition and analysis system most suitable for the aims of a research project can be selected.     

Common functional principal components analysis: a new approach to analyzing human movement data

In many human movement studies angle-time series data on several groups of individuals are measured. Current methods to compare groups include comparisons of the mean value in each group or use multivariate techniques such as principal components analysis and perform tests on the principal component scores. Such methods have been useful, though discard a large amount of information. Functional data analysis (FDA) is an emerging statistical analysis technique in human movement research which treats the angle-time series data as a function rather than a series of discrete measurements. This approach retains all of the information in the data. Functional principal components analysis (FPCA) is an extension of multivariate principal components analysis which examines the variability of a sample of curves and has been used to examine differences in movement patterns of several groups of individuals. Currently the functional principal components (FPCs) for each group are either determined separately (yielding components that are group-specific), or by combining the data for all groups and determining the FPCs of the combined data (yielding components that summarize the entire data set). The group-specific FPCs contain both within and between group variation and issues arise when comparing FPCs across groups when the order of the FPCs alter in each group. The FPCs of the combined data may not adequately describe all groups of individuals and comparisons between groups typically use t-tests of the mean FPC scores in each group. When these differences are statistically non-significant it can be difficult to determine how a particular intervention is affecting movement patterns or how injured subjects differ from controls. In this paper we aim to perform FPCA in a manner allowing sensible comparisons between groups of curves. A statistical technique called common functional principal components analysis (CFPCA) is implemented. CFPCA identifies the common sources of variation evident across groups but allows the order of each component to change for a particular group. This allows for the direct comparison of components across groups. We use our method to analyze a biomechanical data set examining the mechanisms of chronic Achilles tendon injury and the functional effects of orthoses.     

词汇表征和加工理论及其认知神经心理学证据

认知神经心理学为探讨语言心理表征和加工理论提供了新途径 ,使得人们对心理词典结构的认识不断深入细化。研究表明词汇不同性质的信息在表征上相互独立 ,词典系统至少包括语义系统、语音输入词典与语音输出词典、字形输入词典与字形输出词典等模块。本文着重介绍了这一词典系统及其认知神经心理学证据     

A concept approach to input/output logic

This paper provides a semantics for input/input output logic based on formal concept analysis. The central result shows that an input/output logic axiomatised by a relation R is the same as the logic induced by deriving pairs from the concept lattice generated by R using a ∧- and ∨-classical Scott consequence relation. This correspondence offers powerful analytical techniques for classifying, visualising and analysing input/output relations, revealing implicit hierarchical structure and/or natural clusterings and dependencies. The application of all formal developments are illustrated by a worked example towards the end.     

Redundancy analysis an alternative for canonical correlation analysis

A component method is presented maximizing Stewart and Love's redundancy index. Relationships with multiple correlation and principal component analysis are pointed out and a rotational procedure for obtaining bi-orthogonal variates is given. An elaborate example comparing canonical correlation analysis and redundancy analysis on artificial data is presented.A Fortran IV program for the method of redundancy analysis described in this paper can be obtained from the author upon request.