A MATHEMATICAL PROGRAMMING MODEL FOR FACULTY COURSE ASSIGNMENTS

This paper describes an integer programming model that we believe has advantages over other models for determining faculty teaching assignments. Unlike previously proposed models, in this model the decision variables represent the assignment of complete teaching schedules rather than courses to faculty members. The paper compares the proposed model with previous models for application in an academic department.     

A multicriteria decision analysis model for faculty evaluation

In the context of increasing demands for social and financial accountability of universities, the required implementation of transparent faculty evaluation systems constitutes a challenge and an opportunity for universities strategically aligning the activity of academic staff with the university goals. However, despite growing interest in the performance appraisal of faculty, only a few reported studies propose models that cover the full range of academic activities and the models in use are typically based on ad hoc scoring systems that lack theoretical soundness. This article approaches faculty evaluation from an innovative comprehensive perspective. Based on the concepts and methods of multiple criteria value measurement, it proposes a new faculty evaluation model that addresses the whole range of academic activities and can be applied within and across distinct scientific areas, while respecting their specificities. Constructed through a socio-technical process, the model was designed for and adopted by the Instituto Superior Técnico, the engineering school of the Technical University of Lisbon. The model has a two-level hierarchical additive structure, with top-level evaluation areas specified by second-level evaluation criteria. A bottom non-additive third level accounts for the quantitative and qualitative dimensions of academic activity related to each evaluation criterion. The model allows (a) the comparison of the performance of academic staff with performance targets reflecting the strategic policy concerns of university management; (b) the definition of the multicriteria value profile of each faculty member at the top level of the evaluation areas; (c) the computation of an overall value score for each faculty member, through an optimisation procedure that makes use of a flexible system of weights and (d) the assignment of faculty members to rating categories.     

Faculty Performance Evaluation: Modeling to Improve Personnel Decisions*

Based on likely future changes in faculty evaluation practices, this paper examines how institutions of higher education might operationalize performance evaluation as related to research, teaching, and service. A model is developed that allows coupling performance evaluation and relevant market considerations with merit pay, tenure, and promotion decisions. The approach is specifically applicable to tenure-track faculty members in colleges and universities.     

SELF-SAMPLING: A UNIQUE AND EFFECTIVE MEASUREMENT TECHNIQUE IN HIGHER EDUCATION

Self-sampling, which is similar to work sampling, is a measurement technique where participants categorize their own activities. The ratio of observations in an activity category to the total observations provides an estimator of the population proportion of time spent on that category of activity. This paper summarizes how self-sampling works and describes an example involving business school faculty.     

Increasing the Effectiveness of Student Evaluation of Instructor Data through a Factor Score Comparative Report

Effective student evaluation of instructor instruments must provide norm, or comparative, data to aid interpretation. This note highlights an innovative factor score comparative report. Rather than merely reporting comparative data on individual questions items, the innovative report provides comparative percentile data on the six factors underlying our thirty-three item questionnaire. The faculty indicated overwhelming support for the new report. The note also briefly mentions three other activities that are essential for student evaluation of instructor data to improve teacher effectiveness. Our goal is to stimulate other colleges to adopt the innovative norming practice once they have validated their local evaluation instruments. College-wide improvement of teaching will occur through such do-it-yourself efforts and only decision science faculty are technically qualified to lead such efforts.     

TEACHING EFFECTIVENESS IN THE DECISION SCIENCES: THE USE OF STUDENT EVALUATIONS

This article presents the results of an AIDS-sponsored investigation of teaching effectiveness in the decision sciences. Two national samples were employed in the study: a sample of 247 business school deans and a sample of 3,292 students from 32 different business schools. Included among the findings are that 87 percent of the deans responding indicate they require some sort of faculty teaching effectiveness evaluation, and that great care must be exercised when interpreting student ratings of an individual instructor's teaching effectiveness.     

The nature of faculty work: A Canadian and US comparison

Abstract

Results based on 187 responses to an electronic survey from Canadian and US faculty in human resource development and adult education identified career paths of faculty, the nature of the job (i.e. how faculty divide their time between teaching, research and service), the nature of their programmes, and the key changes, issues and trends in their respective fields. There were few differences between the two countries. Where possible, findings also are compared to two previous studies. Identifying what drew faculty to academia and how they spend their time may enhance understanding of how they derive meaning and satisfaction from work. This understanding could help identify ways to mitigate faculty turnover.     

Revitalizing the MBA for the New Millennium: A Collaborative Action Research Approach

Business schools are facing increased competition due to information technology innovations and customer dissatisfaction. In response, business schools are turning to a variety of solutions, such as team teaching, integrated curricula, and distance learning. This article presents the results of a collaborative action research project initiated by one business school faced with the need to revitalize its MBA program. The faculty engaged in this project learned much about the challenges of teaching an integrative course and the constancy of change. We share our conclusions and recommendations about an integrated curriculum, distance learning, adult learning, team teaching, revisions in program duration and structure, as well as advice on the necessary administrative support and compensation for business schools contemplating such changes. This revised version was published online in July 2006 with corrections to the Cover Date.     

TOWARD TEACHING EXCELLENCE IN THE DECISION SCIENCES*

Recently the National Commission on Higher Education Issues found serious problems with college-level teaching and recomended educational reforms. This paper describes one attempt at reform—namely, a course at Georgia State University on university teaching for College of Business doctoral students. The 45-hour seminar, based on a university teaching model, covers setting instructional objectives, lecture and discussion methods, teaching methods for higher-level learning, test construction, course evaluation instruments, and instructional and technological innovations. Previous studies have demonstrated repeatedly that teaching improvement seminars can improve teacher and student performance in the classroom. This paper discusses how the seminar could be implemented at other colleges of business administration, extended to faculty development workshops, and ultimately result in a master teacher or instructional professorship.     

STOCHASTIC DOMINANCE AS A RISK ANALYSIS CRITERION*

This paper discusses the Stochastic Dominance (SD) approach to the evaluation of risky assets. Given a set of portfolios, the familiar EV procedure chooses a set of EV-efficient portfolios while the SD procedures choose SD-efficient sets that usually are quite similar to (but not identical with) the EV-efficient set. The SD approach can be employed as a refinement of the EV model or as an alternative method of evaluating portfolios. The SD view has certain conceptual advantages in the screening of a set of portfolios, but the EV model has the important advantage of an optimizing algorithm that builds efficient portfolios. Also, the SD approach requires more data than the EV approach.     

Measuring and explaining the cost efficiency of municipal solid waste collection and processing services

This paper proposes an adjusted version of the popular efficiency measurement technique data envelopment analysis (DEA) that makes it possible (1) to evaluate the cost efficiency of municipalities in the collection and processing of multiple household waste fractions, (2) robustifying the cost efficiency evaluations for the impact of measurement errors in the data or municipalities with outlying and atypical performances (if present in the sample set), and (3) to correct the evaluations for differences in the operating environments of municipalities (e.g., factors such as demography and median income of the municipality population). The paper illustrates the usefulness of the methodology by carrying out and analyzing a cost efficiency evaluation using data on 293 municipalities in Flanders, Belgium, for the year 2008.     

基于方法集化的动态组合评价方法研究

为了解决多种动态评价方法评价结论非一致性问题,提出动态组合评价方法。给出关于可比动态评价方法集和相容动态评价方法集的定义,并运用模糊聚类分析方法确定相容动态评价方法集;然后以相容动态评价方法集为基础确定可能的组合评价集,建立评价方法集化模型,寻找一个最满意的组合评价,并对该评价结论进行相容性检验。最后用一个实例说明本研究实际应用上的有效性。基于方法集化的动态组合评价方法对解决多种动态评价方法评价结论非一致性问题提供了思路,是综合评价方法研究的有益补充,可以利用该方法进行应用研究。     

多层次结构DEA模型及其应用

在评价实践中,评价者通常倾向采用一组指标或指标体系对DMUs展开相对全面的评价,不同层次指标的重要性也往往不同。然而,标准DEA模型在DMUs有限条件下经常会面临无法直接处理过多的评价指标,也无法直接处理多层次指标的问题。本文从DEA模型中的序结构和测度出发,构建了符合多层次指标体系特点,能相对全面地体现评价者价值导向,且具有合理区分能力的多层次结构DEA模型,并以15个机构基础研究的投入-产出评价为例展开了应用分析。     

基于支持向量机的人的全面发展评价模型及省份实证

根据“坚持以人为本,树立全面、协调、可持续的发展现,促进经济社会和人的全面发展”的科学发展观的内涵,通过人的全面发展评价指标的海选、筛选和理性分析构建了人的全面发展综合评价指标体系.建立了基于支持向量机(Support Vector Machines,SVM)的人的全面发展评价模型,并对我国2006年典型的14个省级行政区人的全面发展状况进行实证分析.本文的创新与特色一是通过高斯核支持向量机把评价指标空间映射到高维特征空间,解决了人的全面发展评价影响因素非线性赋权问题.克服了现有评价方法均采用线性加权方式计算评价结果、不能表达指标与评价结果间的真实关系的缺陷.二是通过正交设计确定支持向量机训练样本的输入数据,并通过AHP确定训练样本的权重,得到指标训练样本的评价结果作为训练样本的输出.解决了在没有训练样本输入和输出情况下如何确定指标训练样本的问题.这就解决了在缺乏训练样本输入、输出数据情况下如何应用支持向量机进行回归,以得到评价结果的问题.三是通过人口累积比重、收入累积比重、通货膨胀等可获得数据指标计算准基尼系数和准国民幸福指数,解决了基尼系数和国民幸福指数的间接测算问题,进而解决了现阶段因统计数据缺失、而无法进行省级行政区人的全面发展评价的问题.     

中国工商管理案例教学现状研究

本文通过对我国六所工商管理学院2002-2004年案例教学情况的调查研究,发现MBA课程满意度与案例教学满意度密切相关,我国MBA学生对案例教学的期望值普遍较高,但对MBA教学总体满意度和案例教学满意度都较低。此外,近两年案例教学比重和案例质量有明显提高,影响案例教学满意度的因素主要是本土化案例比重偏低以及教师的案例教学水平有待提高。     

INFLUENCE OF MISSING ATTRIBUTES ON SELECTING A BEST MULTIATTRIBUTED ALTERNATIVE

Alternatives involving many factors arc difficult to evaluate because of multiple underlying competing objectives. If evaluation is based on an incomplete set of factors, and if the purpose of the evaluation is to select a single overall best alternative, inferior alternatives may be selected with surprising frequency and/or severe negative impact. At the same time, sensitivity analysis of evaluation scores based on statistical criteria can easily mask the impact and the frequency of selection of inferior alternatives. In this paper, criteria appropriate to reflect the decision impact are developed and both the frequency and impact of the selection of inferior alternatives are demonstrated empirically. Previous studies based on statistical criteria [1] [9] indicated minimal impact on overall evaluation and selection. This paper demonstrates that high statistical criterion values coexist with frequent and/or serious errors of selection.     

A method of dissimilarity analysis

This paper finds the essential differences between objects in terms of available attributes in a knowledge representation system (KR-system) where neither condition nor decision attributes are distinguished. We find these differences by using the concepts of “almost indiscernibility relation” and “approximate decision logic (ADL)” language. Here, an information system has been considered where attribute values are not always quantitative, rather subjective having vague or imprecise meanings.     

不完全信息下的一种信用分类方法

本文详细分析了一类典型的不完全信息的信用评价问题,即存在信用参考信息不完全或样本数据较少,以及某些指标数据为区间数等。文章首先考虑具有不完全信用参考信息的情况,在分析这类问题特性的基础上,基于数据包络分析理论(DEA),提出一种以拒绝案例集构造参考单元集的方法,并给出了相应的DEA模型。然后,进一步考虑带有较为复杂区间指标数据这类具有不完全指标信息的信用评价问题,并给出了相应的信用分析方法,最后采用算例说明本文提出方法的合理性。由于所提方法能有效地处理信用信息不完全和指标数据不完全的情况,故其具有较为广泛的实用性。     

模糊粗糙集中综合评价的属性约简和规则获取

传统的评价方法在进行评价之前没有进行属性约简,并且对新样本的评价过程过于复杂.鉴于此,运用(S,T)模糊粗糙集对综合评价中的属性约简和规则获取进行了研究,通过属性约简精简评价指标,通过规则获取来简化新样本的评价过程,为新样本的评价提供了一种全新的方法.最后以一个综合评价实例来演示如何进行属性约简和规则获取.