Measuring business performance: A conceptual framework with focus on improvement

Managers look for measures that represent an integrated performance. These should lead to an analysis of unsatisfactory performance. Performance measurement and its evaluation is the first step toward formulating any plan for improvement. This article examines the imperatives of a good measurement system and presents a framework to measure business performance.     

Measuring performance in leaning process of digital game-based learning and static E-learning

Educational technology research and development - This study investigated and compared the effectiveness of both digital game-based learning (DGBL) and static e-learning material for Newton’s...     

Measuring the impacts of administrative policies on student performance in higher education

In this study, we investigate the joint impacts of class size, modality of content delivery and instructor workloads on 1078 student performances from 2010 through 2014 in a required College of Business Administration Information Systems (IS) course at a public Midwestern university, controlling for 11 demographic and other factors that might impact student performance. Class size, modality of delivery and instructor assignments are strategic college decisions affected by and subject to administrative policies that can impact the probabilities of student performance. Using the Akaike Information Criteria (AIC) and Chi-square significance tests, we construct a parsimonious binary logit model of individual student performance in the IS course and examine the effects of the administratively controllable factors on student performance. We find that the class size and the assignment of instructors to teach the course significantly impact student performance while modality of delivery does not. We offer and evaluate administrative policy recommendations likely to improve student performances.     

Measuring value added effects across schools: Should schools be compared in performance?

This article traces the evolution of a quest for solving the problems involved in the analysis of multilevel data and the estimation of the value added effects of schools in influencing educational outcomes. The authors report the findings of two studies that followed several cohorts of students that were tested at two grade levels (Grade 3 and Grade 5) and at three grade levels (Grade 3, 5, and 7) respectively with basic skills tests of literacy and numeracy in a single school system. The tests were calibrated using Rasch scaling and equated using concurrent equating procedures for approximately 8000 students in 440 schools. Hierarchical linear modelling was employed in the analysis with different multilevel models used in the two studies to assess relative and absolute change in performance respectively. The findings of these studies show that with different regression models and different variables taken into consideration there are very different estimates of the variance between schools and under some circumstances the residual variance between schools is very small. Research is clearly needed into the procedures of analysis and the different value added effects that could and should be employed.     

Measuring the effectiveness of online problem solving for improving academic performance in a probability course

Education and Information Technologies - Research on impact in student achievement of online homework systems compared to traditional methods is ambivalent. Methodological issues in the study...     

数字测频及测频误差

数字测频是目前较先进的频率测量技术 ,其测量精确度可优于 1× 1 0 - 1 3。数字测频误差主要来源于± 1个字误差和时基频率误差     

Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ)

Aside from test anxiety scales, measurement instruments assessing students’ achievement emotions are largely lacking. This article reports on the construction, reliability, internal validity, and external validity of the Achievement Emotions Questionnaire (AEQ) which is designed to assess various achievement emotions experienced by students in academic settings. The instrument contains 24 scales measuring enjoyment, hope, pride, relief, anger, anxiety, shame, hopelessness, and boredom during class, while studying, and when taking tests and exams. Scale construction used a rational-empirical strategy based on Pekrun’s (2006) control-value theory of achievement emotions and prior exploratory research. The instrument was tested in a study using a sample of university students (N = 389). Findings indicate that the scales are reliable, internally valid as demonstrated by confirmatory factor analysis, and externally valid in terms of relationships with students’ control-value appraisals, learning, and academic performance. The results provide further support for the control-value theory and help to elucidate the structure and role of emotions in educational settings. Directions for future research and implications for educational practice are discussed.     

Measuring Uncertainty

When analysing situations which involve decisions to be made as between alternative courses of action under conditions of uncertainty, decision maker and their advisers are often called upon to assess judgemental probability distributions of quantities whose true values are unknown to them. How can this judgement be taught?