This study aims to explore the measurement scale of higher education quality of business and administration sector on student’s perspective. More specifically, this study was conducted to achieve the following key objectives: Identify the components that make up the quality of higher education of business and administration sector on student’s perspective. Exploring and testing the measurement scale of the components those make up the quality of higher education of business and administration sector on student’s perspective.
After studying this chapter you will be able to: Understand the concept of measurement, understand the four levels of scales and their typical usage, explore the concepts of reliability and validity, become familiar with the concept of scaling, learn about the various types of attitude scales,...
Likert items and scales of measurement? includes what are Scales of Measurement? What Does the Literature Say About Likert Items and Scales of Measurement? What Does Common Sense Tell Us About Likert Items and Scales of Measurement?.
Chapter 12: Measurement scales. This chapter covers procedures that will help students understand measurement scales so that they can select or design measures that are appropriate. The chapter focuses on measuring complex constructs like attitudes.
Chapter 12 - Measurement scales. After studying this chapter you will be able to understand: The nature of attitudes and their relationship to behavior; the critical decisions involved in selecting an appropriate measurement scale; the characteristics and use of rating, ranking, sorting, and other preference scales.
American Costumer Satisfaction Index (ACSI)
and European Customer Satisfaction Index (ECSI)
Intangible economic indicators
Conducts analyses of customer service quality in 35
separate industries, 190 companies and government
agencies on a scale of 1 to 100
Post-consumption assessment by the user about the
product or service gained
Uses expectancy confirmation-disconfirmation approach:
focuses on service comparisons with customers prior
Aquatic scientists have always been intrigued with concepts of scale. This interest perhaps stems from
the nature of ßuid dynamics in oceans and lakes energy cascades from spatial scales of kilometers
down to viscous scales at centimeters or less. Turbulent processes affect not only an organisms perception
of, and response to, the physical environment, but also the interaction between species, both within and
across trophic levels.
Studies assessing rating scales are very common in psychology and related ﬁelds, but are rare in NLP. In this paper we assess discrete and continuous scales used for measuring quality assessments of computergenerated language. We conducted six separate experiments designed to investigate the validity, reliability, stability, interchangeability and sensitivity of discrete vs. continuous scales. We show that continuous scales are viable for use in language evaluation, and offer distinct advantages over discrete scales. ...
This book is motivated to a large extent by our dissatisfaction with current practices
in behavioral measurement. Most of the basic data consists of dichotomous
responses, and much of the rest is made of responses on short scales. Neither type
of data furnishes information that can inherently be considered more than ordinal.
The dominant contemporary treatment of this data is to derive from it scores on
interval-scale latent variables through the application of one or another"model"
that is presumed to explain the data.
Transition behavior scale second edition (TBS-2) is a standardized, educationally relevant measure of predicted success in employment and independent living. Areas of concern identiﬁed by the TBS-2 can be incorporated in the development of the individualized transition plan.
Aadaptive behavior evaluation scale revised second edition: 4 - 12 years (ABES-R2: 4 - 12 years) provides a measure of adaptive skills necessary for success in educational and residential settings. The ABES-R2 may be used as a general or specific measure of adaptive skills with any student experiencing academic or behavioral difficulties regardless of the severity or suspected disability.
Methods that measure compatibility between mention pairs are currently the dominant approach to coreference. However, they suffer from a number of drawbacks including difﬁculties scaling to large numbers of mentions and limited representational power. As these drawbacks become increasingly restrictive, the need to replace the pairwise approaches with a more expressive, highly scalable alternative is becoming urgent.
We present a large-scale meta evaluation of eight evaluation measures for both single-document and multi-document summarizers. To this end we built a corpus consisting of (a) 100 Million automatic summaries using six summarizers and baselines at ten summary lengths in both English and Chinese, (b) more than 10,000 manual abstracts and extracts, and (c) 200 Million automatic document and summary retrievals using 20 queries.
We describe a speedup for training conditional maximum entropy models. The algorithm is a simple variation on Generalized Iterative Scaling, but converges roughly an order of magnitude faster, depending on the number of constraints, and the way speed is measured. Rather than attempting to train all model parameters simultaneously, the algorithm trains them sequentially. The algorithm is easy to implement, typically uses only slightly more memory, and will lead to improvements for most maximum entropy problems. ...
In this paper we present a method to group adjectives according to their meaning, as a first step towards the automatic identification of adjectival scales. We discuss the properties of adjectival scales and of groups of semantically related adjectives and how they imply sources of linguistic knowledge in text corpora. We describe how our system exploits this linguistic knowledge to compute a measure of similarity between two adjectives, using statistical techniques and without having access to any semantic information about the adjectives. ...
The miniaturization and performance improvement in semiconductor devices and
integrated circuits (ICs) are expected to continue through leveraging of nanotechnologies and
nanomaterials. This evolution should accelerate the System-on-a-Chip (SoC) trend, i.e., singlechip
integration of multifunctional, mixed-signal electronic components, toward realizing
embedded nanoelectronic systems.