We propose that machine-learned computational models (MLCMs), in which the model parameters and perhaps even structure are learned from data, can complement extant approaches to the study of text and discourse. Such models are particularly useful when theoretical understanding is insufficient, when the data are rife with nonlinearities and…

This paper attempts to examine in a descriptive way the pioneering model of "World Englishes" proposed by Kachru in the mid-1980s that allocates the presence of English into three concentric circles: The "Inner" Circle, the "Outer" Circle, and the "Expanding" Circle. The Inner Circle presents the countries…

Textbooks currently circulating have not been adapted to online learning systems and their contents are less interactive, less communicative, and have not been based on local content potential. This research aimed to produce digital textbooks based on Madura local content and augmented reality to improve students' scientific reasoning ability.…

Emoji are commonly used in social media to convey attitudes and emotions. While popular, their use in educational contexts has been sparsely studied. This paper reports on the students' use of emoji in an online course forum in which students annotate and discuss course material in the margins of the online textbook. For this study, instructors…

A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…

This article analyses an assessment initiative known as the Basic Competency Assessment (BCA) in Hong Kong using Bernstein's performance and competence models of pedagogic practice. On the one hand, BCA is aligned with a competence model through its official projection as a low-stakes, student-focussed and formative assessment. However, an…

This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…

Principal component analysis (PCA) is one of the most important and powerful methods in chemometrics as well as in a wealth of other areas. Running a PCA results in two main elements, the score plot and the loading plot; the score plot provides the location of the samples, and the loading plot indicates correlations among variables, the trends in…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

Understandings of disability are situated within social, political and economic circumstances. Internationally, medical conceptualisations of disability prevail, influencing policy and practice, creating a discourse which encourages categorisation, diagnosis and prescribed ways of understanding behaviour. This body of knowledge has a profound…

With a growing number of leadership programs in universities and colleges in North America, leadership educators and researchers are engaged in a wide ranging dialogue to propose clear processes, content, and designs for providing academic leadership education. This research analyzes the curriculum design of 52 institutions offering a "Minor…

Duplicating processes and procedure with anticipation of deviating outcomes is the defining trait of insanity as attributed to a quote by Albert Einstein. It is the antithesis to innovation, which is what is needed in higher education to create impactful changes in the outreach we should be providing to the community. What is important for those…

Drawing parallels to classical test theory, this article clarifies the difference between rater accuracy and reliability and demonstrates how category marginal frequencies affect rater agreement and Cohen's kappa. Category assignment paradigms are developed: comparing raters to a standard (index) versus comparing two raters to one another…

Molenaar extended Mokken's original probabilistic-nonparametric scaling models for use with polytomous data. These polytomous extensions of Mokken's original scaling procedure have facilitated the use of Mokken scale analysis as an approach to exploring fundamental measurement properties across a variety of domains in which polytomous ratings are…

Text classification typically performs best with large training sets, but short texts are very common on the World Wide Web. Can we use resampling and data augmentation to construct larger texts using similar terms? Several current methods exist for working with short text that rely on using external data and contexts, or workarounds. Our focus is…