Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…

Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…

The present study contributes to the development of effective measures to evaluate classroom climate, especially in elementary education where these remain limited. In addition, it addresses a typical "flaw" of several studies by approaching classroom climate as a group-level construct rather than an individual characteristic. Following…

We describe a data mining pipeline to convert data from educational systems into knowledge component (KC) models. In contrast to other approaches, our approach employs and compares multiple model search methodologies (e.g., sparse factor analysis, covariance clustering) within a single pipeline. In this preliminary work, we describe our approach's…

Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…

Introductory chemistry courses tend to suffer from high failure rates. Success in an introductory course has been linked to how students approach learning. The aim of this study was to explore how students' learning approach was related to their success in the introductory chemistry courses measured by the ACS exam and the final course grade.…

The upgrade educational information technology triggered by COVID-19 has shaped a new educational order and new educational forms. As a result, traditional educational measurement is now facing a systematic transformation, that is, from the Assessment of Learning (AoL) to Assessment for Learning (AfL), and finally to Assessment as Learning (AaL).…

The Cox proportional hazards model has been pervasively used in many social science areas to examine the effects of covariates on timing to an event. The standard Cox model is intended to study univariate survival data where there is a singular event of interest, which can only be experienced once. However, we may additionally wish to explore a…

At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…

This study aims to reveal the critical Internet literacy levels of preservice teachers in terms of multiple variables, by employing the correlational survey design. The sample of the study is formed by 216 preservice teachers of Turkish language studying at a state university located in western Turkey. The Critical Internet Literacy Scale…

Intelligence has been declared as a necessary but not sufficient condition for creativity, which was subsequently (erroneously) translated into the so-called threshold hypothesis. This hypothesis predicts a change in the correlation between creativity and intelligence at around 1.33 standard deviations above the population mean. A closer…

This article discusses estimation of average treatment effects for randomized controlled trials (RCTs) using grouped administrative data to help improve data access. The focus is on design-based estimators, derived using the building blocks of experiments, that are conducive to grouped data for a wide range of RCT designs, including clustered and…

Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…

This research uses a three-phase method to evaluate and forecast the academic efficiency of engineering programs. In the first phase, university profiles are created through cluster analysis. In the second phase, the academic efficiency of these profiles is evaluated through Data Envelopment Analysis. Finally, a machine learning model is trained…

Students using a Learning Management System (LMS) as a learning support have been observed to demonstrate different learning behaviours. Studies have reported students exhibiting different procrastination tendencies, distinct social behaviours and system usage patterns. Students can be clustered together based on similarity in their learning…