We examined the relationship between the levels of sophistication (high-sophisticated and low-sophisticated) of students' domain general epistemic beliefs and an important component of students' critical thinking skills--their ability to evaluate arguments. Participants evaluated arguments and took an epistemic belief survey before recalling…

Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…

Effective presentation skills are an important ability for students and professionals to possess. Automatic analysis of presentation skills can help provide feedback to a speaker, and a complete analysis is possible only with both speaker and audience measurement. In this article, we propose a methodology to predict presentation skills on a small…

A classic issue in the cognitive psychology of human category learning has involved the contrast between exemplar and prototype models. However, experimental tests to distinguish the models have relied almost solely on use of artificially-constructed categories composed of simplified stimuli. Here we contrast the predictions from the models in a…

Educational data mining (DEM) provides valuable educational information by applying data mining tools and techniques to analyze data at educational institutions. In this paper, tree-based machine learning algorithms are used to predict students' overall academic performance in their bachelor's program. The transcript data of the students in the…

In this work, 29 features were defined and implemented to be automatically extracted and analysed in the context of NeuroK, a learning platform within the neurodidactics paradigm. Neurodidactics is an educational paradigm that addresses optimization of the learning and teaching process from the perspective of how the brain functions. In this…

Educational institutions abruptly implemented online higher education to cope with sanitary distance restrictions in 2020, causing an increment in student failure. This negative impact attracts the analyses of online higher education as a critical issue for educational systems. The early identification of students at risk is a strategy to cope…

The purpose of this study was to explore and identify patterns of risk predictors of maltreatment recurrence using predictive risk modeling (PRM). This study used the administrative dataset from the National Child Maltreatment Information System recorded by Korean CPS (Child Protective Service) workers. The information, including recurrent…

We analyse the predictive power of learning strategies for engineering students' performance in mathematics. Learning strategies play an important role in self-regulated learning. Based on a new learning strategy questionnaire that takes into account the specifics of mathematical learning at universities, we investigated what were the strategies…

About one-third of college students drop out before finishing their degree. The majority of those remaining will take longer than 4 years to complete their degree at "4-year" institutions. This problem emphasizes the need to identify students who may benefit from support to encourage timely graduation. Here we empirically develop machine…

Teacher turnover continues to be a significant problem in the United States. Teacher turnover is expensive because it costs money to continue recruiting, hiring, and training new teachers to replace those leaving (Carver-Thomas & Darling-Hammond, 2017). Most important though, teacher turnover hurts student achievement and success (Sorensen…

The data from universal screeners must be valid and reliable in order to use it to make appropriate decisions about how best to allocate resources to support students who are at risk of not passing the state achievement test. The instruments used as part of universal screening must also have diagnostic accuracy. This study examined the diagnostic…

Data-informed decision-making is no longer an optional or occasional practice, as higher education professionals now routinely respond to calls for accountability by providing data to show how their work impacts students. Institutions are operating with a culture that, at a minimum, includes the use of descriptive and diagnostic analyses to assess…

The current study aims to contribute to the literature on how organic chemistry students weigh various factors when predicting products of substitution and elimination reactions. This study focuses specifically on these mechanism types, as they are often the first instances where students must consider the "how" and the "why"…

Little is known about factors that predict attendance in strengths-focused, culturally grounded, family-based programming to prevent adverse childhood experiences (ACEs) among Indigenous populations in the USA. An understanding of these factors may help to create initiatives to reduce barriers to attending programming that could reduce ACEs and…