Interest in the gender gap in the physical sciences has been ongoing for a number of years. This study aimed to explore differences in gender based on self-perception. The use of a post-examination survey was used to examine the role of gender in grade perception in chemistry courses over a several-year period. This included courses for…

Student feedback literacy is emphasised in recent literature as a critical attribute of university graduates. Although the impacts of epistemic beliefs on specific dimensions of student feedback literacy have been discussed in the literature, there is still a lack of quantitative research to investigate the strength of such impacts. This study…

This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

The nodules on the roots of soybeans provide N that the plant uses for growth and development. The goal of this study is to observe if the number of nodules on the taproot, volume of nodules on the taproot, the total number of nodules, or the number of nodules on the secondary roots in the early growth stages of soybeans have a significant…

This paper looks at the tension between the desire to claim predictive ability for Agent-Based Models (ABMs) and its extreme difficulty for social and ecological systems, suggesting that this is the main cause for the continuance of a rhetoric of prediction that is at odds with what is achievable. Following others, it recommends that it is better…

Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…

Massive Open Online Courses (MOOCs) are revolutionizing online education and have become a popular teaching platform. However, traditional MOOCs often overlook learners' individual needs and preferences when designing learning materials and activities, resulting in suboptimal learning experiences. To address this issue, this paper proposes an…

The study examined the impact of child protective services (CPS) contact on out-of-school suspensions for 49,918 Wisconsin students (followed from ages 5-6 to 14-15; [school years 2010-2019; 74% White; 7% Black; 11% Hispanic; 8% other; 49% female]). A quasi-experimental design comparing recent CPS contact to upcoming (future) CPS contact shows…

Mathematics provides us with tools to capture and explain phenomena in everyday biology, even at the nanoscale. The most regularly applied technique to biology is differential equations. In this article, we seek to present how differential equation models of biological phenomena, particularly the flow through ion channels, can be used to motivate…

In any meta-analysis, it is critically important to report the dispersion in effects as well as the mean effect. If an intervention has a moderate clinical impact "on average" we also need to know if the impact is moderate for all relevant populations, or if it varies from trivial in some to major in others. Or indeed, if the…

Across two studies, children ages 6-9 (N = 160, 82 boys, 78 girls; 75% White, 91% non-Hispanic) rated an inaccurate expert's knowledge and provided explanations for the expert's inaccurate statements. In Study 1, children's knowledge ratings decreased as he provided more inaccurate information. Ratings were predicted by age (i.e., older children…

This article introduces a novel method that integrates collaborative filtering into the naive Bayes model to enhance predicting student academic performance. The combined approach leverages collaborative user behavior analysis and probabilistic modeling, showing promising results in improved prediction precision. Collaborative Filtering explores…

Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

This article presents an exploration of college student perspectives of their zeitgeist over five semesters during and after the COVID-19 pandemic. At the start of each semester, from Spring 2021 through Spring 2023, between 100 and 150 individuals offered words and/or phrases which they believed characterized the spirit of the time. While this…