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…

Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…

Futures of education are increasingly defined through predictive technologies and methods. We conceptualize 'algorithmic futuring' as the use of data-driven digital methods and predictive infrastructures to anticipate educational futures and animate actions in the present towards their materialization. Specifically, we focus on algorithmic…

Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…

Recently, researchers have focused on various factors influencing work engagement, particularly in the EFL context. In this vein, this study was carried out to investigate the relationship among proactive personality, flow, and work engagement in China. In so doing, three instruments including Proactive Personality Scale, Work-Related Flow…

One challenging issue in improving the teaching and learning methods in MOOCs is to construct potential knowledge graphs from massive learning resources. Therefore, this study proposes knowledge graphs driving online learning behaviour prediction and multi-learning task recommendation in MOOCs. Based on the knowledge graphs supported by…

Research on study habits among college students demonstrates a difference between what students should do and what they actually do. We sought to understand students' break-taking habits and perceptions within the context of study behaviors. One hundred and sixteen undergraduate students responded to a survey of their study break-taking behaviors,…

As is rapidly becoming clear, data science increasingly permeates many aspects of life. Educational research recognizes the importance and complexity of learning data science. In line with this imperative, there is a growing need to investigate the factors that influence student performance in data science tasks. In this paper, we aimed to apply…

Dropout prediction is an important strategic instrument for universities. The Austrian academic system relies on "student activity" for university funding, defined as accumulating 16+ ECTS credits per study year. This study proposes a combined method of machine learning and ARIMA models, predicting the number of studies eligible for…

Recycling waste is essential to mitigate environmental damage caused by human activity. Environmentally responsible behaviors, shaped during early ages, are closely linked to environmental attitudes, as demonstrated by prior research. This study aims to predict middle school students' recycling behaviors using machine learning algorithms. A…

While the educational value of formative assessment is widely acknowledged, the precise amount needed to effectively predict student performance on summative assessments remains unclear. This study investigates the relationship between intermediate formative assessment performance and final exam scores, addressing the critical question of how much…

Purpose: Internships are a common form of short-term employment for students seeking to demonstrate their value to employers and thereby improve their post-graduation career opportunities. As such, performance during the internship has been found to be positively related to post-graduation vocational outcomes. Yet, internships also serve a…

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…