Personality has been identified as a possible antecedent to emotions experienced in the foreign language (FL) classroom. However, contrasting results and differing personality models have resulted in ambiguous findings. This study set out to delve deeper into the role of personality as a predictor of FL emotions through a series of increasingly…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

Despite its proven success in various fields such as engineering, business, and healthcare, human-machine collaboration in education remains relatively unexplored. This study aims to highlight the advantages of human-machine collaboration for improving the efficiency and accuracy of decision-making processes in educational settings. High school…

Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

Objective: There remains a need for effective and ethical development in students, for cohesive and connected societies of moral actors. This paper adopts an authentic leadership development in students perspective as a possible complement to discipline expertise. This research explored whether taking leadership roles while studying had a positive…

Early detection of and relevant information on children's mathematical difficulties is important to initiate targeted teaching and intervention. This study investigated the extent to which strategy use in single-digit addition provides additional predictive information about 61 grade one children's (6-year-old) mathematical achievement 3 years…

This study examines how well in-service teachers in Hong Kong (N = 1,110) are supported in their efforts to teach in inclusive classrooms. It also examines the psychometric properties of the newly developed Teachers' Perceived Support Needs scale to measure in-service teachers' perceived support needs. Factors that predict teachers' perceived…

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…

Teacher retention is a foundational issue and schools have historically struggled to retain teachers. Previous research indicates that teachers leave the profession at high rates before year five of teaching expertise. Lack of teacher retention contributes to instability and lack of trust in school districts. This secondary data study explores…

A cornerstone of inclusive education is teacher's readiness to respond adequately to different educational needs of students in their diverse classroom. Differentiated instruction, referring to the process by which teachers carefully monitor students' needs and progress, and adapt their instruction according to these differences, is a means to…

Evidence-based early interventions for autism spectrum disorder (ASD) have been shown to improve child outcomes and quality of life (Lord et al., 2018; Reichow et al., 2018; Smith & Iadarola, 2015). However, response to intervention is variable across both children and implementation contexts. Understanding factors that influence this…

No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA…

Although studies have investigated educational attainment of groups of students professing low and high educational self-expectations, groups of noncommittal students, rather than being studied as a discrete group, have been treated as missing and ignored. This study investigated the differences between students of noncommittal, low, and high…