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,…

The number of clinical prediction models sharing the same prediction task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these prediction models have not been sufficiently studied, particularly in the context of meta-analysis settings where only summary statistics are available. In…

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…

Predictive analytics methods in education are seeing widespread use and are producing increasingly accurate predictions of students' outcomes. With the increased use of predictive analytics comes increasing concern about fairness for specific subgroups of the population. One approach that has been proposed to increase fairness is using demographic…

Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…

Decomposing variables into between and within components are often required in multilevel analysis. This method of decomposition should not ignore possible unreliability of an observed group mean (i.e., arithmetic mean) that is due to small cluster sizes and can lead to substantially biased estimates. Adjustment procedures that allow unbiased…

The global health emergency, COVID-19, significantly influenced schooling in Indonesia. Students employed a variety of coping mechanisms to cope with unusual stress levels during confinement time. Hence, as students' COVID-19 resilience, investigation, and prevention were required for high and chronic stress connected with various disorders. This…

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…

The research aims to determine the factors affecting PISA 2018 reading skills using the Random Forest and MARS methods and to compare their prediction abilities. This study used the information from 5713 students, 2838 (49.7%) male and 2875 (50.3%) female, in the PISA 2018 Turkey. The analysis shows the MARS method performed better than the Random…

The aim of the study was to examine self-motivation and study ethics as predictors of academic achievement among undergraduates in a Nigerian University. The study employed the correlation research design in the quantitative approach. Purposive sampling technique was used to draw a sample of 320 students out of which 228 students consented and…

This descriptive correlational study examined the predictive relationships between ACT composite scores, high school GPA, ACT testing attempts, and gender with teacher candidate's overall performance on the edTPA and each of the three edTPA instructional tasks (Task 1, Task 2, and Task 3). The edTPA is a portfolio-based subject-specific teaching…

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…

Starting with the hypothesis that analogical reasoning consists of a search of semantic space, we used eye-tracking to study the time course of information integration in adults in various formats of analogies. The two main questions we asked were whether adults would follow the same search strategies for different types of analogical problems and…