Research has shown that the development of cognitive and social skills in preschool predicts school readiness in kindergarten. However, most longitudinal studies are short-term, tracking children's development only through the early elementary school years. This study aims to investigate the long-term impact of preschool predictors, intelligence,…

The current research is the study of academic buoyancy in relation to emotional intelligence and parenting styles. Academic buoyancy is a strength in a student's life to deal with the routine problems in classroom study like low grades, negative feedback by teachers, and difficulties in understanding of concepts. For the studying the relationship…

Fluid intelligence and conscientiousness are important predictors of students' academic performance and competence gains. Although their individual contributions have been widely acknowledged, less is known about their potential interplay. Do students profit disproportionately from being both smart and conscientious? We addressed this question…

Although previous research has found trait emotional intelligence (TEI) to be a moderate predictor of bullying behaviors in adolescents, this work has limited generalizability. The current study is the first to use a multidimensional approach to both TEI and bullying behaviors when looking at their relationship in high school students. The study…

Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…

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…

Numerous artificial intelligence methods have lately been applied in education. This study proposes an Adaptive Neural-network-based Fuzzy Logic (ANFIS) model combining fuzzy logic and artificial neural networks for predicting students' STEM attitudes. The inputs of the research were determined as grade levels and academic achievement scores, and…

Explainable recommendation, which provides an explanation about why a quiz is recommended, helps to improve transparency, persuasiveness, and trustworthiness. However, little research examined the effectiveness of the explainable recommender, especially on academic performance. To survey its effectiveness, the authors evaluate the math academic…

While intelligence and motivational variables are well-established predictors of academic achievement, Need for Cognition (NFC), the stable intrinsic motivation to engage in and enjoy challenging intellectual activity, has not yet been considered comprehensively in this field, especially not longitudinally. By applying latent change score…

Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…

Although Macau students have consistently been recognized as top performers in international assessments, little research has been conducted to explore the various factors that are associated with their achievement. This paper aimed to identify factors that could best predict Macau students' reading achievement using PISA 2018 data provided by…

Brazil's education system lags behind international standards, with two-fifths of students scoring below the minimum level of proficiency in mathematics, science, and reading. Thus, this study combined machine learning with traditional statistics to identify the most important predictors and to interpret their effects on proficiency in the PISA…

Purpose: The purpose of this paper is to investigate the impact of three predictors (emotional intelligence, perceived supervisor support and work-life balance) on employee engagement. Design/methodology/approach: The employee engagement and its predictor variables considered have been assessed by a survey using a structured questionnaire. Data…

Previous attempts to explain teachers' educational effectiveness have mostly focused on personal traits, organizational commitment, pedagogical content knowledge or the passion for education, and so on. We want to highlight that social skills--competencies that enable teachers to interact effectively with others--might contribute to the teachers'…

Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…