This study was conducted as a descriptive and cross-sectional study to examine the effects of game addiction and social media addiction on the lifestyle of Turkish adolescents. The study was conducted between May to June 2022, involved 1116 adolescents in the 13-18 age group receiving education in three high schools situated in the Western region…

The aim of the study is to determine the level of relationship between school climate and happiness according to student perceptions. This research is in the descriptive relational survey model. The sample of the study consists of a total of 539 students studying in public primary schools in the districts located in Ankara, the capital city of…

Traditional education systems do not provide students with much freedom to choose the right training of study that suits them, which leads on long-term to the negative effects not only on social, economic and mental' well-being of student, but also will have a negative effect on the quality of the work produced by this student in the future. In…

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

The present study investigated whether study engagement is predicted by personal resources (i.e., self-efficacy and psychological flexibility) and achievement goals. A total of 223 French first-year humanities and social sciences students were invited to complete an online questionnaire comprising scales measuring the three predictors. The results…

With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students…

In the context that many students have been fed up with rote learning or mechanical learning in history, this three-wave longitudinal study with one-year intervals examined the potential role of historical empathy in facilitating history learning. A sample of 821 middle school students participated (aged from 11 to 15 years, M = 13.47 years, SD =…

Science learning takes place not only in the context of science class but also after class. Students' internal forms of motivation, such as curiosity and interest, affect the entire science learning process in both in-class and after-class contexts. In addition, both stable existing learner characteristics, such as science curiosity and interest…

Articulating the rules, roles, and values that are expected of undergraduate researchers is important as we strive to create a more accessible path into the scientific community. Rules refer to skills required of scientists, roles refer to behaviors consistent with the expectations of a scientist, and values refer to beliefs of the scientific…

This study examines the factors that influence the intention and actual use of e-learning in entrepreneurship education by undergraduate students. The paper relies on a predictive study design and the partial least squares structural equation modelling to analyse data from a cluster sample of 599 students from the University of Cape Coast, Ghana.…

Arithmetic ability is critical for daily life, academic achievement, career development, and future economic success. Individual differences in arithmetic skills among children and adolescents are related to variations in brain structures. Most existing studies have used hypothesis-driven region of interest analysis. To identify distributed brain…

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…

Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…

With the spread of online education, many studies highlighted the crucial role of digital literacy in second/foreign language (L2) learning. However, the influence of such a competency on L students' perceived emotions has remained under-research. To fill this lacuna, this study used a quantitative design via three questionnaires to investigate…