This research attempts to map the trend of research related to differentiated instruction (DI). The research was conducted in May 2023 by researching research articles in the Scopus database. The search data from Scopus used title, abstract, and keyword searches. Research articles were analyzed descriptively based on year of publication, journal name, affiliation, country, and researcher name. The article database from Scopus was analyzed through VOSviewer and RStudio software so that a bibliometric map could be depicted in research related to DI. Based on the Scopus analysis results, it showed that publications of articles related to DI had increased from 2011 to 2021, although it decreased in 2016. The journal with the largest contributor to the publication of research articles related to DI was the Teaching and Teacher Education Journal. Vrije Universitiet Brusel was the university with the most published articles on DI. The country that contributed the most to the research articles related to DI was the United States. Struyven was the most productive scholar related to DI. Through network visualization, it was revealed that the evolution map of research related to DI was divided into five clusters.

Students’ mastery goal orientation tends to decline over the course of compulsory school, especially after the transition to lower secondary school. According to stage-environment fit theory, secondary school is less accommodating to students' needs, interests, and abilities than primary school. In consequence, the perceived person-environment fit declines as well. It is assumed that a strong sense of classroom community in primary school can counteract a potential decline in both of these important individual aspects. Using data from the Swiss longitudinal research project WiSel (“Wirkungen der Selektion”; “Effects of Tracking”), we conducted a latent growth curve model (LGCM) to examine the correlation between the development of students' mastery goal orientation and the development of their person-environment fit during the transition from primary school to lower secondary school. Perceived classroom community was assumed to benefit from these developments. The results show that both mastery goal orientation and person-environment fit decrease during the transition to lower secondary school. A strong sense of classroom community in fifth grade leads to a smaller decline in both constructs. Implications for educational practice are discussed.

It is unclear how social networks can be utilized in educational settings. An exploratory study was conducted to examine the differences between university students in Mexico and Spain in terms of their perceptions of knowledge and utilization of networks in the university environment. An overall sample of 378 students was collected from two public universities, one in Mexico and one in Spain. This study utilized descriptive statistics as part of a contingency analysis, X² with correction was used for the analysis of differences, Mann-Whitney U for the analysis of independence, Mantel-Haenszel test for association degree, Cramer's V for strength of association, Spearman's correlation coefficient for correlations. According to the results, the use of social networks is clearly related to country of origin, but not to gender. It seems that Instagram is a platform widely used by both Mexican and Spanish students, but it is not used in educational environments. Therefore, the use of social networks in higher education contexts differs by country, as does the knowledge of social bookmarking and the distribution of content to share information and resources.

In an era where diversity and digitalization significantly influence higher education, understanding and adapting to various learning preferences is crucial. This study comprehensively analyzes 394 scholarly articles from 1984 to 2022 using bibliometric methods, providing a dynamic overview of the research patterns in learning styles within higher education. We identified four stages of development during this period: 1984–1995 (Low-interest), 1996–2005 (Early development), 2006–2018 (Development), and 2019–2022 (Intensification). Our analysis highlights that the United States, the United Kingdom, and Australia were the top three leading publishers of research on learning styles in higher education. The results reveal three main topics of publications: educational technology, learning environments, and subject behaviors. This research not only identifies emerging research topics but also underscores the importance of adapting instructional strategies to diverse learning styles to enhance educational outcomes in higher education.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

The present study examined how empathy (affective and cognitive), basic psychological need satisfaction (autonomy, competence, and relatedness), and demographic factors (gender and academic achievement) jointly predict prosocial behavior during emerging adulthood. Grounded in Self-Determination Theory, this research explored whether relatedness need satisfaction mediates the relationship between empathy and prosocial tendencies. A total of N=889 undergraduate students from a large public university in the southeastern United States completed self-report measures assessing empathy, psychological needs, and prosocial behavior. Path analysis revealed that affective empathy and relatedness satisfaction were significant predictors of prosocial behavior. Relatedness also partially mediated the link between empathy and helping actions. Furthermore, gender and GPA contributed to prosocial outcomes, with female students and those with higher academic achievement reporting greater prosocial tendencies. These findings suggest that fostering emotional engagement and supporting students’ psychological needs—particularly the need for relatedness—may be key mechanisms for promoting prosocial development in educational settings during the critical stage of emerging adulthood.