With the current rate of technological advancements, higher education institutions around the world are increasingly adopting a wide variety of technology-related approaches to instruction. One of the teaching strategies used on digital platforms that has been successfully and widely adopted in higher education institutions is blended learning (BL). The objective of this investigation is to provide a comprehensive examination of the research efforts on BL in the context of higher education (HE) over the past 20 years, including the rise in publications, the most cited scientific journals and sources, and the upcoming research topics. This paper uses bibliometric analysis with a dataset of 651 documents from Scopus data, including 638 authors from 95 countries published in 271 journal sources. The results of the study show that the top three countries for BL research in higher education are the United Kingdom, the United States, and Australia; the authors with the highest citation indexes are D. R. Garrison and B. Means, and the top two publishing sources are Education and Information Technologies and Internet and Higher Education. Based on the analysis, the main trends detected are (a) student participation and environment, (b) educational technology instructional innovation, (c) effective instructional strategies within the parameters of the COVID-19 pandemic, (d) effectiveness of evaluation in BL environments and (e) BL with Massive Open Online Courses (MOOCs) and Learning Management System (LMS) in HE. These findings offer meaningful insights to early career researchers who consult the publications and research lists above, as well as to policy makers who develop suitable BL in HE policies.

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.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.

This study aimed to optimize critical thinking by empowering reflective and impulsive students' collaboration, communication, and information literacy skills through information literacy-oriented e-books in STEM-integrated problem-based learning (PBL). The research method used was a descriptive explorative approach. The study subjects consisted of five reflective students and five impulsive students. The measurement of cognitive style used the Matching Familiar Figure Test (MFFT) instrument. Collaboration skills were assessed through observation sheets, critical thinking and communication skills were assessed through student worksheets based on problem-solving tasks, and information literacy was assessed through a questionnaire. The study found that reflective students excelled in critical thinking and information literacy, while impulsive students demonstrated superior collaboration skills. As for communication skills, reflective and impulsive students have different advantages for each indicator of communication skills. This study can conclude that implementing information literacy-oriented e-books through STEM-integrated PBL can optimize reflective and impulsive students' critical thinking, collaboration, communication, and information literacy skills. The implication of this study is the importance of integrating 21st century skills holistically in learning practices, especially in the digital era, to prepare the younger generation to face the challenges of the 21st century.

The education of gifted students is often characterized by high expectations, ambitious goals, and significant effort invested in learning. Their experiences of success and failure are shaped by a variety of factors, including personal, family, school, cultural, and social influences. This article examines how gifted students perceive and experience their own successes and failures, as well as how these experiences are perceived and responded to by their peers. Using qualitative methods, the study involved semi-structured interviews with thirty gifted students from seventh to ninth grades across ten elementary schools in Slovenia. The findings indicate that gifted students experience a range of emotions in response to success, from satisfaction to anxiety, while their reactions to failure often involve frustration and self-criticism. Peer responses to their success and failure vary significantly, ranging from supportive encouragement to jealousy and social exclusion. These findings highlight the complex interpersonal dynamics at play within school environments. Understanding and addressing these dynamics is crucial for creating inclusive, supportive, and stimulating learning environments that nurture both the academic and social-emotional well-being of gifted students.

Work-based learning (WBL) is an important tool for enhancing students' employability skills in vocational education and training. Many studies have underlined the importance of a variable of WBL, self-efficacy, and vocational identity in developing vocational students' employability skills. Nonetheless, the research is limited and examined separately. Therefore, this study investigates how WBL, self-efficacy, and vocational identity influence employability skills and how self-efficacy moderates between WBL and employability skills. Four hundred and three state university students in Yogyakarta were involved in the data collection. This study used structural equation modeling (SEM) analysis to test its hypothesis. The results of the study revealed that the implementation of WBL did not have a direct effect on employability skills; however, self-efficacy was able to moderate the relationship between WBL and employability skills. However, WBL directly influences vocational identity, which in turn directly influences employability skills, while self-efficacy also directly influences employability skills. This research has important implications for improving learning that can improve students' self-efficacy skills in an effort to build students' employability skills in vocational education and training.

This research investigated the validity of measurement and causal model of online scam protection behavior (OSPB) among at risk Thai students. The sample comprised 286 high school students from three demonstration schools under the University. Data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The factor loadings for all items satisfied the standard criteria with scores ranging from .40 to .80, item-total correlations ranging from .405 to .718, and Cronbach’s alpha coefficients ranging from .773 to .928. The modified model demonstrated a better fit with the empirical data (χ² = 47.62, df = 37, p = .113,  χ²/df = 1.287, RMSEA = .032, SRMR = .028, GFI = .97, CFI = 1.00, NFI = .99). All factors: a) awareness of online risks, b) inhibitory control, c) game-based learning, d) social support, and e) motivation to prevent online scams can predict 81% of OSPB. The motivation to prevent online scams strongly influenced OSPB, with an effect size of .60. Additionally, all factors can predict 88% of the motivation for online scam prevention, suggesting that Protection Motivation Theory (PMT) is a suitable framework for understanding and evaluating Thai students' preventive behaviors in online deception scenarios. This newly developed instrument is highly reliable and can be effectively used by researchers and educators to assess the risk of online fraud victimization among high school students.

The aim of this research was to assess changes in secondary school students’ grades longitudinally, including the semester before the COVID-19 pandemic, the period of distance learning, and two semesters when students had returned to face-to-face learning. In this longitudinal study, n=263 Latvian students’ grades from the period of six semesters (autumn 2019 to spring 2022) were collected and analyzed for seven study subjects (mathematics, English, Latvian, biology, chemistry, physics, and literature), using Friedman’s ANOVA, and Wilcoxon test for comparison. Results show that grades increased for several study subjects during the beginning of the distance learning period (e.g., mathematics and Latvian). However, this initial increase diminished after students had returned to schools to study in-person, especially for the subjects of mathematics and Latvian (native language). Decreases in students’ grades after returning to face-to-face studies indicate possible accumulated negative long-term effects of distance learning. The dynamics of the grades differ in various study subjects (e.g., relative stability in chemistry, decrease in mathematics, Latvian, biology), thus justifying the approach to analyze each study subject or study field separately. This study gives insight into longitudinal changes in students’ academic achievement, following the same students throughout their whole secondary school period from 10th to 12th grade during the pandemic.

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.

Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.

The proliferating field of writing education increasingly intersects with technological innovations, particularly generative artificial intelligence (GenAI) resources. Despite extensive research on automated writing evaluation systems, no empirical investigation has been reported so far on GenAI’s potential in cultivating intermedial writing skills within first language contexts. The present study explored the impact of ChatGPT as a writing assistant on university literature students’ intermedial writing proficiency. Employing a quasi-experimental design with a non-equivalent control group, researchers examined 52 undergraduate students’ essay writings over a 12-week intervention. Participants in the treatment group harnessed the conversational agent for iterative essay refinement, while the reference group followed traditional writing processes. Utilizing a comprehensive four-dimensional assessment rubric, researchers analyzed essays in terms of relevance, integration, specificity, and balance of intermedial references. Quantitative analyses revealed significant improvements in the AI-assisted group, particularly in relevance and insight facets. The findings add to the research on technology-empowered writing learning.

This research exclusively aims to determine the type of digital media most often used in the teaching and learning process of history and the motivation to use digital media by teachers in teaching history based on the unified theory of acceptance and use of technology (UTAUT). This study demonstrates that online learning platforms have become a widely used tool among Indonesian history teachers, with the highest adoption of online learning platform use in Junior and Senior High School, reflecting the high access to this platform across types of schools. The key driving factor for technology in history learning is that the technology must be user-friendly and have sufficient support for its use by educators. This research, using the technology acceptance model (TAM), contributes to teachers about motivational and environmental factors on technology adoption in teaching. Accessibility and proper support are the primary drivers for using technology in education and were the most impactful factors for teachers incorporating technology into history learning. Along with this supportive infrastructure, an effort must also be made to provide a conducive environment, such as teachers working together in this direction, and sufficient infrastructure for teachers so that it becomes easier for them to access and utilize technology. These methods can all help teachers gain confidence in their use of technology.

This study used data from the COVID Social Mobility and Opportunities (COSMO) Study, to examine young people’s university aspirations and post-18 education expectations during COVID-19 in relation to their demographic and socio-economic position, school engagement, education disruption, and attitudes to education. Through a series of binary regression analyses, the findings showed the important role school engagement (in the form of online lesson attendance, schoolwork and teacher contact) played in young people’s university aspirations and post-18 education plans, especially at the height of the pandemic. Education disruption and locus of control were found to contribute to young people’s aspirations and post-18 expectations. The findings also highlighted the influence of gender, ethnicity and socioeconomic position regarding university aspirations and expectations, laying bare the obstacles in accessing learning faced by disadvantaged young people at a crucial time in their education. The findings contribute to continued debates about educational aspirations in the post COVID-19 world and have policy implications especially as this generation of young people are still in education. They may also contribute to discussions on ways of supporting this COVID-19 generation through fiscal changes and widening participation policies that extend to post-18 education and early career development.

The current study sought to evaluate the impact of programs used to enhance the self-regulation and social interaction for children with Autism Spectrum Disorders (ASD), as perceived by their families. The descriptive approach was used to collect and analyze data and derive conclusions after developing the study instruments. The study sample consisted of 150 families of children with ASD enrolled in special education centers in Amman, Jordan. The study participants were purposefully selected to respond to the two provided measurement scales. To measure the impact of the intervention programs, the researchers developed the Self-Regulation Behavior Scale and the Social Interaction Scale, ensuring the validity and reliability of both scales. The results of the study indicated that from the families’ perspective, programs for children with ASD had a moderate impact on enhancing self-regulation and a high impact on social interaction. Additionally, the findings of the study revealed statistically significant differences in the degree of improvement in self-regulation and social interaction behaviors related to the child’s gender and the severity of their disorder. However, no statistically significant differences were found related to the child’s age and gender in their level of improvement in self-regulation and social interaction behaviors.

Augmented Reality (AR) technology is emerging as a promising tool in education, offering immersive and interactive learning experiences that enhance students’ understanding of abstract scientific concepts. This quasi-experimental study investigated the impact of AR on student learning outcomes in chemistry topics, including acids, bases, pH, oxides, and salts, among lower secondary students in Vietnam. A total of 191 students participated in the study, divided into two groups: the experimental group (n = 94) received AR-integrated lessons. The control group (n = 97) received instruction through traditional methods, including lectures and discussions. Data were collected at three points: prior to the intervention (Test 0, baseline) to establish group equivalence; during the intervention (Test 1) to monitor interim changes; and after the intervention (Test 2) to evaluate overall impact. These were complemented by semi-structured surveys and interviews to assess students’ academic performance, conceptual understanding, and active engagement in the lessons. Mixed-effects ANCOVA revealed a significant Group × Time interaction, F(1,188) = 9.93, p = .002, partial η² = .050, indicating that the experimental group demonstrated significantly greater improvement than the control group. The large between-group effect size (partial η² = .231) confirms substantial practical significance of the AR intervention. Qualitative findings indicated that the use of AR enhanced students’ motivation, engagement, and conceptual understanding by enabling them to visualize three-dimensional molecular structures and conduct simulated experiments in a safe, controlled environment. Despite challenges such as limited technological infrastructure and the need for specialized teacher training, the study demonstrates that AR holds considerable potential for transforming chemistry education in Vietnam. These findings underscore the importance of continued research, targeted professional development, and supportive policies to optimize the integration of AR into diverse educational settings, ultimately improving students’ interest and learning outcomes.

This study explored how the Self-Determination Theory (SDT) framework shaped physics teachers’ professional identities. Through a qualitative case study design, the researcher analyzed the teaching practices, interactions, and pedagogical preferences of two experienced physics teachers. The data sources included classroom observations, semi-structured interviews, informal conversations, and teaching materials. The male teacher adopted a traditional, authority-based approach, while the female teacher employed a student-centered, autonomy-supportive, and relationship-based teaching approach. These findings revealed that teacher identity differed significantly according to the level of meeting the three basic components of SDT: autonomy, competence, and relatedness. The teacher, who gave her students the right to choose experimental activities, collaborated with science centers and included parents in the process, developed a more flexible, participatory, and supportive structure. The other teacher allowed limited student participation in decision-making processes and created a more control-oriented classroom atmosphere. These results showed the importance of addressing autonomy-supported approaches in science teacher education.

Text readability assessment stands as a fundamental component of foreign language education because it directly determines students' ability to understand their course materials. The ability of current tools, including ChatGPT, to precisely measure text readability remains uncertain. Readability describes the ease with which readers can understand written material, while vocabulary complexity and sentence structure, along with syllable numbers and sentence length, determine its level. The traditional readability formulas rely on data from native speakers yet fail to address the specific requirements of language learners. The absence of appropriate readability assessment methods for foreign language instruction demonstrates the need for specialized approaches in this field. This research investigates the potential use of ChatGPT to evaluate text readability for foreign language students. The examination included selected textbooks through text analysis with ChatGPT to determine their readability level. The obtained results were evaluated against traditional readability assessment approaches and established formulas. The research aims to establish whether ChatGPT provides an effective method to evaluate educational texts for foreign language instruction. The research evaluates ChatGPT's capabilities beyond technical aspects. The study examines how this technology may influence students' learning experiences and outcomes. The text clarity evaluation capabilities of ChatGPT might lead to innovative approaches for developing educational tools. The implementation of this approach would generate lasting benefits for educational practices in schools. For example, ChatGPT’s readability classifications correlated strongly with Flesch-Kincaid scores (r = .75, p < .01), and its mean readability rating (M = 2.17, SD = 1.00) confirmed its sensitivity to text complexity.

The evaluation of Service-Learning (S-L) projects in online environments has become increasingly relevant in educational research, at the same time as the importance of using mixed methods has risen. However, there are few studies focusing on the evaluation of virtual Service-Learning, as most studies concentrate on face-to-face Service-Learning projects. In this regard, the aim of the present research is to assess three Virtual Service-Learning (vS-L) projects using a blended (quantitative-qualitative) evaluation method, also conducted online. The evaluation was conducted by students from the National University for Distance Learning, who completed a questionnaire asynchronously and participated in synchronous focus groups within their respective groups. Data were arranged in a mixed panel (questionnaire items and focus group verbatim opinions). The questionnaires demonstrated that Service-Learning is an excellent methodology to broaden students’ skills, abilities, and competencies to better face the professional world. The focus group verbatim interventions showed that the construction of indicators improves learning. Overall, the assessment results revealed a high level of student satisfaction. The implementation of our mixed-methods approach is innovative because it is conducted entirely online and utilizes computer technology for processing the gathered information.