Integrated learning has emerged as an approach to developing critical thinking and creativity skills. This meta-analysis synthesizes the effects of integrated learning on critical thinking and creativity, drawing from experimental studies published over the past decade. This study addresses the research question: What are the impacts and factors influencing integrated learning on students' critical thinking skills and creativity compared to conventional learning over the past decade? In the database, 403 articles were obtained, which were then supplemented by seven articles from manual searches, so that there were a total of 410 articles. After a strict inclusion process, 8 articles were selected for analysis. The inter-rater reliability test using Cohen's Kappa coefficient produced a value of 0.78, which indicates a substantial level of agreement. The analysis includes data from 497 participants for critical thinking and 266 for creativity. Heterogeneity in critical thinking skill data was 96%, and in creative skills, it was 86%; then, a subgroup analysis of education level was carried out to find out where the high heterogeneity was. The results show a significant positive effect of integrated learning, with an SMD of 1.48 (p = .004) for critical thinking and 1.60 (p = .0001) for creativity. Funnel plots and Egger's regression tests indicate no risk of publication bias. In addition, this study also synthesized the causal factors of how integrated learning affects critical thinking skills and creativity. Further research is recommended to explore its long-term impact and implementation strategies in various educational settings.  

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.

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.

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.

The emergence of artificial intelligence (AI) has transformed higher education, creating both opportunities and challenges in cultivating students’ critical thinking skills. This study integrates quantitative bibliometric analysis and qualitative systematic literature review (SLR) to map global research trends and identify how critical thinking is conceptualized, constructed, and developed in the AI era. Scopus served as the primary data source, limited to publications from 2022 to 2024, retrieved on February 8, 2025. Bibliometric analysis using Biblioshiny R and VOSviewer followed five stages—design, data collection, analysis, visualization, and interpretation—while the SLR employed a deductive thematic approach consistent with PRISMA guidelines. A total of 322 documents were analyzed bibliometrically, and 34 were included in the qualitative synthesis. Results show that Education Sciences and Cogent Education are the most productive journals, whereas Education and Information Technologies have the highest citation impact. Several influential documents and authors have shaped global discussions on AI adoption in higher education and its relationship to critical thinking. Thematic mapping identified five major research clusters: pedagogical integration, ethical and evaluative practices, technical and application-oriented AI models, institutional accountability, and socio-technical systems thinking. Conceptually, critical thinking is understood as a reflective, evaluative, and metacognitive reasoning process grounded in intellectual autonomy and ethical judgment. Across the reviewed literature, strategies for fostering critical thinking converge into three integrated approaches: ethical curriculum integration, pedagogical and assessment redesign, and reflective human–AI collaboration. Collectively, these strategies ensure that AI strengthens rather than replaces human reasoning in higher education.