This study explores the impact of artificial intelligence (AI) integration on students' educational experiences. It investigates student perceptions of AI across various academic aspects, such as module outlines, learning outcomes, curriculum design, instructional activities, assessments, and feedback mechanisms. It evaluates the impact of AI on students' learning experiences, critical thinking, self-assessment, cognitive development, and academic integrity. This research used a structured survey distributed to 300 students through Microsoft Forms 365, yet the response rate was 29.67%. A structured survey and thematic analysis were employed to gather insights from 89 students. Thematic analysis is a qualitative method for identifying and analysing patterns or themes within data, providing insights into key ideas and trends. The limited response rate may be attributed to learners' cultural backgrounds, as not all students are interested in research or familiar with AI tools. The survey questions are about AI integration in different academic areas. Thematic analysis was used to identify patterns and themes within the data. Benefits such as enhanced critical thinking, timely feedback, and personalised learning experiences are prevalent. AI tools like Turnitin supported academic integrity, and platforms like ChatGPT and Grammarly were particularly valued for their utility in academic tasks. The study acknowledges limitations linked to the small sample size and a focus on undergraduate learners only. The findings suggest that AI can significantly improve educational experiences. AI provides tailored support and promotes ethical practices. This study recommends continued and expanded use of AI technologies in education while addressing potential implementation challenges.

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.  

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 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 bibliometric analysis examines global trends and scholarly discussions on learning poverty, with a focus on numeracy and literacy skills among young learners over the past decade (2015-2023). All data is retrieved from the Scopus database, and quantitative methods were employed to evaluate the impact and influence of literature in this area. In conducting the bibliometric analysis, the study utilised Microsoft Excel for descriptive statistics, Harzing’s Publish or Perish for citation metrics, and VOSviewer to visualize networks related to the co-occurrence of keywords and co-word analysis. The analysis findings indicate a substantial increase in research output on learning poverty, particularly after 2020, driven by the educational disruptions caused by the COVID-19 pandemic. The key themes identified in the literature include the expansion of educational inequalities, the impact of the digital divide, and the role of educational technologies in addressing learning losses. Co-occurrence and co-word analyses reveal a strong focus on COVID-19, educational inequality, and the integration of advanced learning technologies in recent research. These findings underscore the critical importance of targeted interventions and equity-focused policies to combat learning poverty. The analysis also emphasizes the importance of ensuring that all children, regardless of their socioeconomic background, acquire essential literacy and numeracy skills. Furthermore, the study emphasises the need for resilient and adaptable educational systems to better prepare for future challenges, particularly in the face of global crises such as pandemics. Essentially, the conclusions discuss the sustained efforts to address educational disparities and promote equitable learning opportunities for all.

This preliminary study examines how three generative AI tools, ChatGPT-4, Google Gemini, and Microsoft Copilot, support B+ level English as a Foreign Language (EFL) students in opinion essay writing. Conducted at a preparatory school in Türkiye, the study explored student use of the tools for brainstorming, outlining, and feedback across three essay tasks. A mixed methods design combined rubric-based evaluations, surveys, and reflections. Quantitative results showed no significant differences between tools for most criteria, indicating comparable performance in idea generation, essay structuring, and feedback. The only significant effect was in the feedback stage, where ChatGPT-4 scored higher than both Gemini and Copilot for actionability. In the brainstorming stage, a difference in argument relevance was observed across tools, but this was not statistically significant after post-hoc analysis. Qualitative findings revealed task-specific preferences: Gemini was favored for clarity and variety in brainstorming and outlining, ChatGPT-4 for detailed, clear, and actionable feedback, and Copilot for certain organizational strengths. While the tools performed similarly overall, perceptions varied by task and tool, highlighting the value of allowing flexible tool choice in EFL writing instruction.

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.

This study aims to investigate the effect of digital leadership, creativity, and proactive personality on innovative work behavior (IWB) through work engagement. The research involved 436 private school teachers in Indonesia. The research data were collected by a Likert scale questionnaire. Data analysis is done using structural equation modeling based on Partial Least Squares (SEM-PLS), with descriptive and correlational analysis as supplements. The findings indicated that digital leadership, creativity, proactive personality, and work engagement affect teacher IWB; digital leadership, creativity, and proactive personality impact teacher work engagement; and digital leadership, creativity, and proactive personality affect teacher IWB through work engagement. These findings introduce a new empirical model of the influence of digital leadership, creativity, and proactive personalities on teachers' IWB through work engagement. This model deserves to be discussed critically and in-depth, and adapted and adopted by researchers to enrich their future research. This model can also be modified and adopted by school practitioners (management) to accelerate and optimize teachers' IWB capacity based on digital leadership, creativity, proactive personality, and work engagement.