The aim of this exploratory case study is to investigate the impact of the pandemic as an unexpected situational variable on university instructors’ perceptions and attitudes towards technology integration, as well as their foresight about the future of education in post Covid-19 era. The data for the study came from autobiographies, narratives, and opinionnaires. The findings revealed that the degree of familiarity with educational technology and eagerness to integrate technology into education made a difference in academicians’ adaptation to the new mode of delivery. As for their predictions for the future, an increase in the use of educational technology not only in teaching, but also in testing and assessment is expected. Participants also emphasized a need to enhance the infrastructure to avoid any further technical issues and offer continuous development opportunities for teachers and students to become familiar with new technologies.

This study sought to investigate the current state of innovative teaching research and identify emerging themes and trends in the field from 2013 to 2023. The Scopus database was searched for the term “innovative teaching,” resulting in 1005 documents. After manual screening, 903 articles were exported in the BibTeX format for further processing in Bibliometrix using three bibliometric analysis types: network analysis, science mapping, and performance analysis. Performance analysis revealed bursts in publication output in 2015 and 2021, with a moderate boost in 2018. Ten top-cited journal papers were identified. The citation rates were low between 2019 and 2021, but there has been an upturn since 2022. The top keywords included simulation and nursing education, and there was a shift in research topics from broad educational concepts to more specific approaches, such as e-learning. Innovative teaching has been predominantly investigated in higher education, particularly in nursing education, with themes like “teaching/learning strategies” suggesting an emphasis on enhancing teaching practices not just through technology infusion. This study can aid educators and researchers in staying current with innovative teaching developments and inform their teaching practices.

The pervasive development and momentous changes of internationalization in higher education have led to the acceleration of research on its key component – the curriculum. However, there has not been any comprehensive analysis of the research status of the internationalization of the curriculum (IoC). To address the gap, this study employs the bibliometric method to construct an intellectual structure of research on the topic. The data, retrieved from the Scopus Database, consisted of 386 publications. The extracted data were then analyzed using citation, co-authorship, and keyword co-occurrence analysis. The results reveal a significant growth in research volume during the last ten years and the domination of Global North in the geographical distribution of publications. Besides, the most prominent authors include those who introduced fundamental knowledge on the topic. The most cited works and the most popular publishing sources focus on various aspects of internationalization of higher education. They also show a multidisciplinary interest in the topic. Finally, concerning newly emerged themes of studies on IoC, “cultural competence” and “internationalization at home” are outstanding keywords. The research findings emphasize IoC as a potential research matter. Hence, this study is recommended as a starting point for future researchers when examining related subjects.

This study investigates the impact of external variables, technological pedagogical and content knowledge (TPACK) self-efficacy, and facilitating conditions on teacher adoption of online teaching technology during the COVID-19 pandemic. It employs explanatory research to characterize the effect of external variables on the variables of the technology acceptance model. 240 high school teachers filled out Google Forms survey questionnaires for six research variables and analyzed by the SmartPLS program. The result indicates that attitude and perceived usefulness significantly and positively influence behavioral intention. Perceived usefulness and ease of use have a strong positive effect on attitude. Furthermore, perceived ease of use has a considerable effect on perceived usefulness. Perceived usefulness and ease of use are not significantly influenced by external variables. Facilitating conditions significantly positively affect behavioral intention, whereas TPACK self-efficacy negatively affects behavioral intention.

There has been a clear shift in higher education to prepare and empower the current students for a future quite different and more complex than that faced by previous generations. In particular, it is expected that they will possess comprehensive abilities to deal with challenges arising from new employment demands and beyond. While liberal arts education has a long history in the West, it has been increasingly implemented more recently in East Asia as one response to the need for educational reform. The research reported here is an empirical study of how liberal arts education has affected individuals from two institutions with distinctive interpretations of “liberal arts education” - University N, the first Sino-foreign joint university in mainland China, and University L, the only public liberal arts university in Hong Kong. Drawing on Bourdieu’s Theory of Practice, this study illustrates the interplay and balance among students’ practical concerns, their sense of social obligation fostered through liberal arts education elements and the wider social structure. Semi-structured interviews with senior students, fresh graduates, and educators were conducted to gather in-depth primary data. These reveal that, by providing interdisciplinary knowledge and transferable skill sets, a liberal arts education experience does enhance individuals’ personal agency and intellectual competencies in a professional context - they are trained to become independent thinkers and learners. Moreover, the “humanistic” aspect of liberal arts is also relevant: having engaged in various activities and programs, students in both universities are encouraged to care, cooperate, and make positive differences in their increasingly interconnected communities.

Higher education institutions have focused their efforts on promoting research seedbeds as a strategy for formative research. In this regard, the impact of such a strategy remains unknown due to the lack of models that enable its evaluation. Therefore, this study aimed to design an evaluation model for the academic productivity of research seedbeds based on the available evidence in the literature. To achieve this, a systematic review was conducted following the PRISMA model, analyzing 53 documents including articles, book chapters, and conference proceedings from the SCOPUS, ProQuest, Jstor, Scielo, and ScienceDirect databases. The results identified indicators that allowed for the design of a model based on six constructs: research training, institutional capabilities, bibliographic production, innovation and development, social appropriation of knowledge, and human resource training. It was concluded that the indicators evaluating research seedbeds seek greater scientific development involving students and improving the quality of research products, which directly impacts the institutional research mission.

Compliance with any policies, laws and regulations, including university compliance with quality assurance mechanisms globally, depends on the practicability of those mechanisms. Like other countries, Tanzania has quality assurance mechanisms that require universities to comply. However, the existing audit reports have shown non-compliance cases to such mechanisms. This study sought to explore the practicability of the existing quality assurance mechanisms in promoting universities’ compliance in Tanzania. The documentary reviews, interviews, and focus group discussions were used to collect data from the 4 universities and 46 students, academics, and quality assurance directors and officers as a sample size selected purposively. The data were analysed through content analysis. The findings revealed that the existing quality assurance mechanisms are generally practicable; however, there are quality assurance requirements with practicability challenges due to contextual factors. Such requirements include senior academics in administrative duties, academics’ promotion, academics’ recruitment, inclusive and participatory teaching approaches, requirements with extra financial costs, examination scripts’ marking, and invigilation restrictions. This study concludes that the practicability challenges of some quality assurance mechanisms are one reason for non-compliance cases at some Tanzanian universities. It recommends that key stakeholders be involved in establishing mechanisms, and all contextual factors must be addressed to enhance practicability.

Research in higher education has revealed a significant connection between executive functions (EF) and study success. Previous investigations have typically assessed EF using either neuropsychological tasks, which provide direct and objective measures of core EF such as inhibition, working memory, and cognitive flexibility, or self-report questionnaires, which offer indirect and subjective assessments. However, studies rarely utilize both assessment methods simultaneously despite their potential to offer complementary insights into EF. This study aims to evaluate the predictive capabilities of performance-based and self-reported EF measures on study success. Employing a retrospective cohort design, 748 first-year Applied Psychology students completed performance-based and self-report questionnaires to assess EF. Maximum likelihood correlations were computed for 474 students, with data from 562-586 first-year students subsequently subjected to hierarchical regression analysis, accommodating pairwise missing values. Our results demonstrate minimal overlap between performance-based and self-reported EF measures. Additionally, the model incorporating self-reported EF accounted for 13% of the variance in study success after one year, with the inclusion of performance-based EF raising this proportion to 16%. Self-reported EF assessments modestly predict study success. However, monitoring levels of self-reported EF could offer valuable insights for students and educational institutions, given that EF play a crucial role in learning. Additionally, one in five students reports experiencing significant EF difficulties, highlighting the importance of addressing EF concerns for learning and study success.

This study investigates the social attitudes and acceptance levels towards Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual, and other sexualities and gender identities, collectively referred to as LGBTQIA+, among students within the College of Education at Nueva Ecija University of Science and Technology. Employing a descriptive correlational research design, the research utilized surveys and interviews to collect data from a diverse student body, analyzing their perspectives on LGBTQIA+ inclusion and the impact of educational environments on their acceptance levels. Results indicate a generally positive attitude and high acceptance of LGBTQIA+ students, with significant relationships identified between students' acceptance levels and their gender and year level, while no significant correlations were found with their course and religion. The study emphasizes the critical role of educational settings in fostering an inclusive atmosphere that supports LGBTQIA+ students, highlighting the importance of promoting understanding and acceptance to enhance the educational experience for all students. By shedding light on current attitudes and acceptance levels, this research contributes valuable insights into the efforts required to create more inclusive educational environments for LGBTQIA+ individuals. The findings are of particular relevance to educators, policymakers, and educational researchers interested in advancing LGBTQIA+ inclusion within educational settings.

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.

Considering the importance of the results of national and international standardized tests, which are a benchmark for measuring educational quality, the objective of this research was to model strategies to improve the results of the evaluations, specifically the Saber 11 standardized tests. These tests are applied to students who finish their Vocational Education and Training (VET) in Bogotá, Colombia. To achieve this objective, we employed the Systems Dynamics methodology for a comprehensive analysis, which is a tool that allows for the analysis and projecting of the behavior of different systems, in which anticipation by means of modeling results over time is required. The modeling was conducted in two stages: First, a causal loop diagram and a stock-and-flow diagram that linked 45 variables were designed, showing the underlying physical structure of the system. Then, five groups of alternative simulations were conducted over a time frame of six years: Reference mode, student self-efficacy rate, management rate, teaching competencies rate, and educational policy. An increase in results was observed in each scenario. The combined activity of educational stakeholders is a notably effective strategy to achieve significant improvements. The data used for these simulations came from a six-year period of standardized test results in Bogotá. This period was selected to capture both recent trends and long-term outcomes, ensuring that the model reflects current educational conditions while allowing for meaningful trend analysis.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

This study evaluates the impact of an educational intervention strategy – Project-Based Learning (PBL) – designed to enhance university students' knowledge of the Sustainable Development Goals (SDGs), their integration into academic curricula, and their relevance for future professional and personal applications. The research is motivated by the recognised importance of the SDGs in education and the current limited integration and understanding within higher education settings. The study applied a pre-test and post-test experimental design used, involving 199 first-year students from the University of Cordoba (Spain), enrolled in Primary and Early Childhood Education programmes. The intervention comprised PBL activities aimed at increasing knowledge and perceptions of the SDGs. Data were collected using a questionnaire assessing three dimensions: knowledge of the SDGs, the importance of their inclusion in the curriculum, and the perceived relevance of applying SDG principles in professional and personal contexts. The findings indicate that the intervention strategy effectively improved, albeit partially, students' understanding and perception of the SDGs. There was a significant improvement in students' knowledge. However, regarding the perceived importance of integrating the SDGs into their curriculum and the relevance of the SDGs for their future professional and personal lives, no effects were observed. These results underscore the partial efficacy of PBL in promoting sustainability competences and global citizenship among students, suggesting the need to explore other pedagogical methodologies for greater effectiveness. The study advocates the integration of SDGs into higher education curricula to better prepare students for future challenges, emphasising the need for further research to explore the long-term impacts and broader applicability of such educational intervention.

Research fronts are dynamic, knowledge-driven clusters of scholarly activity that emerge in response to pressing problems and/or groundbreaking discoveries. Clarivate Analytics provided a valuable tool based on Citation Productivity and Trajectory (CPT) indicator, which successfully identified particularly hot research fronts on a global scale. To enhance the accuracy and comprehensiveness of identifying both active and emerging research trends, this study develops an extended Clarivate formulation incorporating a novel Impact Factor (IF) metric. The refined approach incorporates growth rates, publication productivity, and the average publication gap between published and citing publications. This method is applied to exploring key research fronts in the digital education ecosystem using bibliometric data from the Scopus database in the period of 2019-2023. The results reveal that artificial intelligence and online learning are the most prominent and influential fields, with virtual reality, blockchain, hybrid learning, and digital literacy representing fast-growing areas. By analyzing both quantitative and qualitative aspects, this work informs key stakeholders about the evolving priorities and trends in the digital educational landscape.

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.

The use of technology in education aims to improve students' problem-solving skills so that they have the skills needed by 21st century society in dealing with various kinds of challenges and problems. This study was carried out aiming to obtain the characteristics of augmented reality-based learning media for mathematics learning in student problem-solving skill, and obtain the results of the average difference in the problem-solving abilities of junior high school students. This research and development (R&D) study, employing the (Analyze, Design, Develop, Implement, and Evaluate) ADDIE model, investigated Augmented Reality (AR)-based learning media for mathematics to enhance junior high school students' problem-solving skills. The aim was to identify characteristics of effective AR media and assess their impact on problem-solving abilities. Quantitative data, collected from student problem-solving tests, were analyzed using a t-test in SPSS. The AR media featured virtual manipulation, virtual measurement tools, and real-world problem exploration. While the experimental group using AR showed a higher average problem-solving score compared to the control group using Problem-Based Learning (PBL), the difference was not statistically significant (t (df) = 0.638, Cohen's d = 0.0876). This lack of significance, despite the higher mean, is likely due to a small sample size and the limited integration timeframe, coupled with pre-existing skill variations. Future research should address these limitations to further explore the potential of AR in mathematics 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.