Publishing research is crucial and is of utmost significance. However, it is a daunting task for most researchers, especially if one is a beginner with very limited experience. The generalizability of much of the previously published research was limited to the negative aspects of the publishing process rather than the whole circumstances they had to face. Therefore, this article sought to explore the experiences of preservice teachers as novice researchers in publishing their research outputs in a research journal. This study employed a qualitative-phenomenological approach. Five major themes emerged from the interview with eight purposively selected former preservice teachers who had first-time encounters in publishing that the research investigates. These themes were encapsulated through the acronym “FLAME,” namely: (a) facing personal circumstances, (b) leveraging positive dispositions, (c) acknowledging dependency on research promoter, (d) meeting publishing standards, and (e) encountering poor physical and mental well-being. This article concludes that the journal publishing process is a multidimensional and enriching experience, providing the full spectrum of positive and negative experiences for novice researchers. This paper highlighted some implications that can be used as a guide to support novice researchers in the publication process.

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.

School attendance problems are of great research interest, which is reflected in the increase of scientific publications. This increase hinders the adequate follow-up and updating of the scientific community on the subject. The aim of the present bibliometric study lies in the review of the scientific literature published on school attendance problems during 2014-2021. A bibliographic search and analysis of scientific articles was performed, obtaining a definitive sample of 700 documents. Results were extracted and analyzed for the following indicators: temporal productivity, productivity by authors, co-authorship index, productivity by journals, use of topics, research areas addressed and types of samples used. The number of publications indicates a progressive increase of interest on the subject, which has not corresponded to the creation of a specific journal on the subject. There is also evidence of the need for consensus on the topics to be used; the preference for knowing the factors associated with school attendance problems over other areas of research; and the generalized use of community samples as opposed to more specific ones. In conclusion, the characteristics researched on school attendance problems are presented; knowledge that will facilitate the establishment of intervention processes applicable to different contexts and realities.

The world eagerly anticipates advancements in AI technologies, with substantial ongoing research on the potential AI applications in the domain of education. The study aims to analyse publications about the possibilities of artificial intelligence (AI) within higher education, emphasising their bibliometric properties. The data was collected from the Scopus database, uncovering 775 publications on the subject of study from 2000 to 2022, using various keywords. Upon analysis, it was found that the frequency of publications in the study area has risen from 3 in 2000 to 314 in 2022. China and the United States emerged as the most influential countries regarding publications in this area. The findings revealed that “Education and Information Technologies” and the “International Journal of Emerging Technologies in Learning” were the most frequently published journals. “S. Slade” and “P. Prinsloo” received the most citations, making them highly effective researchers. The co-authorship network primarily comprised the United States, Saudi Arabia, the United Kingdom, and China. The emerging themes included machine learning, convolutional neural networks, curriculum, and higher education systems are co-occurred with AI. The continuous expansion of potential AI technologies in higher education calls for increased global collaboration based on shared democratic principles, reaping mutual advantages.

This research aimed to explore the influence of a robotic program using the robot kit "RoboBuilder RQ+110" on students' attitudes toward effective communication. The study used a quantitative research design and involved 475 grade 4 (10 years old) students from Malaysia's Selangor and Malacca states. A quasi-experimental research (pre-test & post-test) approach with control and experimental groups was adopted, and the data were analyzed with inferential statistical test and repeated measures analysis of variance (ANOVA) using SPSS 25 software at 0.05 significance level. Questionnaires were administered to collect data from the experimental and control groups. The results showed statistically significant changes (α ≤ .05) in attitudes toward effective communication for the experimental group that received a robotics program compared with the control group. The study results suggest that innovative technological tools or programs such as robotics programs are recommended as innovative science, technology, engineering, and mathematics (STEM) program rooted in constructivism to improve students' attitudes toward effective communication.

This integrative literature review aims to provide a broader and updated perspective of teachers’ intergenerational learning (IL). The search was done in Web of Science and EBSCO ultimate  databases between 2011 and 2022. Thirty-two empirical studies were selected and submitted to a thematic analysis and five themes were identified: (a) defining and conceptualising generation, (b) IL from understandings to practices, (c) contexts, factors and roles from different generations and institutions to promote IL, (d) factors that facilitate the success of IL, and (e) factors that make IL difficult. Data shows an increase in the last decades of research in IL within the educational context, but an absence of the prospective dimension still prevails. Intergenerational knowledge has been researched mainly from an individual professional perspective at the micro and meso levels of scholarship. Effectiveness requires intentional cultivation and a genuine desire for intergenerational knowledge exchange, involving active engagement and awareness among diverse generations and alignment with organizational aims. The promotion of IL takes place in very different ways and forms, and reflection on what is different seems to be a dominant trait. Furthermore, the review could conclude that intergenerational opportunities to work together will improve teacher education and continuous professional development. 

The ability to think creatively has a vital role in the development of preschool children. This research provides a comprehensive review of innovative approaches and strategies for developing creative thinking in preschool children based on current trends and methodologies used in educational settings. This research shows three significant areas: (a) creative thinking skills in preschool children, (b) factors influencing creative thinking skills in depth, and (c) innovative strategies and approaches to stimulate creative thinking abilities in preschool children. This research uses a literature study method assisted by the publish perish application to find reference sources related to creative thinking abilities in preschool children. Studies show that creative thinking abilities in preschool children enable them to find innovative solutions, help them adapt to challenges, foster self-confidence and courage, and enrich their experience and knowledge of the world around them. Meanwhile, preschool children's creative thinking abilities are influenced by collaboration from the external environment (parents, teachers, and society); providing support and examples for children to develop and stimulate their creative thinking skills is very important.

In the early stages of adopting online learning, both learners and teachers displayed resistance, but the COVID-19 pandemic has forced a widespread shift to digital learning. To facilitate this transition, there is a growing focus on highlighting the effectiveness of online learning, which directly impacts learning outcomes. This study investigates online learning effectiveness through an integrated framework that considers online assessment practices and online course design as independent variables, with online learning support as a moderating variable. Understanding the effectiveness of online learning is crucial as hybrid learning becomes the "new norm" in education, combining online and offline methods for teaching the digital generation. Using a quantitative research design involving 232 students at Universiti Kebangsaan Malaysia, the study found that online assessment practices and course design significantly influence students perceived learning outcomes in an online learning environment. Additionally, online learning support positively moderates this relationship. These findings offer a comprehensive perspective on how online assessment practices, course design, and support systems contribute to the quality of higher education in Malaysia amidst evolving educational practices.

Recently, a large-scale study of college students’ motivation orientations when they transitioned to online learning because of the global COVID-19 pandemic found that unlike prior studies, in the 3 x 2 goal orientation framework the standard for competence (self, other, task) was of greater importance than valence (approach, avoidant). Moreover, previous research found students’ different goal orientations related to how they responded to the shutdown academically from both volition and social perspectives. We investigated whether a three-factor model would replicate with unique undergraduate cross-cultural samples, and we wanted to examine how students with different goal orientations responded to the shutdown of their universities due to the pandemic. Students from a U.S. university and students from Oman completed a 44-item goal orientation survey, a demographic survey, and an 11-item survey to assess students’ experiences following the pandemic. Results indicate that students who set task-based goals were less likely to have negative experiences related to the social aspects of the pandemic and those students who had negative responses to the lack of social contact were also expected to have lower grades.

Critical thinking is a skill that enables individuals to keep pace with changes and enhances crucial competencies for contemporary competitiveness. Many researchers have studied learning management approaches to develop students' critical thinking, resulting in a substantial body of knowledge but lacking clear systematic summaries. The researchers aimed to (a) examine the effect sizes and research characteristics influencing students' critical thinking, and (b) compare the effect sizes of learning management approaches after adjusting with propensity score matching from 108 graduate research published between 2002 and 2021. Data were collected using research characteristics recording forms and research quality assessment questionnaires. Effect sizes were calculated using Glass's method and analyzed through random effect, fixed effect, and regression meta-analysis. Findings revealed that (a) research on developing learning management approaches influences students' critical thinking at a high level (d ̅ = 1.669), with nine research characteristics, including the field of publication, courses, total duration, teacher learning process, learning media, measurement and evaluation, research design, research statistics, and research quality, statistically significantly influencing students' critical thinking, and (b) after adjustment, inquiry-based learning significantly influences students' critical thinking. Recommendations for developing students' critical thinking include learning activities that encourage problem exploration, expanding thinking through collaborative analysis, and applying diverse media and activity sheets tailored to context suitability.
 

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.

This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.

Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.

Digital competence entails the healthy, safe, and responsible use of digital technologies to take engage in society, to learn, work and to interact with. However, the use of digital devices is not exempt of risks. The objectives of this study were to analyze the mediating effect of fear of missing out (FoMO) on phubbing and nomophobia, and to explore the perception of the use of Internet-connected devices among 522 Spanish university students, with an average age of 27.11 years. The 80.8% are women and 68.2% study degrees related with Educational Sciences. A mixed-methods approach was used, combining bivariate correlation with structural equation modelling (SEM), and qualitative content analysis. SEM analysis revealed that FoMO had a significant effect on nomophobia and phubbing. Qualitative content analysis underlined that the time spent, problematic use, and sense of dependence were the main concerns for participants. It is emphasized that the plethora of ICT opportunities exposes individuals to risk contexts, necessitating media education to mitigate psychological and social consequences stemming from Internet risks.

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.

One of the ways to enhance and improve the quality of learning delivery is through the use of technology, particularly the Internet, which facilitates faster and easier access to information. This research aims to explore the degree to which factors such as digital literacy, metacognitive awareness, meaningful learning, habits of using smartphones, and personal learning competence are related to one another. Both the relationship between metacognitive awareness and personal learning competence, as well as the relationship between smartphone habits and personal learning competence, are moderated by a moderating variable known as the fear of missing out. Fear of missing out is a moderating variable. Structural equation modeling, specifically partial least squares, was employed to analyze data from 597 engineering students. SmartPLS version 4 was the tool used for this analysis. The study found that the moderating variable, fear of missing out, significantly impacts metacognitive awareness, learning personal competence, and smartphone habits, making it a crucial factor to investigate. This result is significant because it is a variable that influences the learning that students go through for their education and because it is an extremely important thing to investigate.

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.

Emotional empathy, mindfulness, and subjective well-being are essential to understanding human behavior and mental health among students. However, more research is needed to investigate how these constructs interplay within academic contexts. This study explored the hierarchical relationships between emotional empathy, mindfulness, and subjective well-being. The Multidimensional Emotional Empathy Scale (MDEES), The Kentucky Inventory of Mindfulness Skills (KIMS), and the Subjective Well-Being Scale (WeBs) were administered with a sample of postgraduate professional diplomas in teaching students attending Al Ain University in Abu Dhabi campus and Al Ain campus (n = 1545). The results showed that emotional empathy (positive sharing, suffering, feeling for others, and emotional contagion) positively affects physical and eudaimonic well-being. A negative correlation was found between financial and social well-being and other components of emotional empathy, such as emotional attention and responsive crying. Mindfulness significantly improves emotional empathy in components like describing, accepting without judgment, and observing. This study revealed that some components of mindfulness, such as observing and acting with awareness, decrease emotional empathy, such as suffering and feeling for others. Acting with the awareness component in mindfulness decreases positive sharing, responsive crying, and emotional contagion. Future research could explore these relationships further and examine potential cultural differences.

School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.

The world is looking forward to advancements in artificial intelligence (AI) technology, with significant research underway regarding the application of AI in education. This study analyzed publications on the potential of AI in secondary schools, focusing on its bibliometric aspects. Data from the Scopus database revealed 1,764 publications from 2019 to 2024. The analysis showed a steady annual growth in publications in this area. China and the USA were the leaders in the number of publications. Xiaoyue Wang was the most prolific researcher, having authored 71 AI-related articles. Yueying Li, Xiaoxu Chen, Yanzhu Zhang, and Yi Liu contributed to the field with 56, 55, 53, and 51 articles, respectively. The themes that emerged from 2019 to 2022 are related to media, application, study, institutions, artificial, digital, learning, factors, development, technologies, medical, automated, perception, support, and sustainability. From 2023 to 2024, the topics discussed in AI are related to students, education, perception, algorithms, digital, prediction, networks, challenges, writing, teachers, AI-powered, curriculum, century, integration, technology, and framework. The difference in research in 2019-2022 and 2023-2024 is focusing the theme's focus from the general to the specific. The co-occurrence analysis revealed that prominent keywords appeared in 3 clusters. Cluster 1 is the most popular in recent times. It deals with the application, assessment, and management of AI. Cluster 2 relates to AI relationships and models, while Cluster 3 relates to AI data sources.