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.

Momentum-impulse requires critical thinking skills, and teaching should be encouraging for students. Critical thinking skills can be fostered through inquiry-based learning. During the COVID-19 pandemic, familiar learning media were used for students. Therefore, it is necessary to develop creative learning media. This developmental research aimed to create a momentum-impulse e-book based on inquiry supported by infographics (MIB -In-graph) to enhance students' critical thinking skills. The developmental model was a 4D model with field testing, i.e., a pretest-posttest control group design with three classes. Descriptive analysis showed that MIB-In-graph, an Android application, received a good average rating in content, worksheets, and forms. Students’ responses were very positive. Mixed design ANOVA showed that the mean score of students’ critical thinking skills increased significantly from the pretest to the posttest in each class and students’ critical thinking skills in the experimental class was more salient than control class 1 and control class 2. The highest difference in mean scores was in the experimental class. The differences were influenced by various factors such as learning approaches, media use, pictures, and collaboration.

Due to irregular daytime routines, chronotype changes, side jobs and exam periods after the COVID-19 pandemic, university students are trying to find new balances in their everyday life. The aim of the present study is to analyze the impact of daytime chronotype and hour preferences for the circadian rhythm on academic achievement among university students, considering their sleep habits and class frequencies in daytime and nighttime classes. Furthermore, this study aimed to analyze the differences in chronotype preferences with regard to age, sex, and academic schedule students are attending. A sample of 87 university second-year Psychology and Management students attending the academic year 2021/2022 after the governmental relief measures of the COVID-19 pandemic completed a 13-item questionnaire on sleep habits and preferences. Further variables encompassed sleep behaviors, such as age, sex, daytime and nighttime classes, as well as academic achievement. The results of the study showed that university students had a higher preference for the morningness type. Additionally, chronotype traits explained 30% (values from regression analysis) of academic achievement but did not directly impact academic results. The sleep-wake cycle diverged among age groups because the youngest participants (19–21 years old) and older participants (35–44 years old) reported higher academic scores during the first semester and the full academic year. No significant differences were identified with respect to sex. There is a lack of literature explaining the effect of sleep hours on academic achievement among students after stay-at-home rules during the COVID-19 pandemic. Thus, it is imperative to understand the difficulties students face with regard to their studying hours, working shifts, and daytime or nighttime classes to create a sustainable university system that attends to students’ needs and necessities.

Psychosocial and educational intervention approaches employ diverse treatment frameworks, most of which involve delivering some form of feedback to participants about their behavior. General conceptions of feedback are well-known to underlie mainstream therapeutic and educational approaches. Recently emerging ‘smart’ approaches also rely on feedback principles. However, little scholarship is available to stitch together evolving strands of feedback principles and no literature characterizes explicitly the diverse landscape of feedback practices employed in education or intervention science. This paper reviews intrinsic conceptions of feedback along with diverse cases of its use in intervention and education. Based on our consideration, we present a typology of feedback modalities that we hope will enrich the efforts of interventionists and educators to design treatment and educational frameworks incorporating feedback.

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.

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.

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.

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.

Psychological capital (PsyCap) emerges as a pivotal asset for mitigating student burnout in college settings, as it bolsters their learning empowerment and engagement. However, there have been inadequate empirical studies investigating the significance of these resources in promoting engagement and empowerment, ultimately leading to a reduction in students’ burnout within the context of higher education. To bridge this gap, we examined the extent to which PsyCap predicts student burnout through its impacts on academic engagement and learner empowerment. The sample of the study was college students (N = 562) who completed a battery of self-report questionnaires measuring their PsyCap, academic engagement, learner empowerment, and student burnout. We employed hierarchical multiple regression analyses and PROCESS macro to ascertain prediction and serial mediation effects. The results substantiated the hypotheses that PsyCap positively related to learner empowerment and academic engagement while negatively associated with student burnout. Further, students with higher levels of learner empowerment and engagement reported lower levels of burnout in their academic studies. The mediational results also revealed that engagement and learner empowerment acted as significant serial mediators between PsyCap and student burnout. The study’s findings underscore the critical significance of PsyCap within higher education, particularly in nurturing learner empowerment, and engagement, thereby reducing student burnout.

The integration of AI tools in education is reshaping how students view and interact with their learning experiences. As AI usage continues to grow, it becomes increasingly important to understand how students' perceptions of AI technology impact their academic performance and learning behaviours. To investigate these effects, we conducted a correlational study with a sample of 44 students to examine the relationship between students' perceptions of ChatGPT’s utility—focusing on usage frequency, perceived usefulness, accuracy, reliability, and time efficiency—and key academic outcomes, including content mastery, confidence in knowledge, and grade improvement. Additionally, we explored how these perceptions influence student behaviours, such as reliance on ChatGPT, procrastination tendencies, and the potential risk of plagiarism. The canonical correlation analysis revealed a statistically significant relationship between students' perceptions of ChatGPT's utility and their academic outcomes. Students who viewed ChatGPT as reliable and efficient tended to report higher grades, improved understanding of the material, and greater confidence in their knowledge. Furthermore, the bivariate correlation analysis revealed a significant relationship between dependency on ChatGPT and procrastination (r = 0.546, p < .001), indicating that a higher reliance on AI tools may contribute to increased procrastination. No statistically significant association was identified between ChatGPT dependency and the risk of plagiarism. Future research should prioritize the development of strategies that promote the effective use of AI while minimizing the risk of over-reliance. Such efforts can enhance academic integrity and support independent learning. Educators play a critical role in this process by guiding students to balance the advantages of AI with the cultivation of critical thinking skills and adherence to ethical academic practices.

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.