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.

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.

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.

Augmented reality technologies can create unique interactive learning environments for students with special educational needs that enrich the learning process and provide immediate feedback. This research analyzed the use of augmented reality in teaching digital literacy courses for primary school children with special educational needs. The study involved a quasi-experiment with participants using a mobile augmented reality application to assess its impacts on learning outcomes. The results showed the positive effects of augmented reality on student achievement. The results highlight the potential of augmented reality in inclusive education. In addition, the findings emphasize the importance of further research and development in this area and an increased use of augmented reality to improve the educational experience of students with disabilities. In light of the results, we conclude with recommendations for integrating augmented reality into educational programs and improving educational practices.

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.

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 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 field of engineering education is constantly evolving to meet the challenges of technological and societal advancements. Continuous research should be conducted to identify the potential match between the skills that employers seek and the ones engineering graduates gain at college. The purpose of this study is to identify areas of agreement and disagreement between the faculty and employers regarding the skills and knowledge that engineering students acquire during their undergraduate education. The study uses an explanatory sequential design method by employing a questionnaire that was developed based on the Engineering Competency Model (ECM) by the Employment and Training Administration of the USA Department of Labor and responded to by 125 volunteer engineering faculty. Additionally, interviews were conducted with 2 industry professionals to gain deeper qualitative insights. The study found that while faculty mainly stated that students acquire personal effectiveness, academic, and workplace competencies in college, employers disagreed with these perceptions, particularly regarding interpersonal skills, integrity, professionalism, writing, and communication. Additionally, the study found a significant mismatch between faculty and employer assessments of industry-wide competencies, with employers expressing concerns about graduates' preparedness in areas like design, business, and sustainability. These findings suggest significant updates and cooperation with industry experts in engineering curricula and their implementation.

To ensure a sustainable future, it is important to align educational practices with global sustainability goals. This study examines the impact of integrating the United Nations’ Sustainable Development Goals (SDGs) into a first-year social education methodology course. Using a survey of 70 students, the relationships between students’ knowledge of the SDGs, their academic performance, and their satisfaction with the integration of the SDGs into their course curriculum were analysed. Findings indicated a significant correlation between enhanced understanding of the SDGs and improved academic performance. The incorporation of the SDGs into the course received somewhat mixed evaluations, however, with most students reporting high overall satisfaction but identifying specific aspects as in need of improvement. Despite this, a greater increase in knowledge of the SDGs by the end of the course appeared to enhance students’ overall satisfaction with the teaching project. These outcomes emphasise the complexity of embedding sustainability in higher education, suggesting that while direct academic improvements may be subtle, cultivating knowledge of the SDGs is pivotal for fostering better educational outcomes and greater student satisfaction. Future research should consider longitudinal and qualitative studies to further explore these dynamics and provide deeper insights into the long-term effects and experiential aspects of integrating the SDGs into university education.

This article provides a comprehensive guide to conducting and documenting systematic reviews (SRs) in educational research. While SRs are increasingly recognized for their value in synthesizing and evaluating literature on specific research questions or topics, there remains a notable scarcity of research-based papers that guide their development within the field of education. Systematic reviews, distinguished from traditional literature reviews by their standardized processes—including systematic searching, selection, and critical appraisal of relevant studies—offer a more accurate and comprehensive understanding of the research landscape by integrating findings from multiple sources. This paper underscores the importance of adhering to established methodologies and guidelines to ensure the quality and reliability of SRs. Essential elements discussed include defining research questions, developing search strategies, applying inclusion and exclusion criteria, and synthesizing results. The paper also highlights the role of frameworks such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in enhancing transparency and methodological rigor. By following this structured approach, researchers can produce systematic reviews that provide valuable insights into educational practices and policies, thereby supporting evidence-based decision-making and advancing the field of education.

This research aims to systematically review the integration of artificial intelligence (AI) in English language teaching and learning. It specifically seeks to analyze the current literature to identify how AI could be utilized in English language classrooms, the specific tools and pedagogical approaches employed, and the challenges faced by educators. Using the PRISMA-guided Systematic Literature Review (SLR) methodology, articles were selected from Scopus, Science Direct, and ERIC, and then analyzed thematically with NVivo software. Findings reveal that AI enhances English teaching through tools like grammar checkers, chatbots, and language learning apps, with writing assistance being the most common application (54.55% of studies). Despite its benefits, challenges such as academic dishonesty, over-reliance on AI (27.27% of studies), linguistic issues, and technical problems remain significant. The study emphasizes the need for ethical considerations and teacher training to maximize AI’s potential. It also highlights societal concerns, including the digital divide, underscoring the importance of equitable access to AI-powered education for learners of all socioeconomic backgrounds.

The present study examined how empathy (affective and cognitive), basic psychological need satisfaction (autonomy, competence, and relatedness), and demographic factors (gender and academic achievement) jointly predict prosocial behavior during emerging adulthood. Grounded in Self-Determination Theory, this research explored whether relatedness need satisfaction mediates the relationship between empathy and prosocial tendencies. A total of N=889 undergraduate students from a large public university in the southeastern United States completed self-report measures assessing empathy, psychological needs, and prosocial behavior. Path analysis revealed that affective empathy and relatedness satisfaction were significant predictors of prosocial behavior. Relatedness also partially mediated the link between empathy and helping actions. Furthermore, gender and GPA contributed to prosocial outcomes, with female students and those with higher academic achievement reporting greater prosocial tendencies. These findings suggest that fostering emotional engagement and supporting students’ psychological needs—particularly the need for relatedness—may be key mechanisms for promoting prosocial development in educational settings during the critical stage of emerging adulthood.

This study aims to develop and validate the Teachers' Spiritual Leadership Questionnaire (TSLQ) to assess teachers' spiritual leadership from students' perspectives. Grounded in the principles of spiritual leadership—Vision, Hope/Faith, and Altruistic Love—the TSLQ explores how teachers inspire, influence, and guide students toward both academic and holistic development. The study addresses the lack of assessment tools in educational settings and introduces a structured validation process to ensure the instrument's accuracy and reliability. The questionnaire was developed and refined through several stages using expert input, literature review, and statistical validation methods. A total of 402 students participated, and their responses were analyzed using factor analysis to examine the tool's structure and effectiveness. Findings confirmed that the TSLQ is valid and reliable, with strong alignment between items and the three key dimensions of spiritual leadership. The results supported the model's overall strength, indicating that the questionnaire effectively captures the intended constructs. The study concludes that the TSLQ is a sound instrument for understanding spiritual leadership in the classroom and can help educators and researchers better assess its impact on students' academic and personal growth. Further research is recommended to test the tool in different cultural and educational settings and to explore additional dimensions of spiritual leadership. This new tool offers valuable insights for enhancing teaching practices and promoting a supportive and values-driven learning environment.

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 rapid integration of artificial intelligence (AI) technologies into the field of higher education is causing widespread public discourse. However, existing research is fragmented and lacks systematic synthesis, which limits understanding of how college and university students adopt artificial intelligence technologies. To address this gap, we conducted a systematic review following the guidelines of the PRISMA statement, including studies from ScienceDirect, Web of Science, Scopus, PsycARTICLES, SOC INDEX, and Embase databases. A total of 5594 articles were identified in the database search; 112 articles were included in the review. The criteria for inclusion in the review were: (i) publication date; (ii) language; (iii) participants; (iv) object of research. The results of the study showed: (a) The Technology Acceptance Model and the Unified Theory of Technology Acceptance and Use are most often used to explain the AI acceptance; (b) quantitative research methods prevail; (c) AI is mainly used by students to search and process information; (d) technological factors are the most significant factors of AI acceptance; (e) gender, specialty, and country of residence influence the AI acceptance. Finally, several problems and opportunities for future research are highlighted, including problems of psychological well-being, students’ personal and academic development, and the importance of financial, educational, and social support for students in the context of widespread artificial intelligence.