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.

Teaching is a demanding and complex exercise, exposed to the direct or immediate resolution of multiple problematic situations, whether pedagogical, relational, or socio-affective. The teacher's personal resources are often insufficient to cope with the profession's demands. The research reports that there is a gap between research and educational practice. Hence, the objective of this research was to analyze the criteria used by early childhood educators to attribute validity to the written sources of information that guide their pedagogical decisions. The present study follows a qualitative research methodology. The sample for this study was non-probabilistic and consisted of 18 early childhood educators who participated through semi-structured interviews and discussion groups. The data obtained were analyzed by inductive categorization using NVivo 14. The findings revealed that the validity criteria assigned by the educators about the sources of information related to theoretical aspects is mainly attributed to the texts and authors they know, while those referring to practical aspects are attributed to their own experiences or the other educators at the same level. The results showed that specific information and obtaining it in the shortest possible time were the criteria that determined the use of information sources.

The wide use of the Internet of Things (IoT) in all spheres of life has led to a surge of cyberbullying among learners worldwide. That is why it cannot be denied that underlying factors, manifestations, consequences, and preventive measures of cyberbullying improve the welfare and overall mental development of students. This systematic literature review examines the causes, effects, and preventive measures of cyberbullying based on empirical studies conducted on learners in various situations. The review will focus on existing material published between 2015 and April 2024. For the inclusion and exclusion of literature, the Scopus online database was employed, along with the guidelines of the PRISMA model. Of 1004 studies, 51 were closely reviewed to determine the responses to the objectives of this study. NVIVO-12 was used for both thematic and content analysis in this study. The results show that there are 29 causes, 12 forms, 31 effects, and 41 different preventives for cyberbullying. The results of this study will not only enhance the comprehension of various concerns for parents, guardians, policymakers, educators, and governments but also provide valuable insights to researchers for addressing this issue.

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.