The study aimed to explore the self-directed learning readiness model and its relationship with various factors such as emotional intelligence, transformational parenting, need-supportive teaching style, and self-efficacy as potential mediators. The research was conducted with 415 junior high school students in Surabaya, Indonesia. To ensure the reliability and validity of the instruments used in the study, confirmatory factor analysis was performed. The loading factor values of all the items in the instruments were found to be greater than .50 indicating a satisfactory level of validity. Additionally, the reliability coefficient of all the instruments exceeded .90 demonstrating good internal consistency. Analysis using structural equation modeling (SEM) demonstrated that the theoretical model of self-directed learning readiness was consistent with empirical conditions because it meets the standard value of goodness of fit. Furthermore, through the indirect effect tests, it was discovered that need-supportive teaching style, emotional intelligence, and transformational parenting significantly influenced self-directed learning readiness, with self-efficacy acting as a mediator. Among the factors examined, self-efficacy was found to have the greatest impact in explaining readiness for self-directed learning readiness.

Teachers' learning styles are a crucial part of the learning process as they determine how teachers' brains capture and integrate information linked with the senses. Kurnia, identified as an auditory teacher, was expected to capture written information in a provided numeracy problem. Nevertheless, she prefers to capture visual information, like tables or figures, and utilize them to develop thought-provoking questions. Thus, this study intends to investigate her reasons and the factors affecting Kurnia's decision to utilize visual information as a reference in developing questions. This research adopts a qualitative design covering a case study. Kurnia was selected from 32 teachers from 28 schools; roughly 43% were from public schools, and 57% from private schools. Kurnia placed more emphasis on pictorial information before proposing questions, which was caused by situational factors: the subject matter, the grade level, the student's engagement in the class, the teacher's experience, the teaching experience, and the diversity of students' learning styles. This article recommends that teachers recognize their learning styles to know their strengths and weaknesses in teaching mathematics, and that they convey understandable information utilizing effective instructional methods that represent each learning style of students in the classroom.

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.

<p>&lt;p style=&quot;text-align:justify&quot;&gt;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 &amp;quot;new norm&amp;quot; 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.&lt;/p&gt;</p>

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 article describes a methodology and a didactic innovation in higher education that employs Collaborative Online International Learning (COIL) across four universities in the fields of sociology, psychology, social education and economics in order to explore the phenomenon of economic violence. The COIL activities were developed by four teachers in the second semester of 2022. The students explored the social and cultural origins of economic violence and the daily exposure to economic inequality in the domestic sphere, while also studying the prevention and responses offered by anti-violence centers from both organizational and social perspectives. The most novel aspect of COIL projects is the research approach to the topic (gender violence) and the students' participation in extracurricular activities, namely presenting the results of their research developed during their academic subjects after the course, at international events. In this study, we describe the projects and the assessment of this part of the research, analyzing the perceptions of the Italian and Spanish students who participated in the dissemination activity. The students' perceptions were recorded through a semi-structured questionnaire utilizing Likert scales and open-ended questions, which included their self-assessments of their knowledge before and after participating in the project, the impact on their development of competences and skills, and their satisfaction with the whole experience. Students acquired a great deal of knowledge and understanding of the phenomenon being studied through COIL methodology and connected these extracurricular activities to a clear improvement in their transversal skills.