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The concept of Mobile learning has paved a prospective innovation in modern education. Mobile learning environment creates new opportunity of rich technology enhanced presentation and interaction for learners. Virtual and Augmented reality (VR/AR) are new concept and tools that support them portability, accessibility, flexibility and timeless in various learning activities and resources, in the combination of real-world and computer-generated platform. Integrated VR/AR in learning environment considered for educators as being an effective approach to enhancing students’ creativity, competencies in practice. Furthermore, VR/AR integration in mobile learning requires concepts of the framework which can be related traditional learning theories, its potential applications, current challenges and future directions for designing and developing educational lesson-experiences. A conceptual framework has been presented to address the design and integration emerging technology VR/AR to support and facilitate immersive learning environment.

Right off the bat, the ideas and arrangement about imagined information mining innovation expounds in this paper, data mining at that point the innovation and regression analysis technology and the visualization data, what’s more, are talked about; finally, the use of data mining addressed in combination with sliding bearing wear coefficient testing, regression analysis technology and data visualization. In this paper structure, a framework to actualize data mining technology for visualized data mining under the web condition. Data visualization helps to explore data with some satisfactory results in a powerful way. Also, as a part of the data reduction process by combining data, a significant role has been played by data visualization. The linear and nonlinear regression analyses are used in this method, and application research progresses to proving the factors in our methods.

In the first European Education Summit in January 2018, the European Commission broadened the theme of New Skills Agenda for Europe. In terms of education, transformation and educational technology to enhance innovation, an integrated learning process may force long-term strategic objectives for students with lifelong learning, mobility, enhancing creativity, innovation, and entrepreneurship. Vietnam is one of the world’s most rapidly improving education systems and it is undertaking major reforms on teaching, learning, and leadership. One of Vietnam’s efforts to innovate and improve the quality of education is promulgating the 2018 standards for principals and professional standards for teachers at all levels. Applications of today’s technologies allow learners to connect with diverse data sources in various fields, and in multiple formats beyond the physical campus of schools. Optimistic projections about the rapid developments in physical, digital, and biological technology will urge redefinition and accordingly proper execution in education.

The conceptual model of smart university has been generalized as a digital transformation-oriented higher educational institution using digital infrastructure (digital legal, digital human resources, digital data, digital technologies and digital applications) to provide personalized learning services to learners of all generations in the country and around the world, meeting the lifelong learning requirements and sustainable development of individuals as well as nations. It is described through the V-SMARTH model, including 6 basic components of digital resources, open access learning materials, virtual learning environment, individualized education, interactive learning and digital platform. These elements come together in three pillars of digitization, digital learning model innovation and comprehensive digital transformation process. The study also approached the notion of the smartness and the readiness level of the smart university. In particular, the issue of performance metrics of smart universities has been developed and implemented with the UPM rating for the VNU University of Engineering and Technology.

Today’s students are digital natives who learn best when they have in hand digital tools for various interactive experiences. Digital transformation in education, mobile/wearable devices, and applications, BYOD/BYOTs do this, but it can be a complex process, especially in pedagogical aspects. There is also change the conception of ICT use in education by well-known educational technology preferably digital trend in advance. In Vietnam, mobile device ownership is increasing day by day. Relatively, discussions on the benefits of mobile device applications in education.

This paper presents a model for forecasting the learning outcomes and suggesting the recommend courses for undergraduate students. In this research, we propose methods based on machine learning techniques and recommender systems to answer three research questions of forecasting student’s outcomes problem: (1) How to forecast the course’s grade for the next subject. (2) How to predict the final grade point average basing on the subjects students have studied. (3) How to suggest a list of subjects that students should learn in the next semester. The model has been tested with the grade data in 22-course subjects with the participation of 580 students. The results, in the best case, for predicting the missing subject grades with the tested data set were 0.656, a good result for scores in the range [0, 10]. Assessing the user’s satisfaction of the model through the survey, the results show that 68.2% of students think that the system is useful for them.

The title co-crystal, C9H9NO2·C6H6O2, is composed of one 2,6-diacetylpyridine molecule and one resorcinol molecule as the asymmetric unit. In the 2,6-diacetylpyridine molecule, the two carbonyl groups are antiperiplanar to the pyridine N atom. In the crystal, the 2,6-diacetylpyridine and resorcinol molecules are connected by two O-H...O hydrogen bonds, forming planar chains of alternating components running along [120].