With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

E-learning has become an integral part of higher education, significantly influencing the teaching and learning landscape. This study investigates the impact of student characteristics such as gender, grade, and major on E-learning satisfaction. Utilizing Structural Equation Modeling (SEM) and collecting data through 527 valid questionnaires from Nanjing Normal University students, this research reveals the nuanced relationships between these variables and E-learning satisfaction. The findings indicate that gender, grade, and major significantly and positively impact student satisfaction with E-learning, highlighting the need for tailored E-learning resources to meet diverse student needs. The study underscores the importance of continuous improvement in E-learning resources and platforms to enhance student satisfaction. This research contributes to the understanding of effective E-learning strategies in higher education institutions.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.

The digital era has transformed education, making digital literacy essential for teachers to integrate technology and enhance student outcomes effectively. This study aims to examine how school culture influences teachers’ performance through their digital literacy, focusing on junior high school teachers in Malang City, East Java, Indonesia. Employing a quantitative approach, data were collected from 214 teachers out of a 457 population using questionnaires. The analysis was conducted through AMOS for Confirmatory Factor Analysis (CFA), SPSS for descriptive statistics, and PLS-SEM for hypothesis testing. The findings reveal that school culture significantly affects teachers’ digital literacy (Ho1) and teacher performance (Ho2) with supportive and innovative environments, while rigid cultures limit creativity. Furthermore, digital literacy was found to enhance teachers’ performance (Ho3) and mediate the impact of school culture on teachers’ performance (Ho4), enhancing teachers’ effectiveness in planning, implementing, and evaluating instruction. This study highlights the critical role of school culture in shaping digital literacy and offers new insights for improving teacher practices in diverse educational settings. Moreover, the role of education policies in fostering a collaborative school culture that enhances teachers’ digital literacy and performance, leading to improved educational outcomes, plays a crucial implication.

The technology known as Internet of Things, or IoT, has started to permeate many facets of our lives and offers a plethora of options and empowerment, expanding the potentials of integrating it in education. Considering how new IoT is and how it may affect education, it is now essential to investigate its potential in order to choose where to begin using it in the classroom. Examining the possible applications of IoT in education may be strongly aided by the knowledge and perspectives of professionals and experts. As a result, the present research concentrated on looking at and evaluating the viewpoints that relevant experts shared on platform (X) via a variety of tweets. The present study takes a qualitative approach, analyzing a collection of expert tweets on IoT in education on platform X using qualitative content analysis. The primary themes of the study findings, the software-based and material-based enablers of IoT in education, indicate the key potentials of IoT in education. These consist of data, sensors, interactive devices, e-learning tools, network accessibility and communications, integrating developing technologies, and system administration. The enormous individual enablers of IoT in education also include sustainability, professional growth, planning, preparing the next generation, and upholding the safety of the learning environment. The study suggested that in order to handle the IoT, classrooms and the educational environment needed to be restructured. Additionally, human resources needed to be developed in order to keep up with the educational environment’s progress.