This article presents a vision of what the digital transformation in education could look like and what some of its benefits and challenges are. It argues that digital technology, including artificial intelligence (AI), could improve the effectiveness and quality of education by personalizing education, by making it more inclusive and equitable, and by improving the cost-efficiency of the sector. A digital transformation of education also comes with risks that must be mitigated.

Personalized education, tailored to individual student needs, leverages educational technology and artificial intelligence (AI) in the digital age to enhance learning effectiveness. The integration of AI in educational platforms provides insights into academic performance, learning preferences, and behaviors, optimizing the personal learning process. Driven by data mining techniques, it not only benefits students but also provides educators and institutions with tools to craft customized learning experiences. To offer a comprehensive review of recent advancements in personalized educational data mining, this paper focuses on four primary scenarios: educational recommendation, cognitive diagnosis, knowledge tracing, and learning analysis. This paper presents a structured taxonomy for each area, compiles commonly used datasets, and identifies future research directions, emphasizing the role of data mining in enhancing personalized education and paving the way for future exploration and innovation.

With the initiation of the National Virtual Simulation Experimental Teaching Project in 2018, educational institutions in China have recognized the significance of virtual simulation technology in reforming traditional teaching methods and fostering innovative talent cultivation models. Within the realm of higher education in China, motivating students to sustain their utilization of Virtual Simulation Learning Systems (VSLSs) has become a significant challenge. This article builds upon an assessment of the development status of VSLSs in Chinese higher education and draws upon previous studies to construct a model comprising three dimensions: perceived quality, perceived value, and social influence, with the aim of predicting students’ enduring willingness to engage with VSLSs. To achieve this objective, a structural modeling analysis approach is employed to explore the interrelationships among the constructs under investigation, while a survey questionnaire is utilized to collect relevant data. The sample population consists of 274 college students from diverse disciplinary fields in China, including Science, Technology, Engineering, and Mathematics (STEM) and Humanities, Arts, and Social Sciences (HASS). The findings reveal that perceived value significantly influences students’ willingness to participate, with perceived benefits exerting a greater impact than perceived costs. Furthermore, the overall quality of the VSLSs, encompassing aspects such as software quality, instructional design quality, and virtual simulation quality, holds substantial influence over students’ perceived value. Additionally, societal factors such as course scheduling and recommendations from teachers exhibit a positive impact on students’ intention to continue using VSLSs. Building upon these findings, the article presents relevant recommendations aimed at enhancing students’ sustained utilization of VSLSs.

The emergence of general artificial intelligence (AI) model technology, notably ChatGPT, has substantially transformed contemporary approaches to knowledge exploration and acquisition, presenting significant challenges to educational concepts and methodologies. This article initially delineates the myriad obstacles encountered in learning during the AI era and meticulously scrutinizes the attributes and limitations of conventional educational concepts and instructional approaches, which are prevalent in examination-oriented education in primary and secondary schools. Commencing with the requisites of “human beings” and transition “to adulthood,” it delves into the educational objectives of fostering individuals and advocates for the fundamental integration of education within the realm of philosophy. Subsequently, by elucidating the correlation between “fish” and “fishing” in conjunction with the concept of the History and Philosophy of Science (HPS), it furnishes numerous illustrations of incorporating the thoughts and methodologies of scientists in the exploration and resolution of problems within the classroom. The article underscores the profundity of insight of educators compared to adult cogitation and the perceptual limitations of adolescent students, underscoring the imperative for educators to concentrate on guiding students in their pedagogy.

This article presents the progress of Project 101, an initiative starting from December 2021, to improve computer science curriculum and teaching in top Chinese universities, in order to meet the demand of computer science eduction in the new information age. Project 101 aims at improving classroom teaching, while focusing on the development of core courses, core textbooks, core practice platforms, as well as core faculty training. We present an overview of the organization and plan of Project 101, as well as the current progress after two years’ efforts from the working group of Project 101. Finally, we will also discuss tentative future plans aiming at improving computer science education in a large number of universities based on the current results.