Higher education systems are under increasing pressure to embrace technology-enhanced learning as a meaningful step towards the digital transformation of education. Digital technologies in education promise optimal teaching and learning, but at the same time, they put a strain on education systems to adapt pedagogical strategies. Classical pedagogical frameworks such as Dewey, Piaget, and Vygotsky’s theories focused on student agency and are not specific to contemporary education with ubiquitous digital technologies. Hence, there is a need for a novel and innovative pedagogical framework that aligns with these emerging and advanced digital technologies. However, recent guidelines to incorporate emerging digital technologies in education have largely focused on ethical dimensions and assessment practices. The lack of an overarching pedagogical framework for teaching and learning practices in the digital era is a threat to quality education. The current study proposes a digital pedagogy for sustainable educational transformation (DP4SET) framework applicable to the new modes of teaching and learning powered by digital technologies. The DP4SET framework comprises four components that advocate for digital competence for accessing deep learning, evidence-based practice with quality digital resources, learning environments with applicable digital technology, and synergy between human teachers and trustworthy artificial intelligence (AI). A real-world application of the DP4SET framework in Chinese contexts proves that it promotes the effective use of technology and significantly reshapes teaching and learning in and beyond the classroom. The proposed digital pedagogy framework provides a foundation for modern education systems to accommodate advanced digital technologies for sustainable digital transformation of education.
This study investigates the application of a support vector machine (SVM)-based model for classifying students’ learning abilities in system modeling and simulation courses, aiming at enhancing personalized education. A small dataset, collected from a pre-course questionnaire, is augmented with integer data to improve model performance. The SVM model achieves an accuracy rate of 95.3%. This approach not only benefits courses at Guizhou Minzu University but also has potential for broader application in similar programs in other institutions. The research provides a foundation for creating personalized learning paths using AI technologies, such as AI-generated content, large language models, and knowledge graphs, offering insights for innovative educational practices.
Education digitalization is an inevitable trend of technological development. Based on the theories related to smart classrooms, this research constructs a “3 + 5” teaching model and implements a mixed methods research in Jinshan Elementary School in Chongqing. The “3” in the name refers to three stages of teaching, namely before, during, and after class. The “5” in the name refers to five links of teaching, namely prediction, fine-tuning, detailed explanation, intensive support, and extension. Through questionnaire and interview, it is found that most students and teachers are very satisfied with the “3 + 5” teaching model. The model based on the iFLYTEK smart classroom can accurately locate students’ learning situation, improve classroom efficiency, develop personalized learning plans, and provide data support for the digital transformation of primary school mathematics.
The teaching and research section is the fundamental organizational unit for teaching and research in a university, and the virtual teaching and research section (VTRS) is crucial for the exploration of the digital transformation of new basic teaching organization construction in the information age. However, this new type of organization transcends institutional and spatial boundaries, and motivating participants and sustaining their engagement are key challenges in VTRS implementation. The VTRS for database courses (VTRS-DB) proposes an open community-based operating model, founded on the core concepts of openness, dedication, competition, and orderliness. It establishes a hierarchical organizational structure and working group operation mechanism. After two years of practical exploration, a course knowledge graph and a wealth of teaching experiment cases have been developed. A series of distinctive teaching and research methods, such as collaborative course preparation, have been implemented, and the domestic database in the classroom brand activity has been established. The VTRS-DB has incubated several national and provincial level first-class courses and has won national and provincial level teaching achievement awards, achieving significant results.
