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 examined how a dialogic approach in an online media literacy class at a university in China helped to develop college students’ global awareness when the world was disrupted by the coronavirus disease (COVID-19). Using writing exemplars from students’ online dialogues and reflective journals, this article demonstrates the potentialities of an online dialogic approach to guide a sense of togetherness and critical solidarity. The digital dialogical approach provides an expanded space for students to converse with multiple voices, meditate on tensions, and rethink their own stances as citizens of their country and the world. The article also underscores the role of higher education in cultivating a sense of global community among the younger generation and bridging the ideological divide in society.
With the rapid growth of information technology, digital textbooks, as a crucial component of education digitalization, are gradually emerging as a key tool for teaching in higher education institutions. They transcend the limitations of traditional textbooks, providing a broader scope and a wealth of resources for teaching. Digital textbooks present knowledge through diverse formats, including multimedia content and interactive sessions, thereby enhancing student’s engagement and interest in learning. Furthermore, they can be updated at any time to keep abreast of the development in various disciplines and to meet the needs of the times, ensuring that students can access the latest and accurate information. In addition, digital textbooks can help promote educational equity by making quality educational resources accessible to a broader range of students. As
New quality productive forces characterized by innovation and innovation-driven development are essentially talent-driven. The cultivation of engineering practice and innovation ability of science and engineering talents is closely related to the development of national science and technology. It serves as a decisive factor in seizing opportunities of the new round of scientific and technological revolution and industrial change. To align digital engineering graphics education with the evolving demands of industries driven by new quality productive forces and engineering practice, this paper proposes teaching methods based on digital teaching practices at Tianjin University. These methods aim to deepen students’ understanding of new quality productive forces in engineering practice. The knowledge map of new quality productive forces is designed to enhance students’ innovation ability based on cartographic knowledge. It achieves this by refining typical engineering application scenarios that address global scientific and technological issues, tackle economic challenges, meet national strategic needs, and improve people’s life and health. This approach aims to cultivate innovative engineering and technical talents with a solid theoretical foundation, comprehensive innovation abilities, and strong engineering practice ability.
Generative artificial intelligence (GenAI), achieving human-like capabilities in interpreting, summarising, creating, and predicting language, has sparked significant interest, leading to extensive exploration and discussion in educational applications. However, the frontline practice of education stakeholders or the conceptual discussion of theorists alone is not sufficient to deeply understand and reshape the application of GenAI in education, and rigorous empirical research and data-based evidence are essential. In the past two years, a large number of empirical studies on GenAI in education have emerged, but there is still a lack of systematic reviews to summarise and analyse the current empirical studies in this field to evaluate existing progress and inform future research. Therefore, this work systematically reviews and analyses 48 recent empirical studies on GenAI in education, detailing their general characteristics and empirical findings regarding promises and concerns, while also outlining current needs and future directions. Our findings highlight GenAI’s role as an assistant and facilitator in learning support, a subject expert and instructional designer in teaching support, and its contributions to diverse feedback methods and emerging assessment opportunities. The empirical studies also raise concerns such as the impact of GenAI imperfections on feedback quality, ethical dilemmas in complex task applications, and mismatches between artificial intelligence (AI)-enabled teaching and user competencies. Our review also summarises and elaborates on essential areas such as AI literacy and integration, the impact of GenAI on the efficiency of educational processes, collaborative dynamics between AI and teachers, the importance of addressing students’ metacognition with GenAI, and the potential for transformative assessments. These insights provide valuable guidelines for future empirical research on GenAI in education.
