Mathematically Intelligent Human-Computer Collaborative Teaching: Opportunities, Challenges and Countermeasures

  • Lixing Zhao Education & Liberal Studies, City University of Malaysia, Malaysia
  • Hongli Yang College of Education for the Future, Beijing Normal University, China
DOI: https://doi.org/10.30560/ier.v7n3p11
Keywords: digital intelligence, human-computer collaboration, human-computer co-teaching, artificial intelligence, educational empowerment

Abstract

With the rise of technologies such as Artificial Intelligence (AI), Big Data and Cloud Computing, Digital Intelligence is reshaping the education landscape in far-reaching ways, opening up new paths for education modernization. As a transformative model, human-computer collaborative teaching provides important opportunities for educational practices through the integration of intelligent technologies and traditional educational practices: technology empowerment to promote teaching innovation, optimal allocation of resources to enhance educational equity, support for personalized learning to achieve tailored teaching, and role diversification to help teachers transform. However, there are also many challenges: insufficient technology integration limits practical application, data ethics and privacy issues raise potential risks, lack of standards and quality exacerbates the lack of regulation, and conflicting roles in collaboration hinders management transformation. Based on this, proposed solutions include enhancing the technological literacy of teachers and learners, strengthening data privacy protection frameworks, optimizing instructional systems to support personalized learning, and building educational ecosystems that promote collaboration and adaptability. This paper aims to provide a comprehensive framework to guide the advancement of education modernization and ensure that it matches the needs and potential of digital intelligence.

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Logic diagram of countermeasures for digital intelligent human-machine collaborative teaching
Published
2024-12-05
Issue
Vol 7 No 3 (2024)
Section
Articles
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