Author(s)

Yan Ding ¹

Affiliation(s)

¹ Guangzhou College of Technology and Business, Guangzhou, Guangdong, 510850, China

Corresponding Author

Yan Ding

ABSTRACT

Nowadays, the rapid development of artificial intelligence has brought unprecedented opportunities and challenges to higher education. University students generally believe that "knowledge mastered by AI is equivalent to their own mastery," which leads to educational dilemmas such as cognitive laziness and low learning motivation. Based on constructivist learning theory, self-determination theory, and human-machine collaboration concepts, this paper focuses on analyzing the psychological mechanisms behind university students' misconceptions about artificial intelligence and constructs a "human-machine symbiotic" learning model. The research is conducted from four aspects: role positioning reconstruction, curriculum teaching innovation, core competency cultivation, and teacher role transformation.

KEYWORDS

Artificial Intelligence; Higher Education; Learning Motivation; Human-Machine Symbiosis; Teaching Reform; Python Teaching

CITE THIS PAPER

Yan Ding, Research on Reshaping College Students' Learning Motivation and Teaching Pathways in the AI Era-Taking Python Course as an Example. Advances in Educational Technology and Psychology (2025) Vol. 9: 96-105. DOI: http://dx.doi.org/10.23977/aetp.2025.090615.

REFERENCES

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Sponsors, Associates, and Links

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• Curriculum and Teaching Methodology
  
  
• Transactions on Comparative Education
  
  
• Applied & Educational Psychology
  
  
• Advances in Vocational and Technical Education
  
  
• Adult and Higher Education