Abstract: Objective: To explore the digital transformation path of the smart education model in pharmacology. Methods: Based on
the Superstar Learning Platform, a "three-stage progressive" teaching model of "intelligent pre-class guidance—immersive interactive
during class—consolidation and expansion after class" was designed following the principles of student-centered, contextualized learn⁃
ing and process-based assessment. The teaching process was restructured using a task-driven approach, and knowledge graphs were
used to establish knowledge associations and recommend personalized learning paths. Results: This teaching approach met the stu⁃
dents′ needs for progressive learning, created a more dynamic classroom atmosphere, enhanced their learning interest, and addressed
limitations of traditional and current blended teaching models in personalized support, process evaluation, and effectiveness quantifica⁃
tion. Conclusion: The "three-stage progressive" teaching model can effectively enhance teaching interactivity, students′ learning effi⁃
ciency, and clinical knowledge application. It provides a replicable pathway and a practical case study for the digital transformation of
pharmacology and even medical education as well as the construction of AI courses.

Key words: digital transformation in education, pharmacology, smart education, task-driven approach, knowledge graph