Applying information mining technology in online entrepreneurship training course.

Area of Science:

• Educational Technology
• Data Science
• Entrepreneurship Education

Background:

• Online education growth necessitates effective big data utilization for personalized learning.
• Meeting diverse student needs in online courses is a key challenge.

Purpose of the Study:

• To explore information mining applications in online entrepreneurship training.
• To enhance student learning outcomes and entrepreneurship success rates.
• To optimize teaching processes through data analysis.

Main Methods:

• Information mining techniques applied to student behavioral data (study time, interaction, assessments).
• Machine learning algorithms and association rule mining for data analysis.
• Development of targeted teaching strategies based on data insights.

Main Results:

• Significant improvements in student knowledge mastery and entrepreneurship success rates.
• Enhanced personalized learning experiences and teaching efficiency observed.
• Identification of key factors influencing learning and entrepreneurial success.

Conclusions:

• Information mining technology effectively boosts online entrepreneurship course effectiveness.
• Personalized feedback and optimized learning paths are crucial for success.
• Future integration with AI can further enhance online education intelligence and adaptability.