Research on cultivating medical students' self-learning ability using teaching system integrated with learning...

Area of Science:

• Medical Education
• Educational Technology
• Big Data in Education

Background:

• The advancement of information technology and big data necessitates developing medical students' self-learning abilities.
• Traditional education models may not adequately foster the crucial skill of knowing how to learn.
• Higher education institutions must cultivate both professional knowledge and self-directed learning skills in medical students.

Purpose of the Study:

• To develop and evaluate a novel teaching system designed to analyze medical students' self-learning processes and outcomes.
• To assess the system's effectiveness in improving self-learning capabilities and addressing learning challenges.
• To enhance the efficiency of in-class question answering and teacher support.

Main Methods:

• Development of a specialized teaching system to track and analyze medical student learning behaviors.
• An experimental study involving 116 medical students across two academic years.
• Comparison of an experimental group using the new system against a control group using traditional classroom teaching.

Main Results:

• The system effectively identified self-learning challenges consistent with those in traditional settings.
• Students using the new system demonstrated improved performance compared to the control group.
• The system facilitated quicker identification of student difficulties by educators.

Conclusions:

• The developed teaching system is effective in supporting and enhancing medical students' self-learning abilities.
• This technology improves educational efficiency by enabling targeted support and faster problem resolution.
• Integrating such systems is crucial for future medical education in the era of big data.