Big data analytics platform enhances teaching abilities in normal university students through triple helix collaboration.
Juan Zhao, Zhongjun Hu
Abstract
Open AccessNormal university students face significant challenges in developing comprehensive teaching competencies due to the lack of data-driven feedback and systematic assessment mechanisms in traditional teacher education programs. This research develops and validates an educational practice big data analysis platform guided by Triple Helix theory, which systematically integrates university pedagogical expertise, industry technological capabilities, and governmental educational standards. Through a 16-week quasi-experimental study with 378 participants, the platform demonstrated significant improvements in teaching abilities, with experimental group participants achieving substantial gains in teaching implementation (28.4%), student engagement (25.9%), and technology integration (22.6%) compared to control group. These findings establish that data-driven approaches embedded within cross-sector collaboration frameworks provide effective pathways for transforming teacher education practices.