The Effects of Teaching Presence and Learning Environment Preference on College Students' Deep Learning in the Rotational Synchronous Teaching Model

To understand the effectiveness of the rotational synchronous teaching (RST) model on students' learning, a mediation model was conducted to investigate the effects of teaching presence and learning environment preference on college students' deep learning in RST. A total of 274 college students completed the survey. The correlation analysis results show that teaching presence and learning environment preference are positively related to deep learning. At the same time, teaching presence is also found positively related to learning environment preference. The mediation analysis results indicate that teaching presence directly predicts deep learning and also indirectly predicts deep learning via learning environment preference after controlling for gender. That is, learning environment preference plays a partial mediating role between teaching presence and deep learning.