# The impact of online real-time teaching interaction on teaching effect among undergraduate nursing students: the mediating role of deep learning

**Authors:** Dongmei Liu, Wanpeng Zhen, Shenzhen Yi, Yongchao Jin, Ye Lin, Rui Yang

PMC · DOI: 10.3389/fpubh.2026.1715936 · 2026-01-30

## TL;DR

This study shows that online real-time teaching interactions improve nursing students' learning outcomes, partly by encouraging deeper learning.

## Contribution

The novel contribution is identifying deep learning as a partial mediator between online teaching interactions and teaching effectiveness in nursing education.

## Key findings

- Deep learning and teaching effect are significantly correlated (r = 0.407, p < 0.01).
- Online real-time teaching interactions correlate with teaching effect (r = 0.398, p < 0.01).
- Deep learning partially mediates the relationship, accounting for 36.344% of the total effect.

## Abstract

With the deep integration of information technology and education, online teaching has become an important form of nursing education. However, students may encounter problems such as low participation and difficulty in internalizing knowledge during online learning. Existing studies have shown that deep learning plays a key role in promoting students’ learning outcomes and professional skills development, but its mediating role between online real-time teaching interaction and teaching effect among undergraduate nursing students has not been fully studied.

This study aims to explore the relationships among online real-time teaching interactions, deep learning, and online teaching effect for undergraduate nursing students, with a focus on analyzing the mediating role of deep learning in the relationship between online real-time teaching interactions and teaching effect.

A total of 587 nursing students from the universities in Hebei Province offering nursing programs were recruited via convenience sampling to complete the questionnaire survey. The research instruments included the online real-time teaching interaction scale, the deep learning scale, and the teaching effect scale. Data analysis was performed using SPSSAU, which involved descriptive statistics, correlation analysis, regression analysis, and a test of the mediating effect of deep learning.

There is a significant positive correlation between deep learning and teaching effect among undergraduate nursing students (r = 0.407, p < 0.01), as well as between online real-time teaching interactions and teaching effect (r = 0.398, p < 0.01). Deep learning acts as a partial mediator in the relationship between online real-time teaching interactions and teaching effect, with a mediating effect value of 0.165, accounting for 36.344% of the total effect.

This study reveals that online real-time teaching interaction not only directly and positively predicts the teaching effect of undergraduate nursing students but also exerts an indirect influence by enhancing their deep learning levels. The results indicate that in online nursing education, the intentional design of interactive segments that promote deep learning is crucial. Educators should focus on constructing an interactive environment capable of stimulating higher-order thinking among nursing students to more effectively enhance the quality of online teaching.

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12903777/full.md

---
Source: https://tomesphere.com/paper/PMC12903777