From “Experience Flood Irrigation” to “Data Drip Irrigation”: Construction and Practice of a Flipped Classroom Teaching Model Based on Generative AI

DOI

10.2991/978-94-6239-733-0_42How to use a DOI?

Keywords

Generative Artificial Intelligence; Flipped Classroom; Vocational Education; Precision Teaching; Human-Machine Collaboration

Abstract

In the localized practice of flipped classrooms in vocational colleges, there has long been a dilemma of “resembling the form but lacking the essence”: pre-class preview lacks depth, in-class interaction fails to go beyond superficial dialogue, and after-class evaluation relies on empirical judgment. The content generation and intelligent interaction capabilities of Generative Artificial Intelligence (GAI) provide a technical fulcrum to break this deadlock. Based on constructivist learning theory and precision teaching theory, this study constructs a “GAI four-dimensional empowered” flipped classroom teaching model. The four dimensions are explicitly defined as: intelligent resource generation, human-machine collaborative scenario construction, real-time interactive feedback, and data-driven learning evaluation. Through the three-stage design of “intelligent pre-class guidance — human-machine collaboration in class — precise after-class improvement”, it realizes the transformation of teaching paradigm from experience-driven to data-driven. A quasi-experimental study was conducted taking the course ‘Web Crawler Technology’ in a higher vocational college as the experimental subject. To control for potential confounds, ANCOVA was applied using pre-test scores as a covariate. The results show that the pre - class preview completion rate of the experimental class increased by 26.8 percentage points. The frequency of high - level classroom interaction was 2.3 times that of the control class [operationalized via the ICAP framework; inter - rater reliability κ = 0.85]. The average final score of the experimental class was 11.7 points higher than that of the control class (p < 0.01).

The research verifies that the core mechanism of GAI empowering flipped classrooms lies in realizing full - link intelligence covering “resources - scenarios - feedback – evaluation”. Meanwhile, its application needs to guard against the risk of cognitive outsourcing and build a new human - machine collaborative teaching relationship.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Xiaoli Wu
AU  - Bendalyn Landicho
PY  - 2026
DA  - 2026/07/17
TI  - From “Experience Flood Irrigation” to “Data Drip Irrigation”: Construction and Practice of a Flipped Classroom Teaching Model Based on Generative AI
BT  - Proceedings of the 6th International Conference on Internet, Education and Information Technology (IEIT 2026)
PB  - Atlantis Press
SP  - 401
EP  - 413
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6239-733-0_42
DO  - 10.2991/978-94-6239-733-0_42
ID  - Wu2026
ER  -