Reinforcement Learning Technology Applied to the Innovative Model of Informatisation of Classroom Teaching in Educational Economics
Publié en ligne: 06 nov. 2023
Reçu: 18 déc. 2022
Accepté: 17 mai 2023
DOI: https://doi.org/10.2478/amns.2023.2.00988
Mots clés
© 2023 Liu Chen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
This paper constructs the architecture of the online teaching platform for education economics based on the MVC pattern coupled with three-tier architecture. The optimal value function is solved through the experience playback mechanism and the strategy function of reinforcement learning, and the value function is used to realize the update of the deep Q learning parameters, which is used to realize the guided teaching of students in the platform. A test analysis was conducted to verify the effectiveness of using the online teaching platform for education economics courses. The results show that the waiting time for teaching resource requests in the 0-3s range of this paper’s platform is 29.71% and 51.56% lower than that of the B/C and Web platforms, respectively. The mean value of students’ learning attitude toward the platform was 108.558, and the highest satisfaction score was 0.7088. The online teaching platform can effectively improve students' learning attitude and promote the innovation of information technology in education economics classroom teaching.