Assessment of e-business instructional quality based on BP neural network in new media environment
Pan Ying
Source record
Source: Crossref
Published: Jan 1, 2024
DOI: 10.2478/amns-2024-0742
Open original source ↗Source abstract
Abstract Instructional quality assessment is a systematic project involving a wide range. Restricted and influenced by many factors and conditions. How to accurately and effectively assess the instructional quality of teachers. The determination of the assessment system and method is very important. Some people think that the quality of teaching is “the total of the characteristics of tertiary education that can meet the obvious or implicit needs of individuals, groups, and society. These characteristics are shown through the goals, standards, and achievement levels required by the educated, educators, and social development. In this article, a back propagation neural network (BPNN) is used in classroom instructional quality assessment, and a classroom instructional quality assessment model is constructed. The experimental results of this article show that the accuracy rate of the algorithm based on BPNN reaches 89%, and the learning rate reaches 93%.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.