WenSheng Yan

With the widespread adoption of dance video teaching, traditional evaluation systems struggle to meet the demands of personalized teaching. To address this issue, a layered teaching plan is constructed using age segments and technical levels as dual axes. A dynamic feedback mechanism driven by multi-source data is established, allowing for precise matching of teaching levels through an intelligent diagnostic system. Machine learning algorithms analyze learning data to generate personalized improvement plans. This research achieves real-time interaction between teaching evaluation and the learning process, promoting a transformation from standardized to precise teaching in dance education. It offers an effective path for the adaptive development of dance education in the digital age.

Dance video teaching; Construction of evaluation systems; Personalized teaching; Layered adaptation; Multi-source data

[1] Yuan H,Zhang B.Research on the Construction and Application of a Blended Teaching Evaluation System for Public Finance under the“New Economics and Management”Strategy:Based on the TOE Analytical Framework[J].Higher Education Studies,2025,15(2):356-356. [2] Ma J.RETRACTED ARTICLE:Dynamic image data processing technology application in dance classroom assisted teaching under virtual environment[J].Soft Computing,2023,28(suppl 2):1-1. [3] Malco R,Angel C,Marcelo M,et al.Teaching Video NeuroImages:A treatable rare cause of chorea[J].Neurology, 2023,100(16_Supplement_1):S163-S163. [4] Cardoso T V,Silva D D F,Horta O R M,et al.Teaching Video NeuroImages:Hemichorea-hemiballismus secondary to nonketotic hyperglycemia[J].Neurology,2023,100(16_Supplement_1):S164-S164. [5] Malco R,Angel C,Marcelo M,et al.Teaching Video NeuroImages:A treatable rare cause of chorea.[J].Neurology, 2018,91(11):e1089.

点击下载PDF