In the current educational environment, higher vocational electromagnetic teaching plays a vital role, which aims to provide students with the necessary theoretical basis and practical skills to deal with the electromagnetic problems in the future work. However, with the rapid development of science and technology, the teaching of electromagnetism faces multiple challenges. The traditional teaching mode often focuses on the transmission of theoretical knowledge, but ignores the cultivation of practical operation and innovation ability. In addition, due to the abstraction and complexity of electromagnetism content, many students encounter difficulties in understanding and mastering knowledge, which makes the teaching effect difficult to reach the expectation. Facing these challenges, the introduction of intelligent algorithms offers new possibilities for teaching evaluation. Intelligent algorithms, such as machine learning, deep learning and data mining, can process a large amount of teaching data, mine hidden patterns, and provide objective and accurate evaluation of teaching effects. MATLAB simulation shows that under the condition of certain evaluation criteria, the effect of intelligent algorithm on higher vocational electromagnetically teaching is achieved the design accuracy of the assessment method and the design time of the evaluation method is better than the practical teaching mode.