Evaluating course teaching quality and building effective teaching teams pose significant challenges in university education assessment. Traditional evaluation methods often suffer from inaccuracies, low precision, and high spatiotemporal complexity. Moreover, assessments of teaching team effectiveness have not sufficiently enhanced course system development or improved teaching quality. This paper presents an enhanced fuzzy comprehensive evaluation method for course teaching quality by integrating numerical and level representation techniques and employing elastic proximity. This approach increases evaluation accuracy and precision while reducing algorithmic spatiotemporal complexity. Additionally, it incorporates teaching team evaluations into the assessment of course teaching quality, fostering collaborative development of course systems by teaching teams and collectively enhancing overall teaching quality.