实践教学是高校培养学生实践能力和创新能力的主要途径, 课程教学质量评价是提高教学质量和实现教学目标的重要保证, 目前实践类课程教学质量评价指标体系尚需完善, 评价方法也存在一定程度上的局限性. 本文在研究课程教学质量评价指标体系构建原则的基础上, 设计了实践类课程教学质量评价指标体系, 其一级指标包括教学环境、教学保障、教学过程和教学效果 4 个方面, 这些一级指标之下共设 18 个二级指标. 为提高评价方法的客观性和公正性,设计并实现了一种基于遗传优化神经网络的实践类课程教学质量评价方法, 建立了用于实践类课程教学质量评价的神经网络模型. 实例测试结果表明, 使用该方法能够实现对实践类课程教学质量的快速、准确评价, 为提高课程教学质量提供了有益的帮助.%Practice teaching is a main way to cultivate students' practical ability and creative ability for universities. Course teaching quality evaluation is an important guarantee to promote the teaching quality and achieve the teaching goal. At present, we still need to improve the evaluation index system of practice courses teaching quality, and the evaluation method also has certain limitations. Based on the construction principle of evaluation index system of course teaching quality, a comprehensive evaluation index system of practice courses teaching quality is established. It includes index of 4 one class: teaching environment, teaching guarantee, teaching process and teaching effect. One class index sets target of 18 two class. In order to improve the objectivity and impartiality of evaluation method, an evaluation method of practice courses teaching quality based on neural network optimized by genetic algorithm is designed and realized. The neural network model for practice courses teaching quality evaluation is formed. The illustrational results show that we can realize a fast and accurate evaluation of practice courses teaching quality by this method. It is helpful for us to promote the course teaching.
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