人工智能赋能的应用型本科高校科教协同育人评价模型

Evaluation model of collaborative education of science and education in application-oriented undergraduate universities empowered by AI

针对应用型本科高校科教协同育人评价过程中存在非线性和精度低的问题,文章提出了人工智能赋能的应用型本科高校科教协同育人评价模型。首先,文章从校企合作办学条件、专业理论实践条件、科教融合应用条件和实习就业发展条件4个角度,构建了协同育人评价体系,利用粗糙集方法对评价指标进行约简处理;其次,利用改进灰狼算法对RBF神经网络结构进行优化设计,构建了高校科教协同育人评价模型;最后,以国内10所应用型高校科教协同育人数据为案例,利用优化后的RBF神经网络结构进行数据训练,对4所高校科教协同育人效果进行仿真评价。结果表明,该模型具有较高的精准性。

According to the problems of nonlinearity and low precision in the evaluation process of science and education collaborative education in application-oriented undergraduate universities,an evaluation model of science and education collaborative education in application-oriented undergraduate universities empowered by artificial intelligence is presented.Firstly,from the four aspects of school-enterprise cooperation,professional theory and practice,science and education integration and internship employment development,the evaluation system of collaborative education is constructed,and the evaluation indicators are reduced using rough set method.Secondly,the structure of RBF neural network is optimized through improved Grey Wolf algorithm,and the evaluation model of university science and education collaborative education is constructed.Finally,taking the data of 10 application-oriented universities in China as an example,the optimized RBF neural network is used for data training,and the simulation evaluation of the effect of science and education collaborative education in four universities is operated.The results show that the model has high accuracy.