教学质量促进学习成绩评估建模仿真

发布时间：2018-11-10 16:58

【摘要】：对教学质量促进学习成绩评估建模,可提高教学改革的成功率。进行教学质量促进学习成绩评估建模时,需要计算影响学生自主学习成绩的各因素之间关联度和相关性系数,对学习成绩进行划分,建立学生自主学习成绩转移概率矩阵,但是传统方法通过有限的经验数据学习,建立学生自主学习成绩与其影响因素之间的非线性关系,对教学质量促进学习成绩进行评估,但是不能对影响学生自主学习成绩的各因素之间关联度和相关性系数进行准确计算,无法建立学生自主学习成绩转移概率矩阵,降低了建模的精度。提出一种灰色理论的教学质量促进学习成绩评估建模方法。该模型融合灰关联熵分析理论分析影响学生自主学习成绩的各因素之间关联度,计算影响因素的相关性系数,并依据计算结果进行排序,选取系数较大的关联因素,利用马尔科可夫模型划分各个阶段的学生自主学习状态,给出学生自主学习成绩转移概率矩阵,并组建教学质量促进学习成绩评估模型。仿真结果表明,所提模型能够有效教学质量促进学习成绩评估的精度,且具有较强的泛化能力。
[Abstract]:The success rate of teaching reform can be improved by modeling the teaching quality to promote the evaluation of learning achievement. In the modeling of teaching quality to promote the evaluation of learning achievement, it is necessary to calculate the correlation degree and correlation coefficient among the factors that affect the students' autonomous learning achievement, to divide the learning achievement, and to establish the probability matrix of students' autonomous learning achievement transfer. However, the traditional method establishes the nonlinear relationship between students' autonomous learning achievement and its influencing factors through limited empirical data learning, and evaluates the teaching quality to promote learning achievement. However, it can not accurately calculate the correlation degree and correlation coefficient among the factors that affect students' autonomous learning achievement, and can not establish the transition probability matrix of students' autonomous learning achievement, which reduces the precision of modeling. In this paper, a grey theory modeling method of teaching quality for learning achievement evaluation is proposed. The model combines grey correlation entropy analysis theory to analyze the correlation degree among the factors that affect students' autonomous learning achievement, calculates the correlation coefficient of the influencing factors, and sorts according to the results of the calculation, and selects the correlation factors with large coefficients. In this paper, the Markov model is used to divide the students' autonomous learning states in different stages, and the probability matrix of students' autonomous learning achievement transfer is given, and a model of teaching quality to promote the evaluation of learning achievement is set up. The simulation results show that the proposed model can effectively promote the accuracy of learning achievement evaluation and has a strong generalization ability.
【作者单位】：吉林农业大学信息技术学院;长春大学;
【基金】：吉林省教育科学"十二五"规划重点自助课题(ZC13021) 吉林省教育厅高等教育教学改革研究重点课题(SJZD1501,SJZD1502)
【分类号】：G424.7;N941.5

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