基于马尔可夫链的教学阶段性评价和远期预测模型

Application of Markov Chain in Teaching Evaluation and Long-term Prediction

教学条件基本稳定不变的教学过程具有马尔可夫随机过程的特征,可用马尔可夫链构建数学模型进行教学评价:利用转移矩阵构建转移矩阵的进步矩阵和效率度,建立教学阶段性评价的数学模型;利用转移矩阵的极限向量,建立教学远期效果预测的数学模型。用马尔可夫链建立的数学模型进行评价能较好地反映学习的转变情况,比单纯用分数评价更具合理性。

The teaching conditions remain basically stable in the teaching process with Markovian random process characteristics that can be used to build Markov chain mathematical mode/for teaching and learning and evaluation： using transfer matrix to build its progress matrix and efficiency degree, and then establish the mathematical model of teaching periodic evaluation; using the limit vector of transfer matrix, and then establish the mathematical model prediction of long -- term effect of teaching. Using Markov chain model to evaluate the study reflects the changes in the circumstances better than a simple evaluation with scores.