| 基于马尔科夫链的大学生自主学习能力预测方法 |
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| 引用本文： | 刘德春,张秀国,姜 微. 基于马尔科夫链的大学生自主学习能力预测方法[J]. 计算机与现代化, 2018, 0(5): 106. DOI: 10.3969/j.issn.1006-2475.2018.05.021 |
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| 作者姓名： | 刘德春 张秀国 姜 微 |
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| 基金项目： | 河南省基础与前沿技术研究项目（142300410080 ） |
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| 摘 要： | 以反映大学生自主学习能力的现时状况数据指标为基础，利用马尔科夫链工作原理，分析研究自主学习能力的有效评估方法，构建大学生自主学习能力预测方法模型并提供算法流程，测试表明预测与实际结果高度吻合。所提供的研究模型精细、稳定、实用，能有效应用于提高自主学习能力和相应的预测软件开发当中。
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| 关 键 词： | 马尔科夫链 大学生自主学习 能力预测 状态转移概率矩阵 |
| 收稿时间： | 2018-06-13 |
Self-regulated Learning Ability Prediction for College Students Based on Markov Chain |
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| LIU De-chun,ZHANG Xiu-guo,JIANG Wei. Self-regulated Learning Ability Prediction for College Students Based on Markov Chain[J]. Computer and Modernization, 2018, 0(5): 106. DOI: 10.3969/j.issn.1006-2475.2018.05.021 |
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| Authors: | LIU De-chun ZHANG Xiu-guo JIANG Wei |
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| Abstract: | Based on the data of the college students’ current self-regulated learning condition and the principle of Markov chain, this paper firstly figures out an effective way to evaluate the self-regulated learning ability of college students, then constructs a model to predict it, and finally presents the relative algorithm. The test showes that the predicted results are highly in consistence with the actual results. The model constructed in this paper, which is fine, stable and practical, can be effectively applied to improve students self-regulated learning ability and develop new related predicting software. |
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| Keywords: | Markov chain self-regulated learning of college students ability prediction state transition probability matrix |
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