一种基于机器学习的在线学习行为投入评测模型

An Evaluation Model of Online Learning Behavior Investment Based on Machine Learning

疫情期间在线学习平台迅速爆增,学习者也越来越多,但是在线学习的监督性、学习者的投入度、学习的评估等因素,从而影响了学习者的学习效果。随着学习分析技术和教育数据挖掘的融合应用,文章通过分析学习者的在线学习行为投入数据,采用在线学习平台下对学习者行为投入及时评估的方法,构建一种基于机器学习的在线学习行为投入评测模型。该模型以在线学习者的投入度为评估目的,通过机器学习算法对学习者的投入度进行分析,帮助学习者及时自我调整,也帮助施教者更好地开展教学。

During the epidemic, online learning platforms have exploded rapidly, and there are more and more learners. However, factors such as the supervision of online learning, the degree of learner engagement, and the evaluation of learning affect the learning effect of learners. With the integration and application of learning analysis technology and educational data mining, this paper constructs an online learning behavior based on machine learning by analyzing the online learning behavior input data of learners, and adopting the method of timely assessment of learner behavior input under the online learning platform. The input evaluation model uses the online learner’s engagement as the evaluation purpose, and analyzes the learner’s engagement through the machine learning algorithm, which helps the learners to adjust themselves in time, and also helps the teachers to carry out better teaching.