Applicazione del machine learning ai learning analytics della piattaforma Moodle per creare gruppi eterogenei nei corsi on-line

Giacomo Nalli, L. Mostarda, A. Perali, S. Pilati, D. Amendola
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Abstract

In university courses to promote collaborative activities among students, on-line learningenvironments such as e-learning platforms are used. Effective collaborative activitiesinvolve the creation of heterogeneous groups of 4 or 5 students. In the university contextthe formation of groups is difficult due to the high number of students. Groups are oftenunbalanced and not very functional if chosen randomly. Some e-learning platforms, suchas Moodle, lack an intelligent mechanism that allows the automatic creation of heterogeneousgroups of students. We applied clustering algorithms on Moodle learning analytics(LA) that allowed to build groupings that identify the different characteristics ofstudents based on their behaviors kept on the platform. Therefore we have developedan intelligent numerical tool which, using clusters obtained from Machine Learning onthe LA, generates heterogeneous groups. These groups are made available on the platformfor the teacher. The project will conclude with the development of a Moodle pluginto automate the exchange of data and information between the Machine Learning algorithmand the Moodle platform.
Moodle平台将机器学习应用于学习分析,在在线课程中创建异构组
在大学课程中,为了促进学生之间的协作活动,使用了在线学习环境,如电子学习平台。有效的合作活动包括创建由4或5名学生组成的异质小组。在大学环境下,由于学生人数众多,很难形成团体。如果随机选择的话,团队通常是不平衡的,并且没有很好的功能。一些电子学习平台,如Moodle,缺乏智能机制来自动创建不同的学生群体。我们在Moodle学习分析(LA)上应用了聚类算法,该算法允许建立分组,根据学生在平台上的行为来识别他们的不同特征。因此,我们开发了一种智能数值工具,该工具使用从LA上的机器学习中获得的聚类来生成异质组。这些组在平台上可供教师使用。该项目最后将开发一个Moodle插件,用于在机器学习算法和Moodle平台之间自动交换数据和信息。
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