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Applying Machine Learning and AI on Self Automated Personalized Online Learning

机译:应用机器学习和AI对自动自动的个性化在线学习

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Machine Learning (ML) and Artificial Intelligence (AI) allowed researchers to view and analyze student's behaviors as never before. By monitoring them online, teachers can beforehand help students who need assistance. Many research papers revealed that there is a positive correlation between those students who exhibit good classroom behavior and academic achievement. RSU-AI-Monitoring System is an effective tool for behavioral improvement. RSU-AI-Monitoring System tracks many attributes on user activities' logs such as attendances, quiz marks, login and logout timestamps, IP addresses, names, etc. This research traces and directs students online to proper their behaviors. The experiment traced and tracked on two courses, which are THAI106 and ENG101. These subjects are the general education courses offering online. Student can access these subjects on an e-learning platform via mobile devices. Sample data were collected from 1,890 students in one semester. This paper discusses the data mining, ML and AI techniques to construct a new method enabling personalized learning. The experiment revealed a good progress on the overall student marks on their final examinations. 65 of 345 students were received the grade of B+ after participated in the tutoring program by AI Bot. 240 students who failed on the midterm examinations or received the low quiz scores, were able to pass their final examinations. The experiments revealed that 69.5% of the students had passed their final examinations and 18% obtained the B+ grades.
机译:机器学习(ML)和人工智能(AI)允许研究人员查看和分析之前从未以前则观看学生的行为。通过在线监测他们,教师可以预先帮助需要帮助的学生。许多研究论文透露,这些学生与良好课堂行为和学术成就之间存在正相关性。 RSU-AI监控系统是行为改进的有效工具。 RSU-AI监控系统跟踪用户活动的许多属性,例如出席,测验标记,登录和注销时间戳,IP地址,名称等。本研究迹线,并将学生在线指导到适当的行为。实验追踪并跟踪两种课程,这是泰国106和英格尔101。这些科目是在线提供的一般教育课程。学生可以通过移动设备访问电子学习平台上的这些主题。在一个学期的1,890名学生中收集了样本数据。本文讨论了数据挖掘,ML和AI技术,构建能够进行个性化学习的新方法。该实验揭示了整个学生标志的良好进展,并在其最终考试中进行了良好的进展。在AI Bot参加辅导计划之后,在345名学生的比例中获得了65个学生。 240名未能在中期考试或获得低测验分数的学生,能够通过他们的最终考试。实验表明,69.5%的学生通过了最终考试,18%获得了B +等级。

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