Integration of Gamified Elements and Learning Style Data in Online Learning System

Sushil Shrestha, Manish Joshi, Aakash Bashyal, Arun Timilsina, Sushant Subedi
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Abstract

The increase in usage of Online Learning systems has provided a challenge to deliver e-contents based on user needs. This study uses learning style data to determine the learning profile and provide the content based on the user's needs, whereas gamified elements are used to increase user engagement. The combination of these two approaches would eventually increase the overall user motivation and interest in the platform. The model developed is used to predict the Learning Style (LS) preference by analyzing the activity data obtained from the student interaction in the course. Further, clustering is done to determine the LS preference of the user in the system. Content is designed based on user's learning styles and preferences and uploaded to the platform. Data were collected through surveys after the end of the course to measure students’ perception of the three variables: motivation, learning satisfaction, and learning outcomes. The findings from the study suggest that the students showed high motivation, positive learning outcomes, and satisfaction with the developed contents.
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在线学习系统中游戏化元素与学习风格数据的整合
在线学习系统使用的增加对根据用户需求提供电子内容提出了挑战。本研究使用学习风格数据来确定学习概况,并根据用户需求提供内容,而游戏化元素则用于提高用户粘性。这两种方法的结合将最终提高用户对平台的整体动机和兴趣。该模型通过分析学生在课程中的互动活动数据来预测学生的学习风格偏好。此外,进行聚类以确定系统中用户的LS偏好。根据用户的学习风格和喜好设计内容,上传至平台。课程结束后,通过问卷调查收集数据,测量学生对动机、学习满意度和学习成果三个变量的感知。研究结果显示,学生的学习动机高,学习成果积极,对开发的内容满意。
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