{"title":"Integration of Gamified Elements and Learning Style Data in Online Learning System","authors":"Sushil Shrestha, Manish Joshi, Aakash Bashyal, Arun Timilsina, Sushant Subedi","doi":"10.1177/00472395231202004","DOIUrl":null,"url":null,"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.","PeriodicalId":300288,"journal":{"name":"Journal of Educational Technology Systems","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Educational Technology Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/00472395231202004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.