{"title":"Personalized e-Coaching as a Support in the Social Inclusion Process","authors":"L. Zemko, K. Jelemenská, P. Cicák, T. Mifkovic","doi":"10.1109/ICETA57911.2022.9974954","DOIUrl":null,"url":null,"abstract":"Risk groups of people are exposed to a higher risk of social exclusion. Reasons for this situation may include poor information about gathering help, alternatively problematic availability of information or incorrect mental setting. This work focuses on personalized e-coaching, which aims for positive change of personal habits and thus achieving a healthy, long-term sustainable lifestyle. In case of e-coaching, the whole process is controlled by a software. To achieve the goals, persuasive techniques tend to be used. As a part of the e-coaching process, it is appropriate to provide the respondent with guidelines in the form of personalized recommendations, which may include activities or specific resources depending on preferences, interests and responsibilities of the respondent. We proposed a solution with a client-server architecture, based on the PSD model. The primary task of the server application is obtaining, storing, and providing context-specific personalized data and recommendations. Data is obtained through client applications and external services, combining implicit and explicit methods. Recommendations are based on available data about the respondent, as well as on available contextual data. The application will gradually dynamically learn the preferences and interests of the respondent based on the interaction with individual resources and services of the application.","PeriodicalId":151344,"journal":{"name":"2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETA57911.2022.9974954","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
Risk groups of people are exposed to a higher risk of social exclusion. Reasons for this situation may include poor information about gathering help, alternatively problematic availability of information or incorrect mental setting. This work focuses on personalized e-coaching, which aims for positive change of personal habits and thus achieving a healthy, long-term sustainable lifestyle. In case of e-coaching, the whole process is controlled by a software. To achieve the goals, persuasive techniques tend to be used. As a part of the e-coaching process, it is appropriate to provide the respondent with guidelines in the form of personalized recommendations, which may include activities or specific resources depending on preferences, interests and responsibilities of the respondent. We proposed a solution with a client-server architecture, based on the PSD model. The primary task of the server application is obtaining, storing, and providing context-specific personalized data and recommendations. Data is obtained through client applications and external services, combining implicit and explicit methods. Recommendations are based on available data about the respondent, as well as on available contextual data. The application will gradually dynamically learn the preferences and interests of the respondent based on the interaction with individual resources and services of the application.