S. Emmenegger, Knut Hinkelmann, Emanuele Laurenzi, Barbara Thönssen, Hans Friedrich Witschel, Congyu Zhang
{"title":"工作场所学习——以上下文敏感和个性化的方式提供专家建议和学习资源:一种本体支持的工作场所学习方法","authors":"S. Emmenegger, Knut Hinkelmann, Emanuele Laurenzi, Barbara Thönssen, Hans Friedrich Witschel, Congyu Zhang","doi":"10.26041/FHNW-1012","DOIUrl":null,"url":null,"abstract":"Support of workplace learning is increasingly important as change in every form determines today's working world in industry and public administrations alike. Adapt quickly to a new job, a new task or a new team is a major challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it should be strictly aligned to business goals. In our approach we support workplace learning by providing recommendations of experts and learning resources in a context-sensitive and personalized manner. We utilize users' workplace environment, we consider their learning preferences and zone of proximal development, and compare required and acquired competencies in order to issue the best suited recommendations. Our approach is part of the European funded project Learn PAd. Applied research method is Design Science Research. Evaluation is done in an iterative process. The recommender system introduced here is evaluated theoretically based on user requirements and practically in an early evaluation process conducted by the Learn PAd application partner.","PeriodicalId":360028,"journal":{"name":"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Workplace learning - providing recommendations of experts and learning resources in a context-sensitive and personalized manner: An approach for ontology supported workplace learning\",\"authors\":\"S. Emmenegger, Knut Hinkelmann, Emanuele Laurenzi, Barbara Thönssen, Hans Friedrich Witschel, Congyu Zhang\",\"doi\":\"10.26041/FHNW-1012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Support of workplace learning is increasingly important as change in every form determines today's working world in industry and public administrations alike. Adapt quickly to a new job, a new task or a new team is a major challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it should be strictly aligned to business goals. In our approach we support workplace learning by providing recommendations of experts and learning resources in a context-sensitive and personalized manner. We utilize users' workplace environment, we consider their learning preferences and zone of proximal development, and compare required and acquired competencies in order to issue the best suited recommendations. Our approach is part of the European funded project Learn PAd. Applied research method is Design Science Research. Evaluation is done in an iterative process. The recommender system introduced here is evaluated theoretically based on user requirements and practically in an early evaluation process conducted by the Learn PAd application partner.\",\"PeriodicalId\":360028,\"journal\":{\"name\":\"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26041/FHNW-1012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26041/FHNW-1012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Workplace learning - providing recommendations of experts and learning resources in a context-sensitive and personalized manner: An approach for ontology supported workplace learning
Support of workplace learning is increasingly important as change in every form determines today's working world in industry and public administrations alike. Adapt quickly to a new job, a new task or a new team is a major challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it should be strictly aligned to business goals. In our approach we support workplace learning by providing recommendations of experts and learning resources in a context-sensitive and personalized manner. We utilize users' workplace environment, we consider their learning preferences and zone of proximal development, and compare required and acquired competencies in order to issue the best suited recommendations. Our approach is part of the European funded project Learn PAd. Applied research method is Design Science Research. Evaluation is done in an iterative process. The recommender system introduced here is evaluated theoretically based on user requirements and practically in an early evaluation process conducted by the Learn PAd application partner.