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  1. Integration of Gamification and Learning Analytics in Jupyter

    e-learning and education, Iss. 14

    Learning programming languages and programming concepts is associated with many problems for novices, which leads to high dropout and failure rates. Reasons often given are a lack of motivation or too little interactive materials. While gamification can be applied to increase motivation, the project Jupyter can be used as an interactive programming environment to enable more interactions with sample code. However, an approach of integration gamification in Jupyter is still missing. This report presents a concept of integrating arbitrary game elements and mechanics into Jupyter. Learning Analytics and Gamification Analytics will be applied afterwards to monitor and evaluate the measures and their impact.

  2. Learning Analytics: Challenges and Future Research Directions

    e-learning and education, Iss. 10

    In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.

  3. Integration of Gamification and Learning Analytics in Jupyter

    e-learning and education, Iss. 14

    Learning programming languages and programming concepts is associated with many problems for novices, which leads to high dropout and failure rates. Reasons often given are a lack of motivation or too little interactive materials. While gamification can be applied to increase motivation, the project Jupyter can be used as an interactive programming environment to enable more interactions with sample code. However, an approach of integration gamification in Jupyter is still missing. This report presents a concept of integrating arbitrary game elements and mechanics into Jupyter. Learning Analytics and Gamification Analytics will be applied afterwards to monitor and evaluate the measures and their impact.

  4. Learning Analytics: Challenges and Future Research Directions

    e-learning and education, Iss. 10

    In recent years, learning analytics (LA) has attracted a great deal of attention in technology-enhanced learning (TEL) research as practitioners, institutions, and researchers are increasingly seeing the potential that LA has to shape the future TEL landscape. Generally, LA deals with the development of methods that harness educational data sets to support the learning process. This paper provides a foundation for future research in LA. It provides a systematic overview on this emerging field and its key concepts through a reference model for LA based on four dimensions, namely data, environments, context (what?), stakeholders (who?), objectives (why?), and methods (how?). It further identifies various challenges and research opportunities in the area of LA in relation to each dimension.