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Teaching in classic courses offers too little interaction between docents and students and should be improved. Addressed approaches include a range from Simple Voting Systems to Clickers and Audience Response Systems, and interaction and Student motivation may be improved in them. However, different university course settings are affected in different ways by these systems. Therefore, this paper presents a comparison of a selected range of these systems (implemented as tool kits) within two course settings, namely readings and tutorials. These tools are Audience Response Systems, Question and Answer Systems (Q&A Systems), Discussion Systems (Panels), as well as Virtual Whiteboard Feedback Systems. A synopsis of feasibility for different settings is provided and concluded with important results on the distinguishability of Q&A Systems and Panels.

Crowdsourcing has gained increasing interest during the last years as means for solving complex tasks with the help of a flexible group of contributors. The crowd can contribute with collecting data in the field, completing map information or votes for ideas or products. Even though the participation of large numbers of users with heterogeneous devices in crowdsourcing is a highly recurrent task, generic infrastructures for crowdsourcing can be hardly found. Especially the management of users, mobile devices and contributed data has to be repetitively implemented in new projects. To ease the development of crowdsourcing applications, in this paper we propose a generic platform for crowdsourcing supporting diverse crowdsourcing scenarios, the ability to handle large numbers of users and the involvement of heterogeneous mobile devices. The evaluation is based on scalability and performance experiments in order to demonstrate the feasibility of our approach.

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