115,120 research outputs found

    App creation in schools for different curricula subjects - lesson learned

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    The next generation of jobs will be characterized by an increased demand for people with computational and problem solving skills. In Austria, computer science topics are underrepresented in school curricula hence teaching time for these topics is limited. From primary through secondary school, only a few opportunities exist for young students to explore programming. Furthermore, today's teachers are rarely trained in computer science, which impairs their potential to motivate students in these courses. Within the "No One Left Behind" (NOLB) project, teachers were supported to guide and assist their students in their learning processes by constructing ideas through game making. Thus, students created games that referred to different subject areas by using the programming tool Pocket Code, an app developed at Graz University of Technology (TU-Graz). This tool helps students to take control of their own education, becoming more engaged, interested, and empowered as a result. To ensure an optimal integration of the app in diverse subjects the different backgrounds (technical and non-technical) of teachers must be considered as well. First, teachers were supported to use Pocket Code in the different subjects in school within the feasibility study of the project. Observed challenges and difficulties using the app have been gathered. Second, we conducted interviews with teachers and students to underpin our onsite observations. As a result, it was possible to validate Pocket Codes' potential to be used in a diverse range of subjects. Third, we focused especially on those teachers who were not technically trained to provide them with a framework for Pocket Code units, e.g., with the help of structured lesson plans and predefined templates.Comment: 10 pages, 5 tables EduLearn 201

    An integrated approach to courseware

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    Software engineering is becoming increasingly important as an engineering discipline, and its teaching in universities and other higher education institutions should be of high quality. In this paper we describe a tool (BOSS ā€” the Boss Online Submission System) which aids the education of software engineers. BOSS allows students to submit programming assignments online, and to run black-box tests on their programs prior to submission. Instructors can use BOSS to assist in marking such assignments by allowing submitted programs to be tested against multiple data sets. We describe how BOSS helps in the teaching of specific conceptual aspects of software engineering, and how it addresses some of the practical issues involved in teaching large student numbers in a pedagogically neutral manner

    Towards the Automatic Classification of Documents in User-generated Classifications

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    There is a huge amount of information scattered on the World Wide Web. As the information flow occurs at a high speed in the WWW, there is a need to organize it in the right manner so that a user can access it very easily. Previously the organization of information was generally done manually, by matching the document contents to some pre-defined categories. There are two approaches for this text-based categorization: manual and automatic. In the manual approach, a human expert performs the classification task, and in the second case supervised classifiers are used to automatically classify resources. In a supervised classification, manual interaction is required to create some training data before the automatic classification task takes place. In our new approach, we intend to propose automatic classification of documents through semantic keywords and building the formulas generation by these keywords. Thus we can reduce this human participation by combining the knowledge of a given classification and the knowledge extracted from the data. The main focus of this PhD thesis, supervised by Prof. Fausto Giunchiglia, is the automatic classification of documents into user-generated classifications. The key benefits foreseen from this automatic document classification is not only related to search engines, but also to many other fields like, document organization, text filtering, semantic index managing
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