AutoLearn’s authoring tool: a piece of cake for teachers

نویسندگان

  • Martí Quixal
  • Susanne Preuß
  • David García-Narbona
  • Beto Boullosa
چکیده

This paper 1 presents AutoLearn’s authoring tool: AutoTutor, a software solution that enables teachers (content creators) to develop language learning activities including automatic feedback generation without the need of being a programmer. The software has been designed and implemented on the basis of processing pipelines developed in previous work. A group of teachers has been trained to use the technology and the accompanying methodology, and has used materials created by them in their courses in real instruction settings, which served as an initial evaluation. The paper is structured in four sections: Section 1 introduces and contextualizes the research work. Section 2 describes the solution, its architecture and its components, and specifically the way the NLP resources are created automatically with teacher input. Section 3 describes and analyses a case study using the tool to create and test a language learning activity. Finally Section 4 concludes with remarks on the work done and connections to related work, and with future work.

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تاریخ انتشار 2010