
Pedagogically Founded Courseware Generation for Web-Based Learning
An HTN-Planning-Based Approach Implemented in Paigos
Automatic course generation is a very important area of research with numerous practical applications in e-learning. It has been studied since the 1980s within the fields of intelligent tutoring, AI and education, adaptive hypermedia and web-based educational systems. Many approaches have been proposed, but hardly any have resulted in generic and practically applied systems. A number of problems have remained unresolved. These problems are addressed by this work. This book focuses on course generation based on Hierarchical Task Network planning (HTN planning). This course generation framework enables the formalization and application of complex and realistic pedagogical knowledge. The volume describes basic techniques for course generation, which are used to formalize seven different types of courses (for instance, introducing the learner to previously unknown concepts and supporting the learner during rehearsal) and several elementary learning goals (e.g., selecting an appropriate example or exercise). This framework has been implemented and evaluated with good results in several domains, with users from different countries and universities, in the context of an EU project. Course generation based on HTN planning is implemented in PAIGOS and has been evaluated by technical, formative and summative evaluations.
- ISBN 13 : 3540882138
- ISBN 10 : 9783540882138
- Judul : Pedagogically Founded Courseware Generation for Web-Based Learning
- Sub Judul : An HTN-Planning-Based Approach Implemented in Paigos
- Pengarang : Carsten Ullrich,
- Kategori : Computers
- Penerbit : Springer Science & Business Media
- Bahasa : en
- Tahun : 2008
- Halaman : 257
- Halaman : 257
- Google Book : http://books.google.co.id/books?id=G8XAY45YkkwC&dq=intitle:based+learning&hl=&source=gbs_api
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Ketersediaan :
In this chapter, I will identify and describe general principles that apply to course
generation as formalized in Paigos, independent of both the underlying learning
theory and the learning goals the course is generated for. The chapter starts with
metadata. In Section 4.1, I show that existing learning object metadata standards
fail to describe educational resources sufficiently precise for their automatic
integration into learning processes by intelligent components. I then describe an
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