A Pedagogical Agent with Embedded Data Mining Functions to Support Collaborative Writing

Internet growth has induced the development of a large number of collaborative tools for online writing and information sharing. Educators quickly realized the benefits of such tools for learners, allowing them to work online, to share their knowledge and help each other. Distance learning is a key concept in today’s educational research; collaborative learning environments are becoming widespread, being more dynamic and resourceful. However, distance learning also introduced a series of problems, such as high evasion rates resulting from lack of support and personalized feedback. It has also introduced difficulties for educators to follow and reviews students’ assignments. Based on this scenario, the work presented here proposes the development of a pedagogical agent supported by an intelligent tutoring system to provide students and teachers with assistance in order to minimize some of these problems. The use of a pedagogical agent allows students to have a constant feedback and guidance based on the identification of problems that may emerge from an online collaborative writing activity. The presence of this agent is intended to help students coordinate their efforts in writing a text collaboratively, and improve their work in terms of coherence. Furthermore, the pedagogical agent is also be able to assist teachers, reporting problems and simplifying their tasks related to the analysis of the work produced by each student. To support our pedagogical agent we propose the use of data mining tools to extract information related to the students’ writings, and a recommender system to suggest additional resources.