Reveal the Collaboration in a Open Learning Environment

Authors:
Antonio R. Anaya;Jesús G. Boticario
Affiliations:
E.T.S.I.I. - UNED C/Juan del Rosal, Madrid, Spain 28040;E.T.S.I.I. - UNED C/Juan del Rosal, Madrid, Spain 28040
Venue:
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Year:
2009

Citing 11
Cited 1

Evaluating Collaborative Learning Processes

CRIWG '02 Proceedings of the 8th International Workshop on Groupware: Design, Implementation and Use
Promoting Effective Peer Interaction in an Intelligent Collaborative Learning System

ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Data Mining

Data Mining
Learning from Data Streams: Processing Techniques in Sensor Networks

Learning from Data Streams: Processing Techniques in Sensor Networks
From Modelling Domain Knowledge to Metacognitive Skills: Extending a Constraint-Based Tutoring System to Support Collaboration

UM '07 Proceedings of the 11th international conference on User Modeling
From Mirroring to Guiding: A Review of State of the Art Technology for Supporting Collaborative Learning

International Journal of Artificial Intelligence in Education
Student Models that Invite the Learner In: The SMILI:() Open Learner Modelling Framework

International Journal of Artificial Intelligence in Education
User models for adaptive hypermedia and adaptive educational systems

The adaptive web
Generic user modeling systems

The adaptive web
Towards an ontology for knowledge management in communities of practice

PAKM'06 Proceedings of the 6th international conference on Practical Aspects of Knowledge Management
Comparison of two learning models for collaborative e-learning

Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment

Application of machine learning techniques to analyse student interactions and improve the collaboration process

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

The management and characterization of collaboration to improve students' learning is still an open issue, which needs standardized models and inferring methods for effective collaboration indicators, especially when online courses are based on open approaches where students are not following CSCL scripts. We have supplied our students with a scrutable (manageable and understandable) web application that shows an ontology, which includes collaborative features. The ontology structures collaboration context information, which has been obtained form explicit (based on questionnaires) and implicit methods (supported by several machine learning techniques). From two consecutive years of experiences with hundreds of students we researched students' interactions to find implicit methods to identify and characterize students' collaboration. Based on the outcomes of our experiments we claim that showing useful and structured information to students and tutors about students' collaborative features can have a twofold beneficial impact on students learning and on the management of their collaboration.