Evaluating an Intelligent Collaborative Learning Environment for UML

In this paper, we present an evaluation experiment of AUTO-COLLEAGUE conducted at the University of Piraeus. AUTO-COLLEAGUE is a collaborative learning environment for UML. Students are organized into groups supported with a chat system to collaborate with each other. It builds integrated individual student models aiming at suggesting optimum groups of learners. These optimum groups will allow the trainer of the system to organize them in the most effective way as far as their performance is concerned. In other words, the strengths and weaknesses of the students are blended for the best of the individuals and the groups. The student models concern the level of expertise and specific personality characteristics of the students. The results of the evaluation were quite optimistic, as they indicated a better individual performance of the students.

[1]  Aurora Vizcaíno,et al.  An Adaptive, Collaborative Environment to Develop Good Habits in Programming , 2000, Intelligent Tutoring Systems.

[2]  Antonio F. Gómez-Skarmeta,et al.  Colab: A Platform Design for Collaborative Learning in Virtual Laboratories , 2004 .

[3]  Weiqin Chen,et al.  CoLeMo: A collaborative learning environment for UML modelling , 2006, Interact. Learn. Environ..

[4]  Elaine Rich.  Users are individuals: individualizing user models , 1999, Int. J. Hum. Comput. Stud..

[5]  W. T. Norman,et al.  Toward an adequate taxonomy of personality attributes: replicated factors structure in peer nomination personality ratings. , 1963, Journal of abnormal and social psychology.

[6]  Antonija Mitrovic,et al.  COLLECT-UML: Supporting Individual and Collaborative Learning of UML Class Diagrams in a Constraint-Based Intelligent Tutoring System , 2005, KES.

[7]  Mark Guzdial,et al.  Situating CoWeb: a scholarship of application , 2006, Int. J. Comput. Support. Collab. Learn..

[8]  Departamento de Ingeniería Eléctrica.  Analysing student interaction processes in order to improve collaboration . The DEGREE approach , 2000 .

[9]  Maria Virvou,et al.  User Stereotypes for Student Modelling in Collaborative Learning: Adaptive Advice to Trainers , 2008, JCKBSE.

[10]  Anders I. Mørch,et al.  Simulating pedagogical agents in a virtual learning environment , 2002, CSCL.

[11]  Hong Jiang,et al.  Student Learning and Team Formation in a Structured CSCL Environment , 2006, ICCE.

[12]  Hanni Muukkonen,et al.  Collaborative technology for facilitating progressive inquiry: future learning environment tools , 1999, CSCL.

[13]  John A. Self,et al.  A Collaborative Case Study System for Distance Learning , 2004, Int. J. Artif. Intell. Educ..

[14]  Marlene Jones,et al.  The State of Student Modelling , 1994 .

[15]  Daniel D. Suthers,et al.  A Coached Collaborative Learning Environment for Entity-Relationship Modeling , 2000, Intelligent Tutoring Systems.

[16]  Beatriz Barros,et al.  Analysing student interaction processes in order to improve collaboration. The DEGREE approach , 2000 .

[17]  Amy Bruckman,et al.  AquaMOOSE 3D: math learning in a 3D multi-user virtual world , 2001, CHI Extended Abstracts.