Intelligent assistance for teachers in collaborative e-learning environments

Computers and Education

Volumn 53, Issue 4, 2009, Pages 1147-1154

  Casamayor, Agustin ^a,b   Amandi, Analia ^a,b   Campo, Marcelo ^a,b  

^a UNIVERSIDAD NACIONAL DEL CENTRO DE LA PROVINCIA DE BUENOS AIRES   (Argentina)

^b Facultad de Ciencias Naturales e Instituto M Lillo   (Argentina)

Author keywords

Collaborative work; Distance learning; E learning; Intelligent assistance; Software agents

Indexed keywords

COLLABORATIVE LEARNING ENVIRONMENT; COLLABORATIVE WORK; COMMUNICATION PROBLEMS; CONFLICT DETECTION; DISTANCE LEARNING; DISTANCE LEARNING ENVIRONMENT; E-LEARNING ENVIRONMENT; GROUP WORK; HIGH PRECISION; INTELLIGENT ASSISTANCE; INTELLIGENT ASSISTANCES; RULE-BASED APPROACH;

COMMUNICATION; E-LEARNING; INTELLIGENT AGENTS; MULTIMEDIA SYSTEMS; STUDENTS; TEACHING;

SOFTWARE AGENTS;

EID: 69949110574     PISSN: 03601315     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compedu.2009.05.025     Document Type: Article

References (42)

1. Agrawal, R., Srikant, R. (1994). Fast algorithms for mining association rules in large databases. In Jorge B. Bocca, Matthias Jarke, & Carlo Zaniolo (Eds.), VLDB'94: Proceedings of 20th international conference on very large data bases (pp. 487-499). Santiago de Chile, Chile: Morgan Kaufmann.
2. Agrawal R., Imielinski T., and Swami A. Mining association rules between sets of items in large databases. SIGMOD'93: Proceedings of the 1993 ACM SIGMOD international conference on management of data (1993), ACM Press, New York, NY, USA 207-516 [Vol. 2]
3. Akhtar S., and Wyne M.F. Distance learning education using the web. MATH'06: Proceedings of the 10th WSEAS international conference on applied mathematics (2006), World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA 565-571
4. Alrifai M., Dolog P., and Nejdl W. Learner profile management for collaborating adaptive elearning applications. APS'06: Proceedings of the joint international workshop on adaptivity, personalization & the semantic web (2006), ACM, New York, NY, USA 31-34
5. Ayala, G., & Yano, Y. (1996). Learner models for supporting awareness and collaboration in a CSCL environment. In Intelligent tutoring systems (pp. 158-167).
6. Baeza-Yates R.A., and Ribeiro-Neto B. Modern information retrieval (1999), Addison-Wesley Longman Publishing Co., Inc, Boston, MA, USA
7. Barros M., and Verdejo M. Analysing student interaction processes in order to improve collaboration. The DEGREE approach. International Journal of Artificial Intelligence in Education 11 (2000) 221-241
8. Borges M.A.F., and Baranauskas M.C. CollabSS: A tool to help the facilitator in promoting collaboration among learners. Educational Technology & Society 6 1 (2003)
9. Castillo G., Gama J., and Breda A.M. Adaptive bayes for a student modeling prediction task based on learning styles. In: Brusilovsky P., Corbett A.T., and de Rosis F. (Eds). User modeling. Lecture notes in computer science Vol. 2702 (2003), Springer 328-332
10. Constantino Gonzalez M., Suthers D., and Escamila de los Santos J.G. Coaching web-based collaborative learning based on problem solution differences and participation. International Journal of Artificial Intelligence in Education 13 (2003)
11. Cristofor L., and Simovici D. Generating an informative cover for association rules. ICDM'02: Proceedings of the 2002 IEEE international conference on data mining (ICDM'02) (2002), IEEE Computer Society, Washington, DC, USA 597
12. Felder R.M., and Brent R. Understanding student differences. Journal of Engineering Education 94 1 (2005) 57-72
13. Felder R.M., and Silverman L.K. Learning and teaching styles in engineering education. Engineering Education 78 7 (1988) 674
14. Garcia P., Amandi A., Schiaffino S., and Campo M. Evaluating bayesian networks precision for detecting students learning styles. Computers and Education 49 3 (2007) 794-808
15. Gilbert, J. E., & Han, C. Y. (1999). Arthur: Adapting instruction to accommodate learning style. In World conference on the WWW and internet (WebNet 99) (pp. 433-438).
16. Godoy D., and Amandi A. User profiling in personal information agents: A survey. Knowledge Engineering Review 20 4 (2005) 329-361
17. Jennings N.R., Sycara K., and Wooldridge M. A roadmap of agent research and development. Journal of Autonomous Agents and Multi-Agent Systems 1 1 (1998) 7-38
18. Kay, J., Maisonneuve, N., Yacef, K., Zanane, O. (2006). Mining patterns of events in students' teamwork data. In In educational data mining workshop, held in conjunction with intelligent tutoring systems (ITS) (pp. 45-52).
19. Klemettinen M., Mannila H., Ronkainen P., Toivonen H., and Verkamo A.I. Finding interesting rules from large sets of discovered association rules. CIKM'94: Proceedings of the third international conference on information and knowledge management (1994), ACM, New York, NY, USA 401-407
20. Kligyte, G., Leinonen, T. (2001). Study of functionality and interfaces of existing CSCL/CSCW systems. ITCOLE project.
21. Kosba E., Dimitrova V., and Boyle R. Adaptive feedback generation to support teachers in web-based distance education. User Modeling and User-Adapted Interaction 17 4 (2007) 379-413
22. Lieberman H. Autonomous interface agents. CHI'97: Proceedings of the SIGCHI conference on human factors in computing systems (1997), ACM Press, New York, NY, USA 67-74
23. Littlejohn A., Falconer I., and Mcgill L. Characterising effective elearning resources. Computers & Education 50 3 (2008) 757-771
24. Liu B., Hsu W., Chen S., and Ma Y. Analyzing the subjective interestingness of association rules. IEEE Intelligent Systems 15 5 (2000) 47-55
25. Mandviwalla, M., Grillo, P. (1994). TeamBox: Researching the groupware interoperatibility problem. In CSCW'94: Demonstrations supplement to the CSCW'94 proceedings.
26. Offir B., Lev Y., and Bezalel R. Surface and deep learning processes in distance education: Synchronous versus asynchronous systems. Computer & Education 51 3 (2008) 1172-1183
27. Papanikolaou, K. A., Grigoriadou, M. (2003). An instructional framework supporting personalized learning on the web. In Advanced learning technologies, 2003. Proceedings. The 3rd IEEE international conference on (pp. 120-124).
28. Peña C.I., Marzo J.L., and de la Rosa J.L. Intelligent agents in a teaching and learning environment on the web. ICALT2002 (2002), IEEE, Kazan, Russia
29. Plantamura P., Roselli T., and Rossano V. Can a CSCL environment promote effective interaction?. ICALT'04: Proceedings of the IEEE international conference on advanced learning technologies (ICALT'04) (2004), IEEE Computer Society, Washington, DC, USA 675-677
30. Qu C., and Nejdl W. Constructing a web-based asynchronous and synchronous collaboration environment using WebDAV and Lotus Sametime. Proceedings of the 29th annual ACM SIGUCCS conference on user services (SIGUCCS'01) (2001), ACM Press, New York, NY, USA 142-149
31. Santos, O., Barrera, C., Gaudioso, E., Boticario, J. (2003). ALFANET: An adaptive e-learning platform. In Proceedings of the 2nd international meeting on multimedia and information communication technologies in education.
32. Santos, O., Rodriguez, A., Gaudioso, E., Boticario, J. G. (2003). Helping the tutor to manage a collaborative task in a web-based learning environment. In Proceedings of AIED'03 workshop on towards intelligent learning management systems.
33. Schiaffino S., and Amandi A. User-interface agent interaction: Personalization issues. International Journal of Human-Computer Studies 60 1 (2004) 129-148
34. Sheremetov L., and Guzmán Arenas A. EVA: An interactive web-based collaborative learning environment. Computers & Education 39 2 (2002) 161-182
35. Soller A., Goodman B.A., Linton F., and Gaimari R. Promoting effective peer interaction in an intelligent collaborative learning system. Proceedings of the 4th international conference on intelligent tutoring systems (ITS'98) (1998), Springer-Verlag, London, UK 186-195
36. Soller A., Lesgold A., Linton F., and Goodwin B. What makes peer interaction effective? Modeling effective communication in an intelligent CSCL. In: Brennan S.E., Giboin A., and Traum D. (Eds). Working papers of the AAAI fall symposium on psychological models of communication in collaborative systems (1999), American Association for Artificial Intelligence, Menlo Park, California 116-124
37. Srivastava J., Cooley R., Deshpande M., and Tan P. Web usage mining: Discovery and applications of usage patterns from web data. SIGKDD Explorations Newsletter 1 2 (2000) 12-23
38. Sunderam A.V. Automated personalization of internet news. AH'02: Proceedings of the second international conference on adaptive hypermedia and adaptive web-based systems (2002), Springer-Verlag, London, UK 348-357
39. Tadesco, P., Gomes, A. (2002). Amadeus: A framework to support multi-dimensional learner evaluation. In Proceedings of the 1st international conference on web-based learning, China.
40. Talavera, L., Gaudioso, E. (2004). Mining student data to characterize similar behavior groups in unstructured collaboration spaces. In Workshop on artificial intelligence in CSCL (pp. 17-23), Valencia, Spain.
41. Vizcafno A., Contreras J., Favela J., and Prieto M. An adaptive, collaborative environment to develop good habits in programming. In: Gauthier G., Frasson C., and VanLehn K. (Eds). Intelligent tutoring systems, 5th international conference, ITS 2000, June 19-23, 2000, proceedings. Lecture notes in computer science 1839 (2000), Springer, Montréal, Canada 262-271
42. Wessner M., and Pfister H.R. Group formation in computer-supported collaborative learning. Proceedings of the 2001 international ACM SIGGROUP conference on supporting group work (GROUP'01) (2001), ACM Press, New York, NY, USA 24-31