TY - GEN
T1 - Fading and deepening
T2 - 5th International Conference on Intelligent Tutoring Systems, ITS 2000
AU - VanLehn, Kurt
AU - Freedman, Reva
AU - Jordan, Pamela
AU - Murray, Charles
AU - Osan, Remus
AU - Ringenberg, Michael
AU - Rosé, Carolyn
AU - Schulze, Kay
AU - Shelby, Robert
AU - Treacy, Donald
AU - Weinstein, Anders
AU - Wintersgill, Mary
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2000.
PY - 2000
Y1 - 2000
N2 - Model tracing tutors have been quite successful in teaching cognitive skills; however, they still are not as competent as expert human tutors. We propose two ways to improve model tracing tutors and in particular the Andes physics tutor. First, tutors should fade their scaffolding. Although most model tracing tutors have scaffolding that needs to be gradually removed (faded), Andes’ scaffolding is already “faded,” and that causes student modeling difficulties that adversely impact its tutoring. A proposed solution to this problem is presented. Second, tutors should integrate the knowledge they currently teach with other important knowledge in the task domain in order to promote deeper learning. Several types of deep learning are discussed, and it is argued that natural language processing is necessary for encouraging such learning. A new project, Atlas, is developing natural language based enhancements to model tracing tutors that are intended to encourage deeper learning.
AB - Model tracing tutors have been quite successful in teaching cognitive skills; however, they still are not as competent as expert human tutors. We propose two ways to improve model tracing tutors and in particular the Andes physics tutor. First, tutors should fade their scaffolding. Although most model tracing tutors have scaffolding that needs to be gradually removed (faded), Andes’ scaffolding is already “faded,” and that causes student modeling difficulties that adversely impact its tutoring. A proposed solution to this problem is presented. Second, tutors should integrate the knowledge they currently teach with other important knowledge in the task domain in order to promote deeper learning. Several types of deep learning are discussed, and it is argued that natural language processing is necessary for encouraging such learning. A new project, Atlas, is developing natural language based enhancements to model tracing tutors that are intended to encourage deeper learning.
UR - http://www.scopus.com/inward/record.url?scp=84944319473&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84944319473&partnerID=8YFLogxK
U2 - 10.1007/3-540-45108-0_51
DO - 10.1007/3-540-45108-0_51
M3 - Conference contribution
AN - SCOPUS:84944319473
SN - 3540676554
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 474
EP - 483
BT - Intelligent Tutoring Systems - 5th International Conference, ITS 2000, Proceedings
A2 - Gauthier, Gilles
A2 - Frasson, Claude
A2 - VanLehn, Kurt
PB - Springer Verlag
Y2 - 19 June 2000 through 23 June 2000
ER -