eprintid: 16893
rev_number: 14
userid: 1345
dir: disk0/00/01/68/93
datestamp: 2012-12-17 18:54:07
lastmod: 2017-11-01 13:56:08
status_changed: 2012-12-17 18:54:07
type: article
metadata_visibility: show
item_issues_count: 0
eprint_status: archive
creators_name: Pinkwart, Niels
creators_name: Aleven, Vincent
creators_name: Ashley, Kevin D
creators_name: Lynch, Collin
creators_email: 
creators_email: 
creators_email: ashley@pitt.edu
creators_email: 
creators_id: 
creators_id: 
creators_id: ASHLEY
creators_id: 
title: Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO
ispublished: pub
divisions: sch_law_law
divisions: sch_law_law_facultypub
full_text_status: public
keywords: e-learning, tutoring, systems, learning, management, system
abstract: The Intelligent Tutoring System LARGO is designed to help law students learn argumentation skills. The approach implemented in LARGO uses transcripts of oral arguments as learning resources: Students annotate them and create graphical representations of the argument flow. The system encourages students to reflect upon arguments proposed by the attorneys and helps students detect possible weaknesses in their analysis of the dispute. Technically, graph grammar and collaborative filtering algorithms are employed to detect these weaknesses. This article describes how “usage contexts” are determined and used to create adaptive feedback in LARGO. On the basis of a controlled study with the system that took place with law students at the University of Pittsburgh, we discuss to what extent the automatically calculated usage contexts can predict student’s learning gains.
date: 2009
date_type: published
publication: E-learning and Education
volume: 1
number: 5
publisher: FernUniversität Hagen, CampusSource
institution: University of Pittsburgh
refereed: TRUE
issn: 1860-7470
official_url: http://eleed.campussource.de/archive/5/1608/
etd_access_restriction: immediate
etd_patent_pending: FALSE
article_type: researcharticle
citation:   Pinkwart, Niels and Aleven, Vincent and Ashley, Kevin D and Lynch, Collin  (2009) Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO.  E-learning and Education, 1 (5).   ISSN 1860-7470     
document_url: http://d-scholarship-dev.library.pitt.edu/16893/1/view.pdf
document_url: http://d-scholarship-dev.library.pitt.edu/16893/8/licence.txt