TY - GEN
T1 - Text categorization for assessing multiple documents integration, or John Henry visits a data mine
AU - Hastings, Peter
AU - Hughes, Simon
AU - Magliano, Joe
AU - Goldman, Susan
AU - Lawless, Kim
PY - 2011
Y1 - 2011
N2 - A critical need for students in the digital age is to learn how to gather, analyze, evaluate, and synthesize complex and sometimes contradictory information across multiple sources and contexts. Yet reading is most often taught with single sources. In this paper, we explore techniques for analyzing student essays to give feedback to teachers on how well their students deal with multiple texts. We compare the performance of a simple regular expression matcher to Latent Semantic Analysis and to Support Vector Machines, a machine learning approach.
AB - A critical need for students in the digital age is to learn how to gather, analyze, evaluate, and synthesize complex and sometimes contradictory information across multiple sources and contexts. Yet reading is most often taught with single sources. In this paper, we explore techniques for analyzing student essays to give feedback to teachers on how well their students deal with multiple texts. We compare the performance of a simple regular expression matcher to Latent Semantic Analysis and to Support Vector Machines, a machine learning approach.
UR - http://www.scopus.com/inward/record.url?scp=79959319813&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79959319813&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21869-9_17
DO - 10.1007/978-3-642-21869-9_17
M3 - Conference contribution
AN - SCOPUS:79959319813
SN - 9783642218682
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 115
EP - 122
BT - Artificial Intelligence in Education - 15th International Conference, AIED 2011
T2 - 15th International Conference on Artificial Intelligence in Education, AIED 2011
Y2 - 28 June 2011 through 1 July 2011
ER -