TY - GEN
T1 - Deriving and measuring group knowledge structure via computer-based analysis of essay questions
T2 - IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2008
AU - Clariana, Roy B.
AU - Wallace, Patricia E.
AU - Godshalk, Veronica M.
PY - 2008
Y1 - 2008
N2 - Essays are an important measure of complex learning but pronouns in text can confound the author's intended meaning. Our interest here is in automatic essay scoring. How do pronouns affect computer-based text analysis? Participants in an undergraduate business course (N = 49) completed an essay as part of the course final examination and investigators manually edited every occurrence of pronouns in these essays to their antecedents. The original unedited and the edited essays were processed by ALA-Reader software using linear aggregate and sentence aggregate methods. These data were then analyzed using a Pathfinder network (PFNET) approach. The sentence aggregate approach obtained substantially different PFNET representations of the unedited and edited essays; the presence of pronouns negatively impacted the quality of sentence aggregate data. However, there was little difference between the PFNETs obtained for the unedited and edited essays for the linear aggregate method. The linear aggregate method appears to be relatively robust to pronoun confounding at least for the narrow purposes of establishing group knowledge structure and for expert referent pattern matching for determining individual essay scores.
AB - Essays are an important measure of complex learning but pronouns in text can confound the author's intended meaning. Our interest here is in automatic essay scoring. How do pronouns affect computer-based text analysis? Participants in an undergraduate business course (N = 49) completed an essay as part of the course final examination and investigators manually edited every occurrence of pronouns in these essays to their antecedents. The original unedited and the edited essays were processed by ALA-Reader software using linear aggregate and sentence aggregate methods. These data were then analyzed using a Pathfinder network (PFNET) approach. The sentence aggregate approach obtained substantially different PFNET representations of the unedited and edited essays; the presence of pronouns negatively impacted the quality of sentence aggregate data. However, there was little difference between the PFNETs obtained for the unedited and edited essays for the linear aggregate method. The linear aggregate method appears to be relatively robust to pronoun confounding at least for the narrow purposes of establishing group knowledge structure and for expert referent pattern matching for determining individual essay scores.
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M3 - Conference contribution
AN - SCOPUS:84882931874
SN - 9781627483339
T3 - IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2008
SP - 88
EP - 95
BT - IADIS International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2008
Y2 - 13 December 2008 through 15 December 2008
ER -