TY - GEN
T1 - Automarking
T2 - 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010
AU - Cutrone, Laurie
AU - Chang, Maiga
PY - 2010
Y1 - 2010
N2 - A number of Learning Management Systems (LMSs) exist on the market today. A subset of a LMS is the component in which student assessment is managed. In some forms of assessment, such as open questions, the LMS is incapable of evaluating the students' responses and therefore human intervention is necessary. In order to assess at higher levels of Bloom's (1956) taxonomy, it is necessary to include open-style questions in which the student is given the task as well as the freedom to arrive at a response without the comfort of recall words and/or phrases. Automating the assessment process of open questions is an area of research that has been ongoing since the 1960s. Earlier work focused on statistical or probabilistic approaches based primarily on conceptual understanding. Recent gains in Natural Language Processing have resulted in a shift in the way in which free text can be evaluated. This has allowed for a more linguistic approach which focuses heavily on factual understanding. This study will leverage the research conducted in recent studies in the area of Natural Language Processing, Information Extraction and Information Retrieval in order to provide a fair, timely and accurate assessment of student responses to open questions based on the semantic meaning of those responses.
AB - A number of Learning Management Systems (LMSs) exist on the market today. A subset of a LMS is the component in which student assessment is managed. In some forms of assessment, such as open questions, the LMS is incapable of evaluating the students' responses and therefore human intervention is necessary. In order to assess at higher levels of Bloom's (1956) taxonomy, it is necessary to include open-style questions in which the student is given the task as well as the freedom to arrive at a response without the comfort of recall words and/or phrases. Automating the assessment process of open questions is an area of research that has been ongoing since the 1960s. Earlier work focused on statistical or probabilistic approaches based primarily on conceptual understanding. Recent gains in Natural Language Processing have resulted in a shift in the way in which free text can be evaluated. This has allowed for a more linguistic approach which focuses heavily on factual understanding. This study will leverage the research conducted in recent studies in the area of Natural Language Processing, Information Extraction and Information Retrieval in order to provide a fair, timely and accurate assessment of student responses to open questions based on the semantic meaning of those responses.
KW - Computerized grading
KW - Information retrieval
KW - Natural language processing
KW - Open question
KW - Part of speech tagging
KW - Semantic meaning
KW - WordNet
UR - http://www.scopus.com/inward/record.url?scp=78049306607&partnerID=8YFLogxK
U2 - 10.1109/ICALT.2010.47
DO - 10.1109/ICALT.2010.47
M3 - Published Conference contribution
AN - SCOPUS:78049306607
SN - 9780769540559
T3 - Proceedings - 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010
SP - 143
EP - 147
BT - Proceedings - 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010
Y2 - 5 July 2010 through 7 July 2010
ER -