DocumentCode :
2964463
Title :
Supporting Assessment of Open Answers in a Didactic Setting
Author :
Sterbini, Andrea ; Temperini, Marco
Author_Institution :
Comput. Sci. Dept., Sapienza Univ. of Rome, Rome, Italy
fYear :
2012
fDate :
4-6 July 2012
Firstpage :
678
Lastpage :
679
Abstract :
The Open Answers module is designed to be integrated into the social collaborative reputation-based elearning system SocialX, to manage answers to open questions. In particular, its aim is to support personal evaluation of skills and knowledge of students, involved in peer-assessment-based learning activities, while mitigating the workload imposed upon the teacher, for analysis and correction of the answers. In brief, 1) students do answer open questions, to be evaluated by peers and teacher; 2) students peer-evaluate each other´s answers; 3) the teacher grades only a subset of the whole answers corpus; 4) the system infers the assessment for the remaining answers, by exploiting the relations established through the web of the students´ peer-assessments of those answers, and the personal evaluation maintained for each student. The peer-assessment data are analyzed through a constraint-logic-based model of student´s possible behaviors, obtaining a (possibly big!) set of hypotheses on the answers´ correctness. The teacher is proposed with a minimum set of answers to grade: by such grading (s)he helps narrowing the set of hypotheses. Testing of the constraint-logic-based analysis engine is ongoing by means of simulation devices that generate suitable sets of students´ behaviors.
Keywords :
Internet; computer aided instruction; data analysis; groupware; OpenAnswers module; SocialX; Web-based collaborative e-learning; answer management; constraint-logic-based analysis engine; peer-assessment data analysis; peer-assessment-based learning activities; personal knowledge evaluation; personal skill evaluation; social collaborative reputation-based elearning system; Abstracts; Analytical models; Collaboration; Computers; Educational institutions; Electronic learning; Engines; assessment; peer assessment; social collaborative e-learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies (ICALT), 2012 IEEE 12th International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4673-1642-2
Type :
conf
DOI :
10.1109/ICALT.2012.149
Filename :
6268214
Link To Document :
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