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Building an Open Learner Model from Constraints.

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Title: Building an Open Learner Model from Constraints.
Authors: PY, DOMINIQUE1 dominique.py@lium.univ-lemans.fr, DESPRÉS, CHRISTOPHE1, JACOBONI, PIERRE1
Source: Technology, Instruction, Cognition & Learning. 2015, Vol. 10 Issue 1, p45-58. 14p.
Subject Terms: *Open learning, *Classroom environment, Constraints (Linguistics), Social aspects, Java programming language, Imperative programming
Abstract: Although providing open learner models to teachers and learners has proven effective, building accurate learner models remains a very complex task, partly due to the large amount of data that must be analyzed. We propose a method for specifying an open learner model at the conceptual level. This model re-uses constraints or indicators already existing in the environment, in order to expedite student modeling. Constraints and indicators convey information about student knowledge that can be easily extracted. This method is independent from the domain and from the learning environment; it exploits the interaction tracks after a learning session. It has been implemented and a pilot study has been conducted with an indicator-based environment for Java programming. Initial results show that this modeling method can provide relevant information about learners' knowledge in an efficient manner. [ABSTRACT FROM AUTHOR]
Copyright of Technology, Instruction, Cognition & Learning is the property of Old City Publishing, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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DbLabel: Education Research Complete
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PubType: Academic Journal
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  Data: Building an Open Learner Model from Constraints.
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  Data: <searchLink fieldCode="JN" term="%22Technology%2C+Instruction%2C+Cognition+%26+Learning%22">Technology, Instruction, Cognition & Learning</searchLink>. 2015, Vol. 10 Issue 1, p45-58. 14p.
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  Data: *<searchLink fieldCode="DE" term="%22Open+learning%22">Open learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Classroom+environment%22">Classroom environment</searchLink><br /><searchLink fieldCode="DE" term="%22Constraints+%28Linguistics%29%22">Constraints (Linguistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Social+aspects%22">Social aspects</searchLink><br /><searchLink fieldCode="DE" term="%22Java+programming+language%22">Java programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Imperative+programming%22">Imperative programming</searchLink>
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  Data: Although providing open learner models to teachers and learners has proven effective, building accurate learner models remains a very complex task, partly due to the large amount of data that must be analyzed. We propose a method for specifying an open learner model at the conceptual level. This model re-uses constraints or indicators already existing in the environment, in order to expedite student modeling. Constraints and indicators convey information about student knowledge that can be easily extracted. This method is independent from the domain and from the learning environment; it exploits the interaction tracks after a learning session. It has been implemented and a pilot study has been conducted with an indicator-based environment for Java programming. Initial results show that this modeling method can provide relevant information about learners' knowledge in an efficient manner. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Technology, Instruction, Cognition & Learning is the property of Old City Publishing, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Classroom environment
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      – SubjectFull: Constraints (Linguistics)
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      – SubjectFull: Social aspects
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      – SubjectFull: Java programming language
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              Text: 2015
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