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Analyzing Discourse and Text Complexity for Learning and Collaborating: A Cognitive Approach Based on Natural Language Processing
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Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!
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| With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL) and e-learning technologies, the need of
automatic assessment
and
of
teacher/tutor support
for the two tightly intertwined activities of
comprehension
of reading materials and of
collaboration
among peers has grown significantly. In this context, a polyphonic model of discourse derived from Bakhtin's work as a paradigm is used for analyzing both general texts and CSCL conversations in a unique framework focused on different facets of textual cohesion.
As specificity of our analysis, the
individual learning
perspective is focused on the identification of reading strategies and on providing a multi-dimensional textual complexity model, whereas the
collaborative learning
dimension is centered on the evaluation of participants' involvement, as well as on collaboration assessment.
Our approach based on advanced Natural Language Processing techniques provides a qualitative estimation of the learning process and enhances understanding as a "mediator of learning" by providing automated feedback to both learners and teachers or tutors. The main benefits are its flexibility, extensibility and nevertheless specificity for covering multiple stages, starting from reading classroom materials, to discussing on specific topics in a collaborative manner and finishing the feedback loop by verbalizing metacognitive thoughts. |
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