ReaderBench : An Integrated Cohesion-Centered Framework
ReaderBench is an automated software framework designed to support both students and tutors by making use of text mining techniques, advanced natural language processing, and social network analysis tools. ReaderBench is centered on comprehension prediction and assessment based on a cohesion-based representation of the discourse applied on different sources (e.g., textual materials, behavior tracks, metacognitive explanations, Computer Supported Collaborative Learning – CSCL – conversations). Therefore, ReaderBench can act as a Personal Learning Environment (PLE) which incorporates both individual and collaborative assessments. Besides the a priori evaluation of textual materials’ complexity presented to learners, our system supports the identification of reading strategies evident within the learners’ self-explanations or summaries. Moreover, ReaderBench integrates a dedicated cohesion-based module to assess participation and collaboration in CSCL conversations.
KeywordsTextual complexity assessment Identification of reading strategies Comprehension prediction Participation and collaboration evaluation
This research was partially supported by the 644187 RAGE H2020-ICT-2014 and the 2008-212578 LTfLL FP7 projects, by the NSF grants 1417997 and 1418378 to ASU, as well as by the POSDRU/159/1.5/S/132397 and 134398 projects by ANR DEVCOMP Project ANR-10-blan-1907-01. We are also grateful to Cecile Perret for her help in preparing this paper.
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