TY - GEN
T1 - Readerbench
T2 - 10th European Conference on Technology Enhanced Learning, EC-TEL 2015
AU - Dascalu, Mihai
AU - Stavarache, Larise L.
AU - Dessus, Philippe
AU - Trausan-Matu, Stefan
AU - McNamara, Danielle
AU - Bianco, Maryse
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 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, Reader‐ Bench 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.
AB - 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, Reader‐ Bench 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.
KW - Comprehension prediction
KW - Identification of reading strategies
KW - Participation and collaboration evaluation
KW - Textual complexity assessment
UR - http://www.scopus.com/inward/record.url?scp=84944706606&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84944706606&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24258-3_47
DO - 10.1007/978-3-319-24258-3_47
M3 - Conference contribution
AN - SCOPUS:84944706606
SN - 9783319242576
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 505
EP - 508
BT - Design for Teaching and Learning in a Networked World - 10th European Conference on Technology Enhanced Learning, EC-TEL 2015, Proceedings
A2 - Konert, Johannes
A2 - Klobučar, Tomaž
A2 - Rensing, C.
A2 - Conole, Gráinne
A2 - Lavoue, Élisé
PB - Springer Verlag
Y2 - 15 September 2015 through 18 September 2015
ER -