We’ll have three pieces of work to be presented in EC-TEL 2017 in Tallinn, Estonia, on 12-15 Sept.
First of all, a demo of ReaderBench, the system I’m working on, in collaboration with Mihai Dascalu, Stefan Trausan-Matu and their team of UPB (Romania), as well as Danielle McNamara (Arizona State Univ.) and Scott Crossley (Georgia State Univ.), with a focus on the textual complexity features of the system.
Secondly, a poster introducing to Semantic Boogle, a Boogle-based game for learning vocabulary which populates the grid with semantically-related words from a given stem (and relying on ReaderBench).
Thirdly, a full paper (written with Laurent Thuez, from the nurse training institute of Annecy-Genevois, France, Mihai Dascalu, and Stefan Trausan-Matu ) aiming at automatically analyzing a set of nurse students case studies. We wondered to what extent some indices from a large series of complexity measures can predict the human assessment of these case studies.