|COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring.|
On automatically analyzing learner language: Interpreting form and meaning in context
If you have a question about this talk, please contact Chris Cummins.
The automatic analysis of learner language can play a role in the annotation of learner corpora and in intelligent language tutoring systems. In this talk, I first want to raise some questions about the nature of the linguistic categories which are appropriate for learner language under different perspectives, and which role the context, explicit tasks, and learner modeling play for the interpretation of learner language. Then the talk moves from analyzing form to evaluating aspects of meaning. I discuss our work in the CoMiC project on automatically evaluating the meaning of learner answers to reading comprehension questions, for which we explore which linguistic representations and comparison strategies are effective and robust enough to evaluate meaning in the face of significant well-formed and ill-formed variation.
This talk is part of the RCEAL Tuesday Colloquia series.
This talk is included in these lists:
Note that ex-directory lists are not shown.
Other listsLucy Cavendish College ECNM Group, Department of Materials Science and Metallurgy 1 and 1/2 APDE days
Other talksEthnographic collecting and the despotism of Joseph Banks Semantics derived automatically from language corpora necessarily contain human biases Manufacturing - the vital capability for effective innovation Myelination - the developmental pattern in the mouse neocortex and its role in learning The transiting dust clumps of a young Sun like star TBC