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DeepTutor - Promoting Deep Learning




AuthorTutor - Computer-Aided Authoring of Deep Tutors
The AuthorTutor project aims at developing a COMPUTER-AIDED AUTHORING ENVIRONMENT to enable researchers and developers TO AUTHOR deep TUTORS that promote deep learning of science.

AuthorTutor is a spin-off of the DeepTutor project, funded by the Institute for Education Sciences. DeepTutor is an advanced intelligent tutoring system that fosters students' deep understanding of complex science topics through quality interaction and instruction. More information about DeepTutor is available at www.deeptutor.org.

A major challenge in developing intelligent tutoring systems is authoring of instructional materials such as instructional tasks and assessment instruments as well as other components such as dialogue and semantic algorithms for dialogue-based tutoring systems. The authoring challenge is a major hindrance to porting existing state-of-the-art intelligent tutoring systems to new topics and domains. The AuthorTutor project addresses the authoring challenge by proposing to develop a computer-aided environment that would assist researchers, educators, and developers of tutoring system to port their effective computer tutors to new topics and new domains in a matter of hours and weeks rather than months or years.

In particular, AuthorTutor is developed to efficiently scale DeepTutor or for that matter any other LP-driven educational technology to new domains. The AuthorTutor team will investigate well-defined principles and processes as well as software tools that would assist experts to systematically design the learning progressions and related items. More details about the AuthorTutor project can be found in the white paper available from the News section of this page, on the right hand side.

Besides DeepTutor, AuthorTutor builds upon the SEMILAR project (www.semanticsimilarity.org) which is an environment for investigating and authoring algorithms for understanding natural language utterances such as the ones produced by students during interaction with an intelligent tutoring system. Furthermore, it builds upon pioneering work by Dr. Vasile Rus on authoring speech act taxonomies (see the EDM 2012 publication on automated derivation of speech act taxonomies to be used in dialogue-based intelligent tutoring systems).

For any comments or questions please contact Dr. Vasile Rus (vrus@memphis.edu).


DEPARTMENT OF COMPUTER SCIENCE Dunn Hall 209, Memphis, TN 38152-3240 Phone 901.678.5259 Fax 901.678.1506 vrus@cs.memphis.edu