The project is coordinated around the Text Analytics Pipeline (TAP), an open source infrastructure developed initially at the University of Technology Sydney 2015-17. TAP’s services can be called via its API, demonstrated by these Jupyter Python notebooks, available as part of workshop training resources.

The project will test and extend TAP, e.g. with additional language services such as the Athanor rhetorical parser.

On top of these services will be developed a set of end-user applications tuned to the needs of the different priority areas. The project launches with one application, AcaWriter, already developed in the UTS Academic Writing Analytics (AWA) project, providing automated formative feedback to students on their writing (open source). Some examples below illustrate how this appears. Try out the demo version!

Personal, professional reflection feedback in AcaWriter (see AWA project for Gibson et al. 2017; Lucas et al. In Press):

Research writing feedback in AcaWriter (PhD work led by Sophie Abel, based on Swales’ CARS model):

Civil Law essay writing feedback in AcaWriter (PhD work led by Shibani Antonette, combining automated feedback with peer discussion):