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Writing Instruction for TAs

The Writing Instruction for TAs (WIT) Project is a Faculty of Arts and Science teaching initiative that integrates writing instruction with disciplinary teaching, focusing especially on the role of course teaching assistants. 

Participating academic units receive funding to hire a Lead Writing TA (LWTA) and to allocate additional hours to course TAs for training and for providing writing instruction and formative feedback to students.

The WIT project supports writing instruction at all levels, including formulating departmental writing goals, designing writing assignments for building skills, and developing discipline-specific resources for writing instruction.

Participation in WIT

  • helps academic units implement their commitments to building students' core skills in communication
  • fosters discussions about a program's wider learning expectations and
  • offers opportunities for units to develop distinctive approaches to the learning and teaching of writing as part of their disciplines.









 


Instead of one-size-fits-all courses in academic writing WIT integrates writing into the discipline, allowing academic units to define what types of writing their students need to do — and how it should be structured. For example:

  • Math students received specialized training on writing proofs designed to support very specific arguments.

  • Ecology and Evolutionary Biology students were introduced to science writing. Students were required to turn in three different drafts of a scientific proposal: one for peer review, a rough draft and final draft that were all marked and commented on by TAs.

  • Philosophy students receive extra writing support and training for in-class instruction on both critical reading and philosophical essay writing skills.

  • Students in Chemistry benefited from an approach where they learned how to writing professional lab reports in first year – a skill that is built upon as the students progress to upper level classes.

  • Students in Computer Science learned things such as linux manual pages, software requirements, data structures, and instructions for a phone application. These were presented not artificial tasks to force them to write, but as realistic parts of what may be required in their future jobs.