2 November 2016: Writing Analytics to Improve Formative Feedback

Presenters: Simon Buckingham Shum, Simon Knight, Andrew Gibson, Philippa Ryan and Adam Aitken (University of Technology Sydney).

Hosted by Dr Mathew Hillier, Monash University, Australia. Starting 07:00AM UTC/GMT. Duration 1 hour.

The education sector should be interested in the potential of “the data revolution” since it promises better feedback loops within complex systems. In the field known as Learning Analytics, there is significant effort being invested in the potential of new forms of digital data for improving learning, teaching and research. For educators, critical questions turn on issues such as what data is being logged, for whom, for what purpose, and how this relates to sound pedagogy, learning design and assessment regimes. Student writing is one type of educational data of particular interest to the Connected Intelligence Centre (CIC) at the University of Technology of Sydney (UTS). For a computer, writing is unstructured, messy, and difficult to analyse precisely because it is such a rich expressive medium. Although a computer does not read text like a person, Natural Language Processing can detect linguistic patterns that serve as proxies for the cognitive processes of the student. Since analysis is almost instantaneous, this offers the promise of personalised, formative assessment at a scale and speed that is otherwise impractical. As the product space fills up with automated writing tools, a key question for educators is how does one design writing analytics informed by the scholarship underpinning the teaching and learning of writing, and co-designed with literacy and academic subject matter experts?

In this webinar we introduced the these issues and describe the rationale, design and evaluation of writing analytics tools under development at CIC, and results of pilots with academics and their students engaged in analytical and reflective writing.

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