Time: 12:30 PM
Location: CIC Ideation Studio, UTS Building 22
The Connected Intelligence Centre ran a hands-on workshop for UTS staff on Writing Analytics. The workshop exposed attendees to the use of Natural Language Processing (NLP) tools, explored the potential and pitfalls of writing analytics and discussed the broader educational issues in this space.
Date: Tuesday June 6, 2017
Time: 12:30 – 3:30pm
Location: CIC Ideation Studio, Building 22, UTS (Blacfriars Precinct)
For details of the capabilities of CIC’s writing analytics tool, and the underpinning research, please visit the CIC Writing Analytics homepage.
The value of Writing Analytics
A large majority of academic disciplines focus on the development of learners’ skills in critical review, conceptual synthesis, reasoning and disciplinary/professional reflection. In these subjects, writing arguably serves as the primary window into the mind of the learner. Beyond scholarly academic writing, there is also interest in disciplined, autobiographical reflective writing as a way for student to review and consolidate their learning, thus providing a means for assessing the deepest kinds of shifts that can occur in learner agency and epistemology. However, writing is time consuming, labour intensive to assess, difficult for students to learn and not something that all educators can coach effectively.
Writing Analytics aims to address these challenges through computational analysis with Natural Language Processing (NLP) techniques. In a pedagogical context, Writing Analytics provides opportunities for scalable, near real-time feedback to learners and teachers for the purposes of assisting learners to improve the quality of their writing.
This workshop will introduce participants to some of these broader issues, before getting hands-on with relevant NLP tools in order to obtain a deeper understanding of the potential and pitflalls. Throuhghout the workshop we will engage with the following questions:
- How do we connect low level text analysis features (e.g. word vectors, topic models, parts of speech, lexical metrics) to higher level constructs of a learner’s writing?
- What are the various assumptions underpinning the computational models we use?
- How can we take a pedagogically informed perspective when working with computational models and algorithms?
- How do we measure the efficacy of our writing analytics approaches?
If you are interested in attending this event, please contact UTS:CIC Marketing Officer Jack Schmidt.