Run as part of the Learning Analytics Learning Network (LALN)
November 2020 (Date TBC)
Location: Zoom webinar (Online)
Writing Analytics is a subfield of Learning Analytics that focuses on the challenges learners face in writing. It uses natural language processing (NLP) and machine learning technologies to analyse texts, and can be used to provide automated formative feedback on student writing.
This online workshop introduces educators and researchers to the affordances of writing analytics and automated writing feedback tools for students. We will first provide an overview of writing analytics techniques with examples of their educational applications.
We will then demo and explain the usage of the open-source AcaWriter tool developed by the Connected Intelligence Centre, University of Technology Sydney, which provides UTS students with 24/7 instant feedback on their writing. We will provide practical context by explaining how we co-design and evaluate this tool with educators and students, and how it is integrated with learning design.
A set of resources including Python code to generate sample automated feedback messages for technical participants, a learning design template for educators, and follow-up readings for all, will be shared with workshop participants to enable them to go deeper after the event.
Registration to the workshop is free and open to anyone interested to attend. We will send out a Zoom link to everyone closer to the date.
Please register here to receive the link.
Resources will be posted here to help participants prepare in advance, if they have time, and to get hands-on with writing analytics after the event. There will be activities suited for more technical participants, as well as for those with an interest in designing automated feedback, but no programming ability.
Shibani Antonette is a Lecturer and Researcher at the Faculty of Transdisciplinary Innovation, University of Technology Sydney (UTS). Her research work is on automated feedback from Writing analytics tools and its integration into the classroom for pedagogic use. She uses text analytics for analyzing writing and revision behaviors, and studies the interaction of writers with automated feedback. She is an active member of the learning analytics community and has chaired multiple Writing Analytics workshops at LAK and ALASI.
Ming Liu is a Research Fellow in Text Analytics at the Connected Intelligence Centre, UTS. His research work is focused on researching, developing and integrating automated feedback tools that support writing, reading and peer reviewing in the context of individual learning and collaborative learning using learning analytics and artificial intelligence.He has invested and participated several government funded writing analytics projects, such as Glosser, AcaWriter, Cooperpad and AQG. He has chaired prior Writing Analytics workshops at LAK and ALASI.
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where he directs the Connected Intelligence Centre. His research focuses on learning analytics for higher order competencies such as analytical and reflective academic writing, collaboration and learning-to-learn. He was a founding member and past Vice-President of the Society for Learning Analytics Research (SoLAR), and co-chaired the first Writing Analytics workshop at LAK 2016 and subsequent ones (see Events menu).