I’ve had a longstanding interest in exploring how students engage critically with automated feedback and develop their AI literacy. In our LAK22 paper, we argued why it is so important that we develop these skills in learners. There is a heightened necessity in today’s educational landscape for learners in the age of generative AI (Gen AI) to engage with AI critically.
Our upcoming CHI publication investigates the fundamental question: Why do students engage with Gen AI for their writing tasks, and how can they navigate this interaction critically? In our paper, we define in concrete terms and stages how criticality can manifest when students write with ChatGPT support. We draw from theory and examples in empirical data (which are still unbelievably scarce in the literature) to understand and expand the notion of critical interaction with AI.
A pre-print version is available for download on Arxiv [PDF]. Full citation below:
Next week, I’m presenting my work in the First workshop on Generative AI for Learning Analytics (GenAI-LA) at the 14th International Conference on Learning Analytics and Knowledge LAK 2024:
Antonette Shibani, Faerie Mattins, Srivarshan Selvaraj, Ratnavel Rajalakshmi & Gnana Bharathy (2024) Tamil Co-Writer: Towards inclusive use of generative AI for writing support. In Joint Proceedings of LAK 2024 Workshops, co-located with 14th International Conference on Learning Analytics and Knowledge (LAK 2024), Kyoto, Japan, March 18-22, 2024.
With colleagues in India, we developed Tamil Co-Writer, a GenAI-supported writing tool that offers AI suggestions for writing in the regional Indian language Tamil (which is my first language). The majority of AI-based writing assistants are created for English language users and do not address the needs of linguistically diverse groups of learners. Catering to languages typically under-represented in NLP is important in the generative AI era for the inclusive use of AI for learner support. Combined with analytics on AI usage, the tool can offer writers improved productivity and a chance to reflect on their optimal/sub-optimal collaborations with AI.
The tool combined the following elements:
An interactive AI writing environment that offers several input modes to write in Tamil
Analytics of writer’s AI interaction in the session for reflection (See post on CoAuthorViz for details, and related paper here)
A short video summarising the key insights from the paper is below:
Generative AI (GenAI) has captured global attention since ChatGPT was publicly released in November 2022. The remarkable capabilities of AI have sparked a myriad of discussions around its vast potential, ethical considerations, and transformative impact across diverse sectors, including education. In particular, how humans can learn to work with AI to augment their intelligence rather than undermine it greatly interests many communities.
My own interest in writing research led me to explore human-AI partnerships for writing. We are not very far from using generative AI technologies in everyday writing when co-pilots become the norm rather than an exception. It is possible that a ubiquitous tool like Microsoft Word that many use as their preferred platform for digital writing comes with AI support as an essential feature (and early research shows how people are imagining these) for improved productivity. But at what cost?
In our recent full paper, we explored an analytic approach to study writers’ support seeking behaviour and dependence on AI in a co-writing environment:
Using keystroke data from the interactive writing environment CoAuthor powered by GPT-3, we developed CoAuthorViz (See example figure below) to characterize writer interaction with AI feedback. ‘CoAuthorViz’ captured key constructs such as the writer incorporating a GPT-3 suggested text as is (GPT-3 suggestion selection), the writer not incorporating a GPT-3 suggestion (Empty GPT-3 call), the writer modifying the suggested text (GPT-3 suggestion modification), and the writer’s own writing (user text addition). We demonstrated how such visualizations (and associated metrics) help characterise varied levels of AI interaction in writing from low to high dependency on AI.
Figure: CoAuthorViz legend and three samples of AI-assisted writing (squares denote writer written text, and triangles denote AI suggested text)
Full details of the work can be found in the resources below:
Is autonomy (self-writing, without AI support) preferable to better quality writing (with AI support)?
As AI becomes embedded into our everyday writing, do we lose our own writing skills? And if so, is that of concern, or will writing become one of those outdated skills in the future that AI can do much better than humans?
Do we lose our ‘uniquely human’ attributes if we continue to write with AI?
What is an acceptable use of AI in writing that still lets you think? (We know by writing we think more clearly; would an AI tool providing the first draft restrict our thinking?)
What knowledge and skills do writers need to use AI tools appropriately?
