Automated Feedback: An AI-powered Tool to Scale Micro-level Feedback for Better Academic Writing

Reviewing written work – whether between peers or from teacher to learner – can be an arduous process, exponentially more so within larger student cohorts. With that large potential time-sink, even less time is available for teaching. In addition, the majority of instructors’ time is focused on correcting spelling, grammar, style, and semantics, rather than content and argumentation. These are ‘micro-level’ or ‘lower-order’ concerns: the writing aspects unrelated to argumentation or reasoning such as grammar, spelling, or reference. Focusing on these would divert teachers from providing feedback on ‘higher-order’ writing aspects: argumentation, reasoning, style and flow. This then increases teachers’ workload while reducing the feedback quality delivered to students.
In order to address this issue, FeedbackFruits – an educational technology provider for higher education – collaborated with Erasmus University Rotterdam, Rotterdam University of Applied Sciences, and Deakin University to develop an AI-powered academic writing tool, Automated Feedback. This tool provides instant formative feedback for students on their lower-order concerns (such as correct references and grammar) to iteratively improve their writing product before handing in the final version. That is, teachers set up feedback criteria for students’ assignments covering elements such as structure and content, academic language, citations and references, tables and figures within the tool. To fit into teachers’ existing workflow, the tool integrates with different learning management systems (LMSs) including Canvas, Brightspace, Moodle, and Blackboard. Based on the teacher-configured rubric of feedback criteria, Automated Feedback analyzes the assignment and provides actionable feedback for students, thus helping them develop their academic writing skills, while reducing the reviewing workload of the teacher.

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Jun 02 2022


2:30 pm - 3:00 pm