Automated Writing Evaluation (AWE) is a recursive feedback concept that uses Natural Language Processing (NLP) to provide instantaneous, formative critiques on student prose. Unlike traditional "summative" grading—where a teacher returns a paper days after the student has lost interest—AWE creates a recursive loop. The student writes, receives immediate feedback on grammar, structure, or even argumentation, and is then prompted to revise immediately. This turns the act of writing from a "one-and-done" submission into a continuous, iterative dialogue between the learner and the machine.

Concept in Practice: Grammarly and MI Write

A sophisticated example of AWE is MI Write, used in K-12 settings. When a student drafts an essay, the system doesn't just "fix" errors; it provides "trait-based" feedback (e.g., ideas, organization, word choice).

The First Draft: A student submits a paragraph.
The Recursive Feedback: The AWE tool highlights a lack of evidence in the third sentence.
The Revision: The student adds a citation or data point and re-submits.
The Result: This cycle repeats multiple times before a human instructor ever sees the work. This frees the teacher to focus on high-level conceptual guidance rather than basic mechanics.

Why AWE is Vital for e-Learning Ecologies

AWE aligns with the Recursive Feedback domain because it promotes "mastery learning." It shifts the focus from "what is my grade?" to "how can I improve this specific sentence?" In a MOOC or a large-scale ubiquitous environment, AWE provides the scalability that human instructors cannot, ensuring that every student receives a personalized, "just-in-time" critique that fuels the next step in their learning journey.

References & Resources:

The Role of AWE in the Writing Process (ScienceDirect)
Educational Testing Service (ETS) on Automated Scoring
Writing-to-Learn with AWE (ResearchGate)

Automated Writing Evaluation (AWE): The Infinite Loop of Revision