AI Integrated Workflow for Automated Assignment Grading and Feedback

Automated Assignment Grading and Feedback

1. Assignment Submission

1.1 Student Upload

Students submit their assignments through an online platform, such as Google Classroom or Canvas.

1.2 File Format Verification

The system checks the submitted files for acceptable formats (e.g., PDF, Word, etc.) using tools like Turnitin or Grammarly.

2. AI-Driven Grading

2.1 Initial Assessment with AI Tools

Utilize AI grading tools such as Gradescope or ZipGrade to conduct an initial assessment of the submissions based on predefined rubrics.

2.2 Natural Language Processing (NLP) Analysis

Implement NLP algorithms to analyze written assignments for coherence, grammar, and content relevance using tools like OpenAI’s GPT or IBM Watson.

3. Feedback Generation

3.1 Automated Feedback Compilation

The system compiles feedback based on grading results, utilizing AI tools like FeedbackFruits or Peergrade for personalized comments.

3.2 Customization of Feedback

Instructors can review and customize the AI-generated feedback to ensure it aligns with educational objectives and student needs.

4. Communication of Results

4.1 Notification to Students

Once grading is complete, the system sends automated notifications to students via email or the educational platform.

4.2 Access to Feedback

Students can access their grades and feedback through the same platform where they submitted their assignments.

5. Continuous Improvement

5.1 Data Analysis

Utilize analytics tools to assess overall student performance and identify areas for improvement in teaching methods.

5.2 Iterative Enhancement of AI Models

Regularly update AI algorithms based on feedback and performance data to enhance grading accuracy and feedback quality.

6. Instructor Review

6.1 Final Review of Grades

Instructors review AI-generated grades and feedback to ensure fairness and accuracy before finalizing results.

6.2 Student Appeals Process

Establish a clear process for students to appeal grades, ensuring transparency and trust in the automated system.