Automated Feedback

Automating grading and feedback can save educators time and give students immediate feedback.

AI has the capability to automate grading. This is helpful for multiple reasons, including increased consistency, efficiency, and speed. Not only are educators saving valuable time, but students are able to receive more immediate feedback.

Automating Different Assessment Types

Multiple Choice & True/False Questions
Automated grading is a great fit with multiple choice and true/false questions. It’s able to analyze both digital answer sheets and scanned physical answer sheets, determine if an answer is correct, and assign a grade. This process is both fast and accurate.
Fill-in-the-Blank & Short Answer Questions
AI does have limitations for these types of questions, but it’s still helpful in reducing grading workload. For these, AI must be programmed to evaluate if an answer matches a predefined answer or certain keywords to determine whether an answer is correct or incorrect. 
Essay Questions
Natural language processing (NLP) can be used to assess essay-style questions. AI algorithms can analyze the content, grammar, and structure of essays and provide feedback and a grade based on different criteria. 
Rubric-Based Assessments
AI can be programmed to follow predefined rubrics to grade certain assignments. For example, if a rubric indicates that an assignment should have a certain number of paragraphs, AI can detect this and evaluate the quality of those paragraphs.

Those aren’t the only ways that AI can help with the grading process.

Additional Uses

  • Adaptive Testing
    • Just like with adaptive learning, AI can power adaptive testing by adjusting the difficulty of questions based on how students answer previous ones. This ensures that students are receiving the appropriate amount of rigor for their skill levels.
  • Plagiarism Detection
    • AI can be used to detect plagiarism by comparing student work to its database of academic and online content. It will flag anything it perceives as copied or unoriginal text. We know what you’re all wondering, and yes, AI can actually detect AI-generated text in some cases.
  • Developing Grading Models
    • Grading models can be developed by using machine learning and deep learning. The models can be trained with human-graded assignments and learn patterns within this grading to apply to future assignments. These models will improve over time and become more and more accurate as they’re given and generate more data.
  • Consistency and Objectivity
    • People can get fatigued from lots of grading or unintentionally grade students differently. AI doesn’t. It grades consistently and objectively for all students. 
  • Immediate Feedback
    • Students can receive feedback immediately when AI is doing the grading. AI can even explain to students why an answer is incorrect. This helps student continue on with their learning path without so much wait time. 

So, you see, AI is an invaluable tool when it comes to grading. However, there are a few things you should keep in mind.

Other Considerations

  • Context and Creativity
    • As of right now, AI struggles to assess work that requires creativity, original ideas, or deep understanding of complex ideas. This type of grading is best left in the hands of human graders.
  • Training and Validation
    • It does take a lot of time and energy to train and validate AI grading systems so that they have good accuracy. This means a lot of upfront work is required to create them.
  • Ethical Concerns
    • Using AI to grade does raise some ethical concerns, namely data privacy, transparency, and fairness. It’s important to address these concerns if you’re using AI for your grading so everyone can build trust and be on the same page.