Creating rubrics that allow a large language model to evaluate a student's essay in a manner similar to a human teacher can be a challenging task. While language models like ChatGPT can provide automated assessments, it's important to note that they have limitations and cannot fully replicate the nuanced judgment and contextual understanding of human teachers. Nevertheless, here are some considerations for defining rubrics for automated essay evaluation:

1. Define clear criteria: Clearly articulate the criteria that will be used to evaluate the essay. This can include aspects such as content knowledge, organization, clarity of expression, coherence, use of evidence, and grammar. Each criterion should be well-defined and measurable.

2. Create multiple levels of performance: Develop a set of performance levels or score bands that capture different levels of achievement for each criterion. For example, you might have levels like "excellent," "good," "satisfactory," and "needs improvement" for each criterion. Provide specific descriptions for each level to guide the evaluation process.

3. Weighting and importance: Assign appropriate weights or importance to each criterion based on its significance. This helps in determining the overall score or grade for the essay. Consider the relative importance of different criteria and adjust the weights accordingly.

4. Provide examples: Include examples or anchor papers that illustrate the different levels of performance for each criterion. These examples can serve as reference points for the language model to compare and evaluate the student's essay.

5. Train and fine-tune the language model: Pre-training the language model on a large corpus of essays and fine-tuning it on a specific dataset with human-annotated scores can help align the model's evaluation with human judgments. By exposing the model to a range of essays with associated scores, it can learn to mimic human-like evaluations to some extent.

6. Continuous improvement and feedback: Regularly update and refine the rubrics based on insights gained from comparing the model's evaluations to human teacher evaluations. Collect feedback from human teachers and incorporate their expertise to enhance the rubric's accuracy and fairness.

It's crucial to note that while rubrics can provide structure and consistency, they should be seen as a tool to assist teachers rather than a complete replacement. Automated evaluation should be used in conjunction with human grading to ensure a comprehensive and holistic assessment of the student's work.

Additionally, it is essential to communicate to students that automated evaluation is being used and provide them with opportunities to understand the evaluation criteria and receive feedback from human teachers to support their learning and growth.

Finally, transparency about the limitations of automated evaluation is important to set appropriate expectations among students and other stakeholders.

Hello Professor Ilagan:

I wondered how ChatGPT 3.5 would handle your question. Below is the response I got; I did not edit it. What do you think of it?

" Evaluation Criteria:

Rubric Descriptor Example (for the "Relevance to the topic" criterion):

• Excellent (100%): The essay demonstrates a profound understanding of creativity and innovation concepts, clearly connecting them to real-world examples and addressing various dimensions of the topic, such as divergent thinking, organizational culture, and disruptive technologies.
• Good (80%): The essay shows a good grasp of the core concepts of creativity and innovation, offering relevant examples and discussing key aspects of the topic, but may lack depth in certain areas.
• Average (60%): The essay displays a basic understanding of the topic, addressing some aspects of creativity and innovation but lacking depth, coherence, or clear connections to real-world examples.
• Poor (40%): The essay fails to demonstrate a clear understanding of the topic of creativity and innovation, providing irrelevant or superficial content with limited or no connection to the subject matter.

By providing detailed descriptors for each performance level, you can guide the AES system in evaluating the essays and generating scores aligned with the rubric criteria. Remember to adapt the criteria and descriptors to your specific course and requirements."