Understanding AI Grading in STAR ECR

What is the primary system used for grading STAR ECR responses?

• Automated Scoring Engine (ASE)

• Artificial Intelligence (AI)

• Human Raters Only

• Machine Learning Model

What happens if the ASE system has low confidence in a score?

• The score is automatically accepted

• The response is discarded

• The response is marked as incorrect

• The response is sent to a human rater

What ensures the accuracy of the ASE system?

• 100% human scoring

• Peer reviews

• Random sampling of responses

• Automated checks

How are student responses evaluated according to the rubric?

• Holistically, considering the entire response

• By checking for a thesis statement

• Based on specific elements only

• By counting the number of words

What is the first step in developing the new scoring system?

• Training human scorers

• Reporting results

• Field testing

• Anchor approval meeting

What is the role of anchor responses in the scoring system?

• To provide examples of each score point

• To automate the scoring process

• To serve as final scores

• To replace human raters

What is the ASE system trained to emulate?

• AI scoring

• Human scoring

• Machine learning algorithms

• Automated grading

Who can request a rescore of a student's response?

• Only the student

• District personnel or guardians

• The teacher

• The principal

What is the purpose of item-level reports?

• To compare students across districts

• To summarize the entire test

• To detail points earned for each question

• To provide overall student performance

What is the significance of understanding the grading process?

• It helps in predicting scores

• It simplifies the test

• It reduces the need for human raters

• It is vital for educators, parents, and students