Reducing Unconscious Bias in Student Performance Evaluations With Teacher-Guided AI

Leveraging automation and moderation to promote equitable assessment

Introduction Student assessments are meant to evaluate work objectively based on rigorous rubrics, not preconceptions. However, unconscious biases related to race, gender, personality, and other factors can inadvertently creep into grading and distort results. While most teachers strive for impartiality, inherent biases make true objectivity difficult. Fortunately, advancements in artificial intelligence present new opportunities to supplement teacher grading with automated scoring algorithms that consistently apply criteria without biases. Automation can help surface and reduce unconscious prejudices. [Read More]