Chapter 6: Formative Assessment keywords in sentences that don’t make sense, and other flaws that a human reader would easily notice. In a telling quote, one team that reviewed the state of the art wrote this: “Nevertheless, the time when AES systems will be able to operate on a par with human judges, with similar levels of connoisseurship for such features as meaning, emotion, originality, creativity, fluency, sense of audience and so on, arguably remains a long way off.” —Gardner, O’Leary, and Yuan The authors further note that while human and AI judgements of essays may correlate, people and computers are not noticing the same things in student writing. Due to these limitations, we must continue to emphasize a human in the loop foundation for AI-enhanced formative assessment. AI may support but not replace high-quality, human-led processes and practices of formative assessment in schools. 6.5. Key Opportunities for AI in Formative Assessment Based on the listening sessions we held, we see three key areas of opportunity in supporting formative assessment using AI systems and models. First, we recommend a strong focus on measuring what matters and particularly those things that have not been easily measured before and that many constituents would like to include in feedback loops. The example above, AES, was chosen because writing remains a valuable academic, workplace, and life skill. Looking at community goals through the lens of their visions for their high school graduates, we see that families/caregivers, students, and community leaders want to nurture graduates who solve problems adaptively, who communicate and collaborate well, who persevere and self-regulate when they experience 67 | P a g e
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