Chapter 6: Formative Assessment challenges. “What matters” today reaches beyond a sole focus on the core academic content measured by large-scale summative assessments, to support students and teachers with actionable feedback that nurtures the broader skills students need to succeed and thrive. Further, within core academic content, AI may help us to provide feedback on the more realistic and complex aspects of doing math, for example, or investigating scientific phenomena, understanding history, or discussing literature. Second, we’d like to see a strong focus on improving helpseeking and help-giving. Asking for and giving help is crucial to learning and practicing a growth-mindset and central to the notion of human feedback loops. Students may not always know when they need help. In one example, computer algorithms can detect a student who is “wheel spinning” (working hard on mastering content but not making progress).A student who is working hard may not feel like they need help, and the teacher may not be aware that the student is struggling if he or she appears to be “on task.” AI may also be helpful by highlighting for students and teachers what forms of assistance have been most useful to the student in the recent past so that an educator can expand access to specific assistance that works for that individual student. Finally, educators may learn things from AI-enabled systems and tools that give feedback and hints during the completion of homework, utilizing that feedback to later reinforce concepts in direct instruction and strengthen the one-on-one support provided to students. AIenabled systems and tools can provide teachers with additional information about the students’ recent work, so their instructor has a greater contextual sense as they begin to provide help. 68 | P a g e
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