Chapter 6: Formative Assessment But as our discussion reveals, AI can only make feedback loops better if we keep a firm eye on the weaknesses of AI and how AI introduces new concerns. 6.4. An Example: Automated Essay Scoring One instructive example is Automated Essay Scoring (AES). To become strong writers, which is a valuable life skill, students need regular and specific feedback. However, reviewing and providing feedback on essays is very time consuming for humans. Hence, Ellis Page provided a first vision for computer programs that could review and provide feedback on student essays in 1966, and much effort has gone into AES technologies in the intervening 56 years. Many research review articles are available to summarize the progress, which has been impressive. Further, some of today’s applications of AES technologies will be familiar to readers, such as Grammarly, Turnitin, and the various essay analysis engines used by publishers and assessment companies. Also note that while the traditional AES functionality emphasizes scoring or rating essays, newer AI-enabled products focus more on providing students with constructive criticism and developing their skills as writers. Writing is a life skill that is important to the pursuit of college and career ambitions, and developing writers require comprehensive feedback. If developers could inexpensively augment human feedback to developing writers with AI feedback, it’s possible that support for learning to write could become more equitable. And yet, AES is an instructive example because researchers have analyzed limitations, too. AES technologies in AI can analyze some features of student essays but can also be misled by the length of an essay, by a student who places appropriate 66 | P a g e
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