Open AccessDesigning for human–AI complementarity in K‐12 education
Author(s) -
Holstein Kenneth,
Aleven Vincent
Publication year - 2022
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1002/aaai.12058
Subject(s) - general partnership , analytics , complementarity (molecular biology) , participatory design , metacognition , learning analytics , citizen journalism , computer science , process (computing) , field (mathematics) , artificial intelligence , mathematics education , knowledge management , engineering , psychology , data science , cognition , political science , mechanical engineering , parallels , neuroscience , biology , world wide web , genetics , operating system , mathematics , pure mathematics , law
Recent work has explored how complementary strengths of humans and artificial intelligence (AI) systems might be productively combined. However, successful forms of human–AI partnership have rarely been demonstrated in real‐world settings. We present the iterative design and evaluation of Lumilo, smart glasses that help teachers help their students in AI‐supported classrooms by presenting real‐time analytics about students’ learning, metacognition, and behavior. Results from a field study conducted in K‐12 classrooms indicate that students learn more when teachers and AI tutors work together during class. We discuss implications of this research for the design of human–AI partnerships. We argue for more participatory approaches to research and design in this area, in which practitioners and other stakeholders are deeply, meaningfully involved throughout the process. Furthermore, we advocate for theory‐building and for principled approaches to the study of human–AI decision‐making in real‐world contexts.