Randi Williams, Safinah Ali, Nisha Devasia, Daniella DiPaola, Jenna Hong, Stephen P Kaputsos, Brian Jordan, Cynthia Breazeal
{"title":"面向中学生的人工智能+道德课程:从三个基于项目的课程中汲取的经验教训。","authors":"Randi Williams, Safinah Ali, Nisha Devasia, Daniella DiPaola, Jenna Hong, Stephen P Kaputsos, Brian Jordan, Cynthia Breazeal","doi":"10.1007/s40593-022-00298-y","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial Intelligence (AI) is revolutionizing many industries and becoming increasingly ubiquitous in everyday life. To empower children growing up with AI to navigate society's evolving sociotechnical context, we developed three middle school AI literacy curricula: <i>Creative AI, Dancing with AI,</i> and <i>How to Train Your Robot.</i> In this paper we discuss how we leveraged three design principles-active learning, embedded ethics, and low barriers to access - to effectively engage students in learning to create and critique AI artifacts. During the summer of 2020, we recruited and trained in-service, middle school teachers from across the United States to co-instruct online workshops with students from their schools. In the workshops, a combination of hands-on unplugged and programming activities facilitated students' understanding of AI. As students explored technical concepts in tandem with ethical ones, they developed a critical lens to better grasp how AI systems work and how they impact society. We sought to meet the specified needs of students from a range of backgrounds by minimizing the prerequisite knowledge and technology resources students needed to participate. Finally, we conclude with lessons learned and design recommendations for future AI curricula, especially for K-12 in-person and virtual learning.</p>","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.7000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342939/pdf/","citationCount":"0","resultStr":"{\"title\":\"AI + Ethics Curricula for Middle School Youth: Lessons Learned from Three Project-Based Curricula.\",\"authors\":\"Randi Williams, Safinah Ali, Nisha Devasia, Daniella DiPaola, Jenna Hong, Stephen P Kaputsos, Brian Jordan, Cynthia Breazeal\",\"doi\":\"10.1007/s40593-022-00298-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial Intelligence (AI) is revolutionizing many industries and becoming increasingly ubiquitous in everyday life. To empower children growing up with AI to navigate society's evolving sociotechnical context, we developed three middle school AI literacy curricula: <i>Creative AI, Dancing with AI,</i> and <i>How to Train Your Robot.</i> In this paper we discuss how we leveraged three design principles-active learning, embedded ethics, and low barriers to access - to effectively engage students in learning to create and critique AI artifacts. During the summer of 2020, we recruited and trained in-service, middle school teachers from across the United States to co-instruct online workshops with students from their schools. In the workshops, a combination of hands-on unplugged and programming activities facilitated students' understanding of AI. As students explored technical concepts in tandem with ethical ones, they developed a critical lens to better grasp how AI systems work and how they impact society. We sought to meet the specified needs of students from a range of backgrounds by minimizing the prerequisite knowledge and technology resources students needed to participate. Finally, we conclude with lessons learned and design recommendations for future AI curricula, especially for K-12 in-person and virtual learning.</p>\",\"PeriodicalId\":46637,\"journal\":{\"name\":\"International Journal of Artificial Intelligence in Education\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342939/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Artificial Intelligence in Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40593-022-00298-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence in Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40593-022-00298-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
AI + Ethics Curricula for Middle School Youth: Lessons Learned from Three Project-Based Curricula.
Artificial Intelligence (AI) is revolutionizing many industries and becoming increasingly ubiquitous in everyday life. To empower children growing up with AI to navigate society's evolving sociotechnical context, we developed three middle school AI literacy curricula: Creative AI, Dancing with AI, and How to Train Your Robot. In this paper we discuss how we leveraged three design principles-active learning, embedded ethics, and low barriers to access - to effectively engage students in learning to create and critique AI artifacts. During the summer of 2020, we recruited and trained in-service, middle school teachers from across the United States to co-instruct online workshops with students from their schools. In the workshops, a combination of hands-on unplugged and programming activities facilitated students' understanding of AI. As students explored technical concepts in tandem with ethical ones, they developed a critical lens to better grasp how AI systems work and how they impact society. We sought to meet the specified needs of students from a range of backgrounds by minimizing the prerequisite knowledge and technology resources students needed to participate. Finally, we conclude with lessons learned and design recommendations for future AI curricula, especially for K-12 in-person and virtual learning.
期刊介绍:
IJAIED publishes papers concerned with the application of AI to education. It aims to help the development of principles for the design of computer-based learning systems. Its premise is that such principles involve the modelling and representation of relevant aspects of knowledge, before implementation or during execution, and hence require the application of AI techniques and concepts. IJAIED has a very broad notion of the scope of AI and of a ''computer-based learning system'', as indicated by the following list of topics considered to be within the scope of IJAIED: adaptive and intelligent multimedia and hypermedia systemsagent-based learning environmentsAIED and teacher educationarchitectures for AIED systemsassessment and testing of learning outcomesauthoring systems and shells for AIED systemsbayesian and statistical methodscase-based systemscognitive developmentcognitive models of problem-solvingcognitive tools for learningcomputer-assisted language learningcomputer-supported collaborative learningdialogue (argumentation, explanation, negotiation, etc.) discovery environments and microworldsdistributed learning environmentseducational roboticsembedded training systemsempirical studies to inform the design of learning environmentsenvironments to support the learning of programmingevaluation of AIED systemsformal models of components of AIED systemshelp and advice systemshuman factors and interface designinstructional design principlesinstructional planningintelligent agents on the internetintelligent courseware for computer-based trainingintelligent tutoring systemsknowledge and skill acquisitionknowledge representation for instructionmodelling metacognitive skillsmodelling pedagogical interactionsmotivationnatural language interfaces for instructional systemsnetworked learning and teaching systemsneural models applied to AIED systemsperformance support systemspractical, real-world applications of AIED systemsqualitative reasoning in simulationssituated learning and cognitive apprenticeshipsocial and cultural aspects of learningstudent modelling and cognitive diagnosissupport for knowledge building communitiessupport for networked communicationtheories of learning and conceptual changetools for administration and curriculum integrationtools for the guided exploration of information resources