Pub Date : 2022-08-01DOI: 10.1007/s40593-022-00298-y
Randi Williams, Safinah Ali, Nisha Devasia, Daniella DiPaola, Jenna Hong, Stephen P Kaputsos, Brian Jordan, Cynthia Breazeal
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.
{"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":"10.1007/s40593-022-00298-y","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":4.9,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9342939/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40676584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1007/s40593-022-00302-5
Amanda E. Griffith, G. Katuka, Joseph B. Wiggins, K. Boyer, Jason Freeman, Brian Magerko, Tom McKlin
{"title":"Investigating the Relationship Between Dialogue States and Partner Satisfaction During Co-Creative Learning Tasks","authors":"Amanda E. Griffith, G. Katuka, Joseph B. Wiggins, K. Boyer, Jason Freeman, Brian Magerko, Tom McKlin","doi":"10.1007/s40593-022-00302-5","DOIUrl":"https://doi.org/10.1007/s40593-022-00302-5","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48533509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-21DOI: 10.1007/s40593-022-00296-0
Luke G Eglington, P. Pavlik
{"title":"How to Optimize Student Learning Using Student Models That Adapt Rapidly to Individual Differences","authors":"Luke G Eglington, P. Pavlik","doi":"10.1007/s40593-022-00296-0","DOIUrl":"https://doi.org/10.1007/s40593-022-00296-0","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41837387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-02DOI: 10.1007/s40593-022-00294-2
Christopher M. Ormerod, Susan Lottridge, Amy E. Harris, Milan Patel, Paul van Wamelen, Balaji Kodeswaran, Sharon Woolf, M. Young
{"title":"Automated Short Answer Scoring Using an Ensemble of Neural Networks and Latent Semantic Analysis Classifiers","authors":"Christopher M. Ormerod, Susan Lottridge, Amy E. Harris, Milan Patel, Paul van Wamelen, Balaji Kodeswaran, Sharon Woolf, M. Young","doi":"10.1007/s40593-022-00294-2","DOIUrl":"https://doi.org/10.1007/s40593-022-00294-2","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44345584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid expansion of artificial intelligence (AI) necessitates promoting AI education at the K-12 level. However, educating young learners to become AI literate citizens poses several challenges. The components of AI literacy are ill-defined and it is unclear to what extent middle school students can engage in learning about AI as a sociotechnical system with socio-political implications. In this paper we posit that students must learn three core domains of AI: technical concepts and processes, ethical and societal implications, and career futures in the AI era. This paper describes the design and implementation of the Developing AI Literacy (DAILy) workshop that aimed to integrate middle school students' learning of the three domains. We found that after the workshop, most students developed a general understanding of AI concepts and processes (e.g., supervised learning and logic systems). More importantly, they were able to identify bias, describe ways to mitigate bias in machine learning, and start to consider how AI may impact their future lives and careers. At exit, nearly half of the students explained AI as not just a technical subject, but one that has personal, career, and societal implications. Overall, this finding suggests that the approach of incorporating ethics and career futures into AI education is age appropriate and effective for developing AI literacy among middle school students. This study contributes to the field of AI Education by presenting a model of integrating ethics into the teaching of AI that is appropriate for middle school students.
{"title":"Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study.","authors":"Helen Zhang, Irene Lee, Safinah Ali, Daniella DiPaola, Yihong Cheng, Cynthia Breazeal","doi":"10.1007/s40593-022-00293-3","DOIUrl":"10.1007/s40593-022-00293-3","url":null,"abstract":"<p><p>The rapid expansion of artificial intelligence (AI) necessitates promoting AI education at the K-12 level. However, educating young learners to become AI literate citizens poses several challenges. The components of AI literacy are ill-defined and it is unclear to what extent middle school students can engage in learning about AI as a sociotechnical system with socio-political implications. In this paper we posit that students must learn three core domains of AI: technical concepts and processes, ethical and societal implications, and career futures in the AI era. This paper describes the design and implementation of the Developing AI Literacy (DAILy) workshop that aimed to integrate middle school students' learning of the three domains. We found that after the workshop, most students developed a general understanding of AI concepts and processes (e.g., supervised learning and logic systems). More importantly, they were able to identify bias, describe ways to mitigate bias in machine learning, and start to consider how AI may impact their future lives and careers. At exit, nearly half of the students explained AI as not just a technical subject, but one that has personal, career, and societal implications. Overall, this finding suggests that the approach of incorporating ethics and career futures into AI education is age appropriate and effective for developing AI literacy among middle school students. This study contributes to the field of AI Education by presenting a model of integrating ethics into the teaching of AI that is appropriate for middle school students.</p>","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9084886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45437969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1007/s40593-022-00290-6
P. Wulff, Lukas Mientus, Ann I. Nowak, Andreas Borowski
{"title":"Utilizing a Pretrained Language Model (BERT) to Classify Preservice Physics Teachers’ Written Reflections","authors":"P. Wulff, Lukas Mientus, Ann I. Nowak, Andreas Borowski","doi":"10.1007/s40593-022-00290-6","DOIUrl":"https://doi.org/10.1007/s40593-022-00290-6","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46816473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-15DOI: 10.1007/s40593-022-00292-4
Jingwan Tang, Xiaoping Zhou, Xiaoyu Wan, Michael Daley, Zhengyan Bai
{"title":"ML4STEM Professional Development Program: Enriching K-12 STEM Teaching with Machine Learning","authors":"Jingwan Tang, Xiaoping Zhou, Xiaoyu Wan, Michael Daley, Zhengyan Bai","doi":"10.1007/s40593-022-00292-4","DOIUrl":"https://doi.org/10.1007/s40593-022-00292-4","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49333851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-13DOI: 10.1007/s40593-021-00280-0
Lu Shao, R. Levine, Maureen A. Guarcello, Morten C. Wilke, Jeanne Stronach, James P. Frazee, J. Fan
{"title":"Estimating a Dose-Response Relationship in Quasi-Experimental Student Success Studies","authors":"Lu Shao, R. Levine, Maureen A. Guarcello, Morten C. Wilke, Jeanne Stronach, James P. Frazee, J. Fan","doi":"10.1007/s40593-021-00280-0","DOIUrl":"https://doi.org/10.1007/s40593-021-00280-0","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44421488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-02DOI: 10.1007/978-3-031-11644-5
S. Esmaeilzadeh, Brian Williams, Davood Shamsi, Onar Vikingstad
{"title":"Artificial Intelligence in Education: 23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part I","authors":"S. Esmaeilzadeh, Brian Williams, Davood Shamsi, Onar Vikingstad","doi":"10.1007/978-3-031-11644-5","DOIUrl":"https://doi.org/10.1007/978-3-031-11644-5","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73741242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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