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[{"year":2020,"journal":"International Journal of Advanced Computer Science and Applications","author":"Alturayeif, Nora and Alturaief, Nouf and Alhathloul, Zainab","title":"DeepScratch: scratch programming language extension for deep learning education","booktitle":null,"url":"https:\/\/thesai.org\/Downloads\/Volume11No7\/Paper_77-DeepScratch_Scratch_Programming_Language.pdf","first author":"Alturayeif","country":"Saudi Arabia","assessments":"Project-Based Assessment","concepts":"Big Idea #3: Machine Learning","practices":"Constructing AI Artifacts: Training ML Models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary","setting":"Laboratory"},{"year":2021,"journal":null,"author":"Ali, Safinah and DiPaola, Daniella and Lee, Irene and Hong, Jenna and Breazeal, Cynthia","title":"Exploring Generative Models with Middle School Students","booktitle":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","url":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3411764.3445226","first author":"Ali-a","country":"USA","assessments":"Knowledge assessment, Classroom observation","concepts":"Big Idea #3: Generation, Big Idea #5: Ethics","practices":"Analyzing AI Artifacts: Recognizing everyday AI, Analyzing AI Artifacts: Identifying the inputs and outputs of ML systems, Analyzing AI Artifacts: Identifying ethical implications, Constructing AI Artifacts: Testing or evaluating ML models","perspectives":"Critical Digital Literacy: AI can be both beneficial and harmful","results?":"yes","k-12 study?":"yes","age group":"Middle, Secondary","setting":"Extracurricular (workshop)"},{"year":2021,"journal":"Ilkogretim Online","author":"Choi, Eunsun and Park, Namje","title":"Demonstration of Gamification in Education for Understanding Artificial Intelligence Principles at Elementary School Level.","booktitle":null,"url":"https:\/\/drive.google.com\/file\/d\/1JgiOCV8H7fYpEBVaO28oF06dP43OuPsc\/view?usp=sharing","first author":"Choi","country":"Korea","assessments":"Knowledge Self-Assessment, student course feedback","concepts":"Big Idea #3: Machine Learning, Big Idea #3: Deep Learning","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary","setting":"Extracurricular (workshop)"},{"year":2014,"journal":null,"author":"Benotti, Luciana and Mart{\\'\\i}nez, Mar{\\'\\i}a Cecilia and Schapachnik, Fernando","title":"Engaging high school students using chatbots","booktitle":"Proceedings of the 2014 conference on Innovation \\& technology in computer science education","url":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2591708.2591728","first author":"Benotti","country":"Argentina","assessments":"Student Course Feedback, Classroom Observation","concepts":"Big Idea #2: Automata And Intelligent Agents, Big Idea #4: Natural Language Processing, Big Idea #4: Chatbots","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Classroom"},{"year":2008,"journal":null,"author":"Bigham, Jeffrey P and Aller, Maxwell B and Brudvik, Jeremy T and Leung, Jessica O and Yazzolino, Lindsay A and Ladner, Richard E","title":"Inspiring blind high school students to pursue computer science with instant messaging chatbots","booktitle":"Proceedings of the 39th SIGCSE technical symposium on Computer science education","url":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1352322.1352287","first author":"Bigham","country":"USA","assessments":"Project-Based Assessment","concepts":"Big Idea #4: Chatbots, Big Idea #4: Natural Language Processing, Background: Humans Vs. Ai","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Laboratory"},{"year":2019,"journal":null,"author":"Druga, Stefania and Vu, Sarah T and Likhith, Eesh and Qiu, Tammy","title":"Inclusive AI literacy for kids around the world","booktitle":"Proceedings of FabLearn 2019","url":"https:\/\/www.cs.unm.edu\/~learningcomputing\/readings\/19_druga.pdf","first author":"Druga","country":"USA","assessments":"Perceptions of AI, Classroom Observation, Interviews and Discussion","concepts":"Big Idea #3: Machine Learning, Big Idea #4: Chatbots","practices":"Constructing AI Artifacts: Programming and Computational thinking","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle","setting":"Extracurricular (afterschool)"},{"year":2020,"journal":null,"author":"DiPaola, Daniella and Payne, Blakeley H and Breazeal, Cynthia","title":"Decoding design agendas: an ethical design activity for middle school students","booktitle":"Proceedings of the Interaction Design and Children Conference","url":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3392063.3394396","first author":"DiPaola","country":"USA","assessments":"Knowledge Assessment, Project-Based Assessment","concepts":"Background: What is AI, Big Idea #5: Societal Impact, Big Idea #5: Ethics","practices":"Analyzing AI Artifacts: Identifying ethical implications, Analyzing AI Artifacts: Identifying stakeholders\/values","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Middle","setting":"Extracurricular (summer)"},{"year":2021,"journal":null,"author":"Druga, Stefania and Ko, Amy J","title":"How do children\u2019s perceptions of machine intelligence change when training and coding smart programs?","booktitle":"Interaction Design and Children","url":"https:\/\/stefania11.github.io\/assets\/pdf\/IDC_Machine_Intelligence_Perception_2021.pdf","first author":"Druga","country":"USA","assessments":"Perceptions of AI, Classroom Observation","concepts":"Big Idea #3: Classification, Big Idea #3: Machine Learning, Big Idea #3: Natural Language Processing","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary","setting":"Extracurricular (afterschool)"},{"year":2021,"journal":"KI-K{\\\"u}nstliche Intelligenz","author":"Henry, Julie and Hernalesteen, Alyson and Collard, Anne-Sophie","title":"Teaching Artificial Intelligence to K-12 Through a Role-Playing Game Questioning the Intelligence Concept","booktitle":null,"url":"https:\/\/link.springer.com\/article\/10.1007\/s13218-021-00733-7","first author":"Henry","country":"Belgium","assessments":"Knowledge Assessment","concepts":"Big Idea #2: Logic Systems, Big Idea #3: Data and Data Visualization, Big Idea #3: Machine Learning, Big Idea #3: Prediction, Big Idea #5: Ethics","practices":"Analyzing AI Artifacts: Recognizing everyday AI, Constructing AI Artifacts: Data selection and feature selection","perspectives":"Digital Literacy: awareness of AI in personal life, Digital Literacy: awareness of AI's impact on culture, Critical Digital Literacy: AI can be both beneficial and harmful","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle","setting":"Classroom"},{"year":2018,"journal":null,"author":"Hitron, Tom and Wald, Iddo and Erel, Hadas and Zuckerman, Oren","title":"Introducing children to machine learning concepts through hands-on experience","booktitle":"Proceedings of the 17th ACM conference on interaction design and children","url":"https:\/\/dl.acm.org\/doi\/10.1145\/3202185.3210776","first author":"Hitron","country":"Israel","assessments":"Knowledge assessment, Knowledge transfer and application","concepts":"Big Idea #3: Machine Learning, Big Idea #3: Classification","practices":"Constructing AI Artifacts: Problem Scoping, Constructing AI Artifacts: Training ML models, Constructing AI Artifacts: Testing or evaluating ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle","setting":"Laboratory"},{"year":2019,"journal":null,"author":"Hitron, Tom and Orlev, Yoav and Wald, Iddo and Shamir, Ariel and Erel, Hadas and Zuckerman, Oren","title":"Can children understand machine learning concepts? The effect of uncovering black boxes","booktitle":"Proceedings of the 2019 CHI conference on human factors in computing systems","url":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3290605.3300645","first author":"Hitron","country":"Israel","assessments":"Knowledge transfer and application, Knowledge transfer and application, Knowledge Assessment, Knowledge Assessment","concepts":"Big Idea #3: Machine Learning","practices":"Constructing AI Artifacts: Testing or evaluating ML models, Constructing AI Artifacts: Testing or evaluating ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle","setting":"Laboratory"},{"year":2021,"journal":null,"author":"Long, Duri and Padiyath, Aadarsh and Teachey, Anthony and Magerko, Brian","title":"The Role of Collaboration, Creativity, and Embodiment in AI Learning Experiences","booktitle":"Creativity and Cognition","url":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3450741.3465264","first author":"Long","country":"USA","assessments":"Knowledge Self-Assessment","concepts":"Big Idea #1: Computer Vision, Big Idea #1: Gesture recognition, Big idea #2: Logic Systems, Big idea #2: Graphs and Data Structures, Big Idea #3: Classification, Big Idea #3: Machine Learning, Big Idea #3: Data and data visualization, Big Idea #3: Generation, Big Idea #4: Chatbots, Big Idea #4: Human-Computer Interaction","practices":"Constructing AI Artifacts: Creating (non-ML) models, Constructing AI Artifacts: Training ML models, Constructing AI Artifacts: Testing or evaluating ML models, Constructing AI Artifacts: Collaborating","perspectives":"Identity and Social Awareness: belief in one's capability","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary, Adult","setting":"Extracurricular (museum)"},{"year":2021,"journal":null,"author":"Melsi{\\'o}n, Gaspar Isaac and Torre, Ilaria and Vidal, Eva and Leite, Iolanda","title":"Using Explainability to Help Children UnderstandGender Bias in AI","booktitle":"Interaction Design and Children","url":"https:\/\/dl.acm.org\/doi\/fullHtml\/10.1145\/3459990.3460719","first author":"Melsion","country":"Sweden","assessments":"Knowledge Assessment","concepts":"Big Idea #3: Machine Learning, Big Idea #3: Classification, Big Idea #5: Bias","practices":"Constructing AI Artifacts: Training ML Models, Constructing AI Artifacts: Testing or Evaluating ML Models, Analyzing AI Artifacts: Evaluating bias in models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle","setting":"Laboratory"},{"year":2021,"journal":null,"author":"Olari, Viktoriya and Cvejoski, Kostadin and Eide, {\\O}yvind","title":"Introduction to Machine Learning with Robots and Playful Learning","booktitle":"Proceedings of the AAAI Conference on Artificial Intelligence","url":"https:\/\/www.aaai.org\/AAAI21Papers\/EAAI-51.OlariV.pdf","first author":"Olari","country":"Germany","assessments":"Knowledge Self-Assessment, Student Course Feedback, Attitudes toward computing","concepts":"Big Idea #2: Automata And Intelligent Agents, Big Idea #3: Machine Learning, Big Idea #3: Reinforcement Learning","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary","setting":"Extracurricular (workshop)"},{"year":2021,"journal":null,"author":"Rodr{\\'\\i}guez-Garc{\\'\\i}a, Juan David and Moreno-Le{\\'o}n, Jes{\\'u}s and Rom{\\'a}n-Gonz{\\'a}lez, Marcos and Robles, Gregorio","title":"Evaluation of an Online Intervention to Teach Artificial Intelligence with LearningML to 10-16-Year-Old Students","booktitle":"Proceedings of the 52nd ACM Technical Symposium on Computer Science Education","url":"https:\/\/dl.acm.org\/doi\/10.1145\/3408877.3432393","first author":"Rodriguez-Garcia","country":"Spain","assessments":"Knowledge Assessment","concepts":"Big Idea #3: Machine Learning","practices":"Constructing AI Artifacts: Training ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary","setting":"Informal (Asynchronous online materials)"},{"year":2020,"journal":null,"author":"Shamir, Gilad and Levin, Ilya","title":"Transformations of computational thinking practices in elementary school on the base of artificial intelligence technologies","booktitle":"Proceedings of EDULEARN20 Conference","url":"https:\/\/www.researchgate.net\/profile\/Ilya-Levin-2\/publication\/343424240_TRANSFORMATIONS_OF_COMPUTATIONAL_THINKING_PRACTICES_IN_ELEMENTARY_SCHOOL_ON_THE_BASE_OF_ARTIFICIAL_INTELLIGENCE_TECHNOLOGIES\/links\/5fd09b64a6fdcc697bef8dad\/TRANSFORMATIONS-OF-COMPUTATIONAL-THINKING-PRACTICES-IN-ELEMENTARY-SCHOOL-ON-THE-BASE-OF-ARTIFICIAL-INTELLIGENCE-TECHNOLOGIES.pdf","first author":"Shamir","country":"Israel","assessments":"Knowledge Assessment, Student Course Feedback, attitudes toward computing","concepts":"Big Idea #3: Machine Learning, Background: What Is Ai","practices":"Constructing AI Artifacts: Problem Scoping, Constructing AI Artifacts: Implementation, Constructing AI Artifacts: Training ML models, Constructing AI Artifacts: Testing or evaluating ML models, Constructing AI Artifacts: Testing or evaluating ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary","setting":"Extracurricular"},{"year":2018,"journal":null,"author":"Kahn, K Megasari and Megasari, Rani and Piantari, Erna and Junaeti, Enjun","title":"AI programming by children using snap! block programming in a developing country","booktitle":null,"url":"http:\/\/ceur-ws.org\/Vol-2193\/paper1.pdf","first author":"Kahn","country":"UK","assessments":"Knowledge Assessment","concepts":"Big Idea #1: Computer Vision, Big Idea #4: Speech Synthesis","practices":"Constructing AI Artifacts: Programming and Computational thinking","perspectives":"Critical Digital Literacy: AI strengths and weaknesses","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Extracurricular (workshop)"},{"year":2016,"journal":null,"author":"Kandlhofer, Martin and Steinbauer, Gerald and Hirschmugl-Gaisch, Sabine and Huber, Petra","title":"Artificial intelligence and computer science in education: From kindergarten to university","booktitle":"2016 IEEE Frontiers in Education Conference (FIE)","url":"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&arnumber=7757570","first author":"Kandlhofer","country":"Austria","assessments":"Knowledge Self-Assessment, Knowledge Assessment, Student Course Feedback, Project-Based Assessment, Classroom observation, Attitudes toward computing","concepts":"Big Idea #2: Automata And Intelligent Agents, Big Idea #2: Graphs And Data Structures, Big Idea #2: Sorting And Search, Background: What is AI","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary, University","setting":"Classroom"},{"year":2021,"journal":"KI-K{\\\"u}nstliche Intelligenz","author":"Shamir, Gilad and Levin, Ilya","title":"Neural Network Construction Practices in Elementary School","booktitle":null,"url":"https:\/\/link.springer.com\/article\/10.1007\/s13218-021-00729-3","first author":"Shamir","country":"Israel","assessments":"Knowledge Assessment, Project-Based Assessment, Interviews and Discussion","concepts":"Background: What is AI, Big Idea #3: Machine Learning, Big Idea #3: Classification, Interdisciplinary: Ecosystems","practices":"Constructing AI Artifacts: Programming and Computational thinking, Constructing AI Artifacts: Training ML models, Constructing AI Artifacts: Validating ML models, Constructing AI Artifacts: Testing or evaluating ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary","setting":"Extracurricular"},{"year":2021,"journal":null,"author":"Tseng, Tiffany and Murai, Yumiko and Freed, Natalie and Gelosi, Deanna and Ta, Tung D and Kawahara, Yoshihiro","title":"PlushPal: Storytelling with Interactive Plush Toys and Machine Learning","booktitle":"Interaction Design and Children","url":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3459990.3460694","first author":"Tseng","country":"USA","assessments":"Project-Based Assessment, Knowledge assessment, Knowledge transfer and application, Interviews and Discussion, Classroom Observation","concepts":"Big Idea #1: Sensors and Perception, Big Idea #1: Gesture Recognition, Big Idea #3: Machine Learning, Big Idea #3: Classification, Big Idea #3: Data and data visualization","practices":"Constructing AI Artifacts: Training ML models, Constructing AI Artifacts: Testing or evaluating ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary","setting":"Laboratory"},{"year":2021,"journal":"International Journal of Child-Computer Interaction","author":"Vartiainen, Henriikka and Toivonen, Tapani and Jormanainen, Ilkka and Kahila, Juho and Tedre, Matti and Valtonen, Teemu","title":"Machine 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with very young children: Who is teaching whom?","booktitle":null,"url":"https:\/\/drive.google.com\/file\/d\/15Whj4JvXMhvxgNNcS85cHe030fDHlaf6\/view?usp=sharing","first author":"Vartiainen-b","country":"Finland","assessments":"Knowledge transfer and application, Knowledge Assessment","concepts":"Big Idea #3: Machine Learning","practices":"Constructing AI Artifacts: Training ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary","setting":"Extracurricular"},{"year":2021,"journal":null,"author":"Voulgari, Iro and Zammit, Marvin and Stouraitis, Elias and Liapis, Antonios and Yannakakis, Georgios","title":"Learn to Machine Learn: Designing a Game Based Approach for Teaching Machine Learning to Primary and Secondary Education Students","booktitle":"Interaction Design and Children","url":"https:\/\/dl.acm.org\/doi\/fullHtml\/10.1145\/3459990.3465176","first author":"Voulgari","country":"Malta","assessments":"Student course feedback","concepts":"Big Idea #2: Path Planning, Big Idea #3: Machine Learning, Big Idea #3: Classification, Big Idea #3: Data and Data visualization, Big Idea #3: Reinforcement Learning, Big Idea #5: Bias","practices":"Constructing AI Artifacts: Training ML Models, Constructing AI Artifacts: Testing or Evaluating ML Models, Analyzing AI Artifacts: Evaluating bias in models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary, Middle, Secondary","setting":"Extracurricular"},{"year":2019,"journal":null,"author":"Williams, Randi and Park, Hae Won and Breazeal, Cynthia","title":"A is for artificial intelligence: the impact of artificial intelligence activities on young children's perceptions of robots","booktitle":"Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems","url":"http:\/\/robotic.media.mit.edu\/wp-content\/uploads\/sites\/7\/2019\/02\/CHI__PopBots_cameraready.pdf","first author":"Williams-a","country":"USA","assessments":"Perceptions of AI","concepts":"Big Idea #2: Logic Systems, Big Idea #3: Generation, Big Idea #3: Machine Learning, Interdisciplinary: Robotics","practices":"Constructing AI Artifacts: Programming and Computational thinking, Constructing AI Artifacts: Training ML models","perspectives":"Critical Digital Literacy: AI Systems Depend On Human Input","results?":"yes","k-12 study?":"yes","age group":"Pre-K, Primary","setting":"Extracurricular (afterschool)"},{"year":2021,"journal":null,"author":"Park, Kyungjin and Mott, Bradford and Lee, Seung and Glazewski, Krista and Scribner, J Adam and Ottenbreit-Leftwich, Anne and Hmelo-Silver, Cindy E and Lester, James","title":"Designing a Visual Interface for Elementary Students to Formulate AI Planning Tasks","booktitle":"2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL\/HCC)","url":"https:\/\/www.intellimedia.ncsu.edu\/wp-content\/uploads\/Park-VLHCC-2021.pdf","first author":"Park","country":"USA","assessments":"Classroom observation, Interviews and 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models","perspectives":"Critical Digital Literacy: AI Systems Depend On Human Input","results?":"yes","k-12 study?":"yes","age group":"Pre-K, Primary","setting":"Extracurricular (afterschool)"},{"year":2021,"journal":null,"author":"Ali, Safinah and DiPaola, Daniella and Breazeal, Cynthia","title":"What are GANs?: Introducing Generative Adversarial Networks to Middle School Students","booktitle":"Proceedings of the AAAI Conference on Artificial Intelligence","url":"http:\/\/robotic.media.mit.edu\/wp-content\/uploads\/sites\/7\/2021\/03\/EAAI-What-are-GANs_.pdf","first author":"Ali-b","country":"USA","assessments":"Knowledge Assessment, Student Course Feedback","concepts":"Big Idea #3: Machine Learning, Big Idea #3: Generators Vs. Discriminators","practices":"Analyzing AI Artifacts: Identifying the inputs and outputs of ML systems","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Middle","setting":"Extracurricular (summer)"},{"year":2011,"journal":"IEEE Signal Processing Magazine","author":"Rosen, Gail and Silverman, Jason and Essinger, Steve","title":"Inquiry-based learning through image processing","booktitle":null,"url":"https:\/\/ieeexplore.ieee.org\/abstract\/document\/6105471","first author":"Rosen","country":"USA","assessments":"Knowledge Assessment, attitudes toward computing","concepts":"Big Idea #1: Signal Processing","practices":"","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Classroom"},{"year":2020,"journal":null,"author":"Bilstrup, Karl-Emil Kj{\\ae}r and Kaspersen, Magnus H and Petersen, Marianne Graves","title":"Staging reflections on ethical dilemmas in machine learning: A card-based design workshop for high school 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Systems","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Extracurricular (workshop)"},{"year":2016,"journal":null,"author":"Burgsteiner, Harald and Kandlhofer, Martin and Steinbauer, Gerald","title":"Irobot: Teaching the basics of artificial intelligence in high schools","booktitle":"Proceedings of the AAAI Conference on Artificial Intelligence","url":"https:\/\/studylib.net\/doc\/13888734\/irobot--teaching-the-basics-of-arti%EF%AC%81cial-intelligence-in-...","first author":"Burgsteiner","country":"Austria","assessments":"Knowledge Self-Assessment, Student Course Feedback","concepts":"Big Idea #1: Sensors And Perception, Big Idea #2: Automata And Intelligent Agents, Big Idea #2: Graphs And Data Structures, Big Idea #2: Sorting And Search, Big Idea #3: Machine Learning, Interdisciplinary: Robotics","practices":"Constructing AI Artifacts: Programming and Computational thinking, Constructing AI Artifacts: Training ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Classroom"},{"year":2019,"journal":"IEEE access","author":"Estevez, Julian and Garate, Gorka and Gra{\\~n}a, Manuel","title":"Gentle introduction to artificial intelligence for high-school students using scratch","booktitle":null,"url":"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&arnumber=8915693","first author":"Estevez","country":"Spain","assessments":"Knowledge Assessment, Attitudes toward computing","concepts":"Big Idea #3: Machine Learning, Big Idea #3: Data And Data Visualization","practices":"Constructing AI Artifacts: Training ML models","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Secondary","setting":"Extracurricular (workshop)"},{"year":2021,"journal":null,"author":"Forsyth, Stacey and Dalton, Bridget and Foster, Ellie Haberl and Walsh, Benjamin and Smilack, Jacqueline and Yeh, Tom","title":"Imagine a More Ethical AI: Using Stories to Develop Teens\u2019 Awareness and Understanding of Artificial Intelligence and its Societal Impacts","booktitle":null,"url":"http:\/\/respect2021.stcbp.org\/wp-content\/uploads\/2021\/05\/506_Posters_06_paper_30.pdf","first author":"Foryth","country":"USA","assessments":"Knowledge Assessment, Project-Based Assessment, Classroom Observation","concepts":"Big Idea #2: Logic Systems, Big Idea #3: Generation, Big Idea #3: Machine Learning","practices":"Analyzing AI Artifacts: Data analysis, Analyzing AI Artifacts: Identifying ethical implications, Communicating About AI: Advocacy, Communicating About AI: Tech\/Scientific communication","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Middle, Secondary","setting":"Extracurricular (summer)"},{"year":2021,"journal":null,"author":"Jordan, Brian and Devasia, Nisha and Hong, Jenna and Williams, Randi and Breazeal, Cynthia","title":"PoseBlocks: A Toolkit for Creating (and Dancing) with AI","booktitle":"The 11th Symposium on Educational Advances in Artificial 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intelligence","booktitle":null,"url":"https:\/\/www.sciencedirect.com\/sdfe\/reader\/pii\/S2666920X20300060\/pdf","first author":"Lin","country":"China","assessments":"Attitudes toward computing","concepts":"Background: What is AI, Big Idea #1: Computer vision, Big Idea #3: Machine Learning","practices":"Constructing AI Artifacts: Programming and computational thinking","perspectives":"","results?":"yes","k-12 study?":"yes","age group":"Primary","setting":"Formal"}]