Concord Consortium Inc

Data Science Learning Experiences for Middle School-aged Girls in Informal Gaming Clubs -data Is Increasingly Important in All Aspects of People?s Lives, From the Day-to-day, to Careers and to Civic Engagement. Preparing Youth to Use Data to Answer Questions and Solve Problems Empowers Them to Participate in Society as Informed Citizens and Opens Doors to 21ST Century Career Opportunities. Ensuring Equitable Representation in Data Literacy and Data Science Careers Is Critical. for Many Girls Underrepresented in Stem, Developing a Data Science Identity Requires Personally Meaningful Experiences Working With Data. This Project Aims to Promote Middle School-aged Girls? Interest and Aspirations in Data Science Through an Identity-aligned, Social Game-based Learning Approach. the Goals Are to Create a More Diverse and Inclusive Generation of Data Scientists Who See Data as a Resource and Who Are Equipped With the Skills and Dispositions Necessary to Work With Data in Order to Solve Practical Problems. the Research Team Will Run 10 Social Clubs and 10 Data Science Clubs Mentored by Women in Data Science Recruited Through the University of Miami?s Institute for Data Science and Computing. Participants Will Be 250 Middle School-aged Girls Recruited in Miami, FL, and Yolo County, Ca, Through Local and National Girls? Organizations. Youth Will Participate in a Data Science Club and Will Learn Key Data Science Concepts and Skills, Including Data Structures, Storage, Exploration, Analysis, and Visualization. These Concepts Will Be Learned From Working With Their Own Data Collected in Personally Meaningful Ways in Addition to Working With Data Collected by Others in the Same Social Game Eco-system. the Project Will Also Develop Facilitator Materials to Allow Adult Volunteers to Create Game-based Informal Data Science Learning Experiences for Youth in Their Areas. the Project Is Funded by the Advancing Informal Stem Learning (AISL) Program, Which Seeks to Advance New Approaches to, and Evidence-based Understanding of, the Design and Development of Stem Learning in Informal Environments and Is Co-funded by the Innovative Technology Experiences for Students and Teachers (itest), Which Seeks to Engage Underrepresented Students in Technology-rich Learning Environments, Including Skills in Data Literacy, and Increase Students? Knowledge and Interest in Information and Communication Technology (ICT) Careers. Researchers Will Focus on Two Primary Research Questions: 1) Across Gameplay and Club Experiences, in What Ways Do Participants Engage With Data to Pursue Personal or Social Goals? 2) How Do Gameplay and Club Experiences Shape Girls? Perceptions of Data, Data Science, and Their Fit With Data and Data Science? the Project Will Use Design-based Research Methods to Iteratively Design the Game and Social Club Experiences. to Ensure That Uses of Data Feel Personally and Socially Meaningful to Young Girls, the Virtual World?s Goals, Narratives, and Activities Will Be Co-designed With Girls From Groups Underrepresented in Data Science. the Project Will Research Engagement With Game Data in Two Informal, Game-based Learning Scenarios: Organic, Self-directed, Social Play Club, and Structured, Adult-facilitated Data Science Clubs. the Research Will Use a Combination of Quantitative and Qualitative Methods Including Surveys, Focus Groups, Interviews, and Gameplay and Club Observations. Project Evaluation Will Determine How Gameplay and Club Experiences Impact Participants' Attitudes Toward and Interest in Data-rich Futures. the Project Holds the Potential for Broadening Participation and Promoting Interest in Data Science by Blending Game-based Learning With the Rich Social and Adult Mentoring Through Club Participation. the Results Will Be Disseminated Through Conference Presentations, Scholarly Publications, and Social Media. the Game and Facilitator Materials Will Be Designed for Dissemination and Made Freely Available to the Public. This Award Reflects NSF'S Statutory Mission and Has Been Deemed Worthy of Support Through Evaluation Using the Foundation's Intellectual Merit and Broader Impacts Review Criteria.