Concord Consortium Inc

INQUIRYSPACE 2: BROADENING ACCESS TO INTEGRATED SCIENCE PRACTICES

AI ACROSS THE CURRICULUM FOR VIRTUAL SCHOOLS

INTELLIGENT SIMULATION-BASED LEARNING ABOUT NATURAL DISASTERS -WHILE SIMULATIONS ARE POWERFUL TOOLS FOR SCIENTIFIC INQUIRY, MOST STUDENTS NEED SCAFFOLDING TO ENGAGE PRODUCTIVELY IN SIMULATION-BASED INQUIRY. THIS PROJECT WILL DEVELOP AND STUDY AN AUTOMATED FEEDBACK SYSTEM DESIGNED TO SUPPORT MIDDLE SCHOOL STUDENTS' SIMULATION-BASED INQUIRY INTO WILDFIRES, FLOODS, AND HURRICANES. THE SYSTEM, CALLED HAZBOT, WILL LEVERAGE ADVANCED ARTIFICIAL INTELLIGENCE (AI) TECHNOLOGIES--INCLUDING MACHINE LEARNING AND LARGE LANGUAGE MODELS (LLMS)--TO PROVIDE TIMELY, PERSONALIZED FEEDBACK AS STUDENTS INVESTIGATE THE THREE DIFFERENT NATURAL HAZARDS. HAZBOT WILL GUIDE STUDENTS TO COLLECT, ANALYZE, AND INTERPRET DATA FROM SIMULATIONS AND DEVELOP SCIENTIFIC ARGUMENTS BASED ON THAT DATA. HAZBOT WILL ALSO SYNTHESIZE THE AUTOMATED PERFORMANCE DIAGNOSIS AND FEEDBACK INFORMATION PROVIDED TO STUDENTS AND OFFER TEACHERS TARGETED INSTRUCTIONAL SUGGESTIONS TO SUPPORT INDIVIDUAL STUDENTS AND THE WHOLE CLASS. THE PROJECT WILL RESEARCH THE AUTOMATED SCORING METHODS, THE AUTOMATED FEEDBACK SYSTEM, THE COMBINATIONS OF TEACHER FACILITATION AND AUTOMATED FEEDBACK NEEDED TO SUPPORT STUDENTS' SIMULATION-BASED INQUIRY, AND THE IMPACT OF HAZBOT-INTEGRATED WILDFIRE, FLOOD, AND HURRICANE MODULES ON STUDENT LEARNING OUTCOMES. THE MATERIALS GENERATED THROUGH DESIGN AND DEVELOPMENT WILL BE MADE AVAILABLE FOR FREE TO ALL FUTURE STUDENTS, TEACHERS, AND RESEARCHERS BEYOND THE PARTICIPANTS OUTLINED IN THE PROJECT. ISLAND (INTELLIGENT SIMULATION-BASED LEARNING ABOUT NATURAL DISASTERS) IS A FIVE-YEAR LEVEL III DESIGN AND DEVELOPMENT PROJECT AIMED AT ADVANCING MIDDLE SCHOOL STUDENTS' UNDERSTANDING OF WILDFIRES, FLOODS, AND HURRICANES--AND THEIR ABILITY TO CONSTRUCT EVIDENCE-BASED ARGUMENTS ABOUT THESE HAZARDS--THROUGH SIMULATION-BASED INQUIRY SUPPORTED BY AUTOMATED FEEDBACK. THE PROJECT WILL DESIGN A FULLY INTEGRATED AI-ENHANCED TWO-TIER PEDAGOGICAL AGENT TO (1) DIAGNOSE STUDENT PERFORMANCE IN SIMULATION-BASED SCIENTIFIC INQUIRY AND RESPOND IN REAL TIME TO THEIR EVOLVING NEEDS AND (2) SUPPORT TEACHERS BY SYNTHESIZING STUDENT LEARNING IN AN ACTIONABLE TEACHER DASHBOARD. IN THE FIRST THREE YEARS, THE PROJECT WILL EMPLOY DESIGN-BASED RESEARCH TO DEVELOP AND INTEGRATE THE HAZBOT SYSTEM INTO THREE MODULES IN COLLABORATION WITH 9 TEACHERS AND THEIR 900 STUDENTS ACROSS GEOGRAPHICALLY AND DEMOGRAPHICALLY DIVERSE SCHOOLS. THIS PHASE WILL INVESTIGATE HOW HAZBOT'S AUTOMATED SCORING MODELS CAPTURE STUDENTS' SIMULATION-BASED INQUIRY BEHAVIORS AND PERFORMANCE; HOW ITS FEEDBACK SUPPORTS STUDENTS IN COLLECTING, ANALYZING, AND INTERPRETING DATA AND CONSTRUCTING EVIDENCE-BASED ARGUMENTS; AND WHAT COMBINATIONS OF TEACHER FACILITATION AND AUTOMATED FEEDBACK ARE MOST EFFECTIVE. IN THE FINAL TWO YEARS, THE PROJECT WILL CONDUCT THREE RANDOMIZED CONTROLLED TRIALS (RCTS)--ONE FOR EACH HAZARD MODULE (WILDFIRES, FLOODS, AND HURRICANES)--TO MEASURE THE IMPACT OF THE HAZBOT SYSTEM ON STUDENTS' UNDERSTANDING OF NATURAL HAZARDS AND RISK, AS WELL AS THEIR ABILITY TO CONSTRUCT SCIENTIFIC ARGUMENTS. THESE RCTS WILL INVOLVE A NATIONALLY RECRUITED SAMPLE OF 72 TEACHERS AND 3,600 STUDENTS WITH HALF OF THE TEACHERS RANDOMLY ASSIGNED TO IMPLEMENT A HAZBOT-INTEGRATED VERSION OF THE MODULE AND THE OTHER HALF IMPLEMENTING THE SAME MODULE WITHOUT HAZBOT INTEGRATION. THIS PROJECT WILL GENERATE CRITICAL INSIGHTS FOR DESIGNING LLM-BASED FEEDBACK SYSTEMS THAT CAN (1) BE TRAINED TO UPHOLD DISCIPLINARY STANDARDS, (2) SYSTEMATICALLY SCAFFOLD SIMULATION-BASED INQUIRY, AND (3) INTEGRATE MEANINGFULLY WITH TEACHERS WHO BRING VALUABLE CONTEXTUAL INSIGHTS TO CLASSROOM IMPLEMENTATION. THIS PROJECT IS SUPPORTED BY TWO NSF PROGRAMS: THE DISCOVERY RESEARCH PREK-12 (DRK-12) PROGRAM, WHICH AIMS TO SIGNIFICANTLY IMPROVE THE LEARNING AND TEACHING OF SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) FOR PREK-12 STUDENTS AND TEACHERS THROUGH RESEARCH AND DEVELOPMENT OF INNOVATIVE RESOURCES, MODELS, AND TOOLS; AND THE INNOVATIVE TECHNOLOGY EXPERIENCES FOR STUDENTS AND TEACHERS (ITEST) PROGRAM, WHICH SUPPORTS PROJECTS THAT ADVANCE UNDERSTANDING OF THE PRACTICES, PROGRAM ELEMENTS, CONTEXTS, AND PROCESSES THAT FOSTER STUDENTS' KNOWLEDGE OF AND INTEREST IN STEM DISCIPLINES AND INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) CAREERS. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

THE NEXTBIO PROJECT: A STUDENT COLLABORATORY FOR BIOLOGY CYBERLEARNING

COMMON ONLINE DATA ANALYSIS PLATFORM (CODAP)

LEVERAGING DYNAMICALLY LINKED REPRESENTATIONS IN A SEMI-STRUCTURED WORKSPACE TO CULTIVATE MATHEMATICAL MODELING COMPETENCIES AMONG SECONDARY STUDENTS (M2STUDIO)

GUIDING UNDERSTANDING VIA INFORMATION FROM DIGITAL ENVIRONMENTS (GUIDE)

LOGGING OPPORTUNITIES IN ONLINE PROGRAMS FOR SCIENCE (LOOPS): STUDENT AND TEACHER LEARNING

PRECIPITATING CHANGE IN ALASKAN AND HAWAIIAN SCHOOLS: MODELING MITIGATION OF COASTAL EROSION

GEOHAZARD: MODELING NATURAL HAZARDS AND ASSESSING RISKS

DEVELOPING, RESEARCHING, AND SCALING UP SMARTGRAPHS

GEOLOGICAL MODELS FOR EXPLORATIONS OF DYNAMIC EARTH (GEODE): INTEGRATING THE POWER OF GEODYNAMIC MODELS IN MIDDLE SCHOOL EARTH SCIENCE CURRICULUM

INTEGRATED SCIENCE PRACTICES ENHANCED BY COMPUTATIONAL THINKING (INSPECT)

SENSING SCIENCE THROUGH MODELING: DEVELOPING KINDERGARTEN STUDENTS' UNDERSTANDING OF MATTER AND ITS CHANGES

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.

INTEGRATING METEOROLOGY, MATHEMATICS, AND COMPUTATIONAL THINKING: RESEARCH ON STUDENTS' LEARNING AND USE OF DATA, MODELING, AND PREDICTION PRACTICES

ITEST SCALE-UP: INNOVATIVE TECHNOLOGY FOR SCIENCE INQUIRY SCALE-UP PROJECT (ITSI-SU)

GEOLOGICAL CONSTRUCTION OF ROCK ARRANGEMENTS FROM TECTONICS: SYSTEMS MODELING ACROSS SCALES

HIGH ADVENTURE SCIENCE: EARTHS SYSTEMS AND SUSTAINABILITY

ENHANCING ENGINEERING EDUCATION WITH COMPUTATIONAL THINKING

INDP: INQUIRYSPACE: TECHNOLOGIES IN SUPPORT OF STUDENT EXPERIMENTATION

ADVANCING PUBLIC LITERACY OF UNCERTAINTY IN SCIENCE IN THE CONTEXT OF SIMULATION-BASED NORTH ATLANTIC STORM FORECASTING -NORTH ATLANTIC STORMS--SUCH AS HURRICANES AND NOR'EASTERS--DISRUPT LIVES AND IMPOSE SIGNIFICANT BURDENS ON COASTAL COMMUNITIES. RESIDENTS IN THESE REGIONS RELY ON STORM FORECASTS TO ASSESS RISK AND DECIDE ON PROTECTIVE ACTIONS. TO INFORM THE PUBLIC, NEWS AND SOCIAL MEDIA OUTLETS FREQUENTLY USE SCIENTIFIC VISUALIZATIONS--SUCH AS CONES OF UNCERTAINTY AND SPAGHETTI PLOTS--TO COMMUNICATE STORM TRAJECTORIES AND POTENTIAL IMPACTS. HOWEVER, THESE VISUALIZATIONS ARE DIFFICULT FOR MOST ADULTS TO INTERPRET, LARGELY BECAUSE THEY DO NOT SPECIFY THE EXACT TIME AND LOCATION THE STORM IS EXPECTED TO REACH IN THE FUTURE. THIS PROJECT ADDRESSES THE NEED TO IMPROVE PUBLIC UNDERSTANDING OF THE UNCERTAINTIES EMBEDDED IN STORM FORECASTS AND VISUALIZATIONS BY LEVERAGING ONLINE SIMULATIONS. THE PROJECT TEAM PLANS TO BUILD THE NORTH ATLANTIC STORM (NAS) EXPLORER THAT WOULD ALLOW PARTICIPANTS TO USE INTERACTIVE, WEB-BASED SIMULATION TO EXPLORE FUTURE PATHS OF A STORM IN VARIOUS SCENARIOS BASED ON THE STORM'S REAL-TIME DATA. THIS PROJECT SEEKS TO ENHANCE PUBLIC LITERACY IN NORTH ATLANTIC STORM FORECASTING THROUGH A SIMULATION-BASED EXPERIENCE THAT REPLICATES KEY ASPECTS OF THE SCIENTISTS' STORM MODELING AND FORECASTING PRACTICES. ADULT PARTICIPANTS WILL BE ENGAGED ACROSS THREE RESEARCH STUDIES. THE FIRST STUDY FOCUSES ON DEVELOPING SURVEY INSTRUMENTS TO MEASURE UNCERTAINTY LITERACY IN ATLANTIC FORECASTING (ULAF), TARGETING THREE CONSTRUCTS: (1) INTERPRETING PROBABILISTIC STORM VISUALIZATIONS (E.G., CONES OF UNCERTAINTY AND SPAGHETTI PLOTS); (2) ATTRIBUTING UNCERTAINTIES IN THESE VISUALIZATIONS TO THE SIMULATION-BASED FORECASTING PROCESS; AND (3) PERCEIVING THE RISKS CONVEYED BY THESE VISUALIZATIONS. THE SECOND STUDY, USING DESIGN-BASED RESEARCH, WILL TEST THE PROTOTYPE NORTH ATLANTIC STORM (NAS) EXPLORER SIMULATION. THE THIRD STUDY IN YEAR 3 WILL EVALUATE THE IMPACT OF THE SIMULATION-BASED FORECASTING EXPERIENCE ON ULAF THROUGH A RANDOMIZED CONTROL TRIAL WITH 300 PARTICIPANTS. ACROSS THESE STUDIES, THE PROJECT WILL GENERATE NEW KNOWLEDGE ABOUT PUBLIC UNCERTAINTY LITERACY, SIMULATION DESIGN, AND SIMULATION-BASED FORECASTING EXPERIENCES--INSIGHTS THAT CAN INFORM SCIENCE COMMUNICATION AND PUBLIC EDUCATION FOR A VARIETY OF STORM TYPES AND NATURAL HAZARDS. PROJECT RESULTS WILL BE DISSEMINATED THROUGH CONFERENCE PRESENTATIONS, PEER-REVIEWED JOURNAL ARTICLES, THE PROJECT WEBSITE, AND SOCIAL MEDIA PLATFORMS. THIS INTEGRATING RESEARCH AND PRACTICE 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. THIS INCLUDES PROVIDING EVERYONE MULTIPLE PATHWAYS FOR ACCESSING AND ENGAGING IN STEM LEARNING EXPERIENCES. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

R&D: EVOLUTION READINESS: A MODELING APPROACH

INTEGRATING TRANSDISCIPLINARY AND COMPUTATIONAL APPROACHES IN THE EARTH SCIENCE CURRICULUM USING DATA VISUALIZATIONS, SCIENTIFIC ARGUMENTATION, AND EXPLORATION OF GEOHAZARDS

SCAFFOLDING STUDENTS' INTERDISCIPLINARY COMPUTATIONAL AND COMPUTATIONAL THINKING APPROACHES FOR ENGAGING IN MULTILEVEL ENVIRONMENTAL SYSTEMS MODELING

COMPUTING WITH R FOR MATHEMATICAL MODELING

COLLABORATIVE RESEARCH: SUPPORTING SECONDARY STUDENTS IN BUILDING EXTERNAL MODELS

COLLABORATIVE RESEARCH: SMARTCAD: GUIDING ENGINEERING DESIGN WITH SCIENCE SIMULATIONS

NARRATIVE MODELING WITH STORYQ: INTEGRATING MATHEMATICS, LANGUAGE ARTS, AND COMPUTING TO CREATE PATHWAYS TO ARTIFICIAL INTELLIGENCE CAREERS

COLLABORATIVE RESEARCH: ENHANCING MIDDLE GRADES STUDENTS' CAPACITY TO DEVELOP AND COMMUNICATE THEIR MATHEMATICAL UNDERSTANDING OF BIG IDEAS USING DIG

DATA IN SPACE AND TIME: SUPPORTING LEARNERS IN UNDERSTANDING AND ANALYZING SPATIOTEMPORAL DATA -MANY OF SOCIETY?S BIGGEST DILEMMAS AND GRANDEST OPPORTUNITIES INVOLVE EXTENSIVE INTERPRETATION OF COMPLEX DATA THAT VARY ACROSS BOTH SPACE AND TIME. SUCH SPATIO-TEMPORAL (ST) DATA STAND AT THE FOREFRONT OF THE MOST CRITICAL DECISIONS ACROSS PRACTICALLY ALL SECTORS OF SOCIETY, FROM MAKING SENSE OF CHANGES IN THE CLIMATE AND RESPONSES TO THE CAUSES OF SOCIOECONOMIC DIFFERENCES TO THE UNDERSTANDING OF GLOBAL ECONOMIC CHANGES. OVER THE PAST FEW DECADES, ANALYZING AND INTERPRETING ST DATA HAS MOVED FROM THE PURVIEW OF NICHE DOMAINS TO A NECESSARY SKILL FOR CITIZENS AND WORKERS ALIKE. HENCE, THE NEED TO PREPARE LEARNERS TO WORK WITH SUCH DATA HAS GROWN TO THE SAME LEVEL OF URGENCY. SKILLS AT ANALYZING AND INTERPRETING ST DATA CANNOT BE LEFT TO BEGIN IN UNDERGRADUATE STUDY OR LEARNED DURING WORKPLACE TRAINING. HOWEVER, DESPITE THE GROWING IMPORTANCE OF SUCH DATA IN INDUSTRY AND SOCIETY, THE STEM EDUCATION FIELD'S UNDERSTANDING OF HOW LEARNERS COME TO MAKE SENSE OF ST DATA REMAINS SEVERELY LIMITED. FORTUNATELY, EMERGING RESEARCH AND TECHNIQUES OFFER PROMISE FOR IMPROVING THIS UNDERSTANDING. DRAWING UPON EXISTING RESEARCH INTO VISUAL AND SPATIAL UNDERSTANDING, COGNITIVE INTERPRETATION OF TIME, AND TECHNOLOGY-BASED TOOLS AND TECHNIQUES, THIS PROJECT WILL IDENTIFY HOW LEARNERS APPROACH AND MAKE SENSE OF ST DATA. IN DOING SO, THE PROJECT WILL PRODUCE A GUIDING FRAMEWORK OUTLINING FRUITFUL DIRECTIONS FOR FUTURE RESEARCH AND ACTIONABLE PRINCIPLES FOR THE DEVELOPMENT OF CURRICULA AND INSTRUCTIONAL MATERIALS THAT AIM TO ENGAGE LEARNERS IN EXPLORING ST DATA. THREE OBJECTIVES GUIDE THIS PROJECT AS IT AIMS TO UNDERSTAND HOW SECONDARY SCHOOL LEARNERS MAKE SENSE OF SPATIO-TEMPORAL DATA. FIRST IS TO COMPILE AN INVENTORY OF EXISTING KNOWLEDGE ABOUT LEARNERS? UNDERSTANDING OF ST DATA AND ANALYZING STUDENTS? APPROACHES TO ST DATA. SECOND IS TO DEVELOP AND TEST SUPPORTS AND AFFORDANCES IN AN ITERATIVE PROCESS THAT ADDRESSES IDENTIFIED CHALLENGES AND OPPORTUNITIES. THIRD, AND FINALLY, IS TO DEFINE AND DISSEMINATE A FRAMEWORK IDENTIFYING COGNITIVE CHALLENGES AND RELATED SUPPORTS FOR LEARNING WITH AND ABOUT ST DATA. THE PROJECT WILL CONDUCT USE-INSPIRED BASIC RESEARCH TO EXAMINE LEARNERS? APPROACHES AND SENSE-MAKING VIA THREE RELATED LINES OF INVESTIGATION: 1) WHAT STRATEGIES LEARNERS USE TO MAKE SENSE OF THE DATA AND WHAT CHALLENGES DIFFERENT DATA TYPES POSE? 2) HOW LEARNERS COME TO IDENTIFY AND UNDERSTAND PATTERNS AND RELATIONSHIPS WITHIN SUCH DATA AND WHAT CHALLENGES DIFFERENT PATTERN TYPES POSE? 3) WHAT UNDERSTANDINGS DO LEARNERS CONSTRUCT WHEN ENGAGING WITH ST DATA AND IN WHAT WAYS TECHNOLOGY-BASED AFFORDANCES CAN HELP SUPPORT LEARNERS IN ANALYZING OR CONSTRUCTING UNDERSTANDING FROM SUCH DATA? ADOPTING A DESIGN-BASED RESEARCH APPROACH EMPLOYING A COMBINATION OF THINK-ALOUD PROTOCOLS, RETROSPECTIVE INTERVIEWS, AND DATA SKILLS ASSESSMENT, THE PROJECT WILL CREATE AND DISSEMINATE A FRAMEWORK THAT IDENTIFIES STRUGGLES FACED BY LEARNERS CONFRONTING VARYING TYPES OF ST DATASETS, HIGHLIGHTS USER INTERFACE AFFORDANCES AND DATA VISUALIZATION APPROACHES WITH POTENTIAL FOR ADDRESSING THESE STRUGGLES, AND DRAWS ACTIONABLE CONNECTIONS BETWEEN THE TWO. THIS PROJECT IS SUPPORTED BY NSF'S EHR CORE RESEARCH (ECR) PROGRAM. THE ECR PROGRAM EMPHASIZES FUNDAMENTAL STEM EDUCATION RESEARCH THAT GENERATES FOUNDATIONAL KNOWLEDGE IN THE FIELD. INVESTMENTS ARE MADE IN CRITICAL AREAS THAT ARE ESSENTIAL, BROAD AND ENDURING: STEM LEARNING AND STEM LEARNING ENVIRONMENTS, BROADENING PARTICIPATION IN STEM, AND STEM WORKFORCE DEVELOPMENT. THE PROGRAM SUPPORTS THE ACCUMULATION OF ROBUST EVIDENCE TO INFORM EFFORTS TO UNDERSTAND, BUILD THEORY TO EXPLAIN, AND SUGGEST INTERVENTION AND INNOVATIONS TO ADDRESS PERSISTENT CHALLENGES IN EDUCATION. 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.

COLLABORATIVE RESEARCH: CONNECTED BIOLOGY: THREE-DIMENSIONAL LEARNING FROM MOLECULES TO POPULATIONS

SUPPORTING REASONING WITH MULTIDIMENSIONAL DATASETS: LEVERAGING STUDENT INTUITIONS THROUGH COLLABORATIVE DATA PRODUCTION -IT IS INCREASINGLY VITAL THAT PEOPLE BE ABLE TO MAKE SENSE OF SCIENTIFIC DATA AND EXTRACT INFORMATION FROM PUBLIC DATASETS IN ORDER TO INFORM THEIR DECISIONS ABOUT EVERYTHING FROM BALLOT INITIATIVES ON CLIMATE POLICY TO PERSONAL CHOICES ABOUT VACCINES. THE PROJECT HAS A LONG-TERM GOAL OF BROADENING PARTICIPATION IN STEM BY MAKING DATA LITERACY ATTAINABLE BY MORE STUDENTS. THE PROJECT WILL DEVELOP INSTRUCTIONAL DESIGN SUPPORTS FOR HIGH SCHOOL STUDENTS THAT BUILD ON THEIR NOVICE INTUITIONS FOR VISUALIZING AND INTERACTING WITH COMPLEX DATASETS. THE PROJECT WILL ALSO DEVELOP DESIGN PRINCIPLES TO GUIDE TECHNOLOGY DEVELOPERS, CURRICULAR DEVELOPERS, AND RESEARCHERS IN CREATING ENVIRONMENTS MORE CONDUCIVE TO PROMOTING DATA LITERACY FOR ALL LEARNERS, INCLUDING THOSE WHO ARE NOT CONFIDENT MATH LEARNERS AND THOSE INTERESTED IN FURTHER WORK IN STEM. THESE RESULTS WILL INFORM FUTURE EFFORTS AIMED AT HELPING STUDENTS BETTER UNDERSTAND HOW TO INTERACT WITH DATA. THE PROJECT WILL ALSO PRODUCE WORKING EXAMPLES OF OPEN-SOURCE SOFTWARE AND TECHNOLOGICAL SUPPORTS IN CODAP (COMMON ONLINE DATA ANALYSIS PLATFORM) BASED ON THE DESIGN PRINCIPLES IT DEVELOPS. PROJECT RESEARCH WILL EXPLORE TWO BROAD CONJECTURES ABOUT HOW TECHNOLOGICAL AND INSTRUCTIONAL SUPPORTS FOR INTERROGATING MULTIDIMENSIONAL DATA CAN IMPROVE STUDENTS? ABILITIES TO MAKE SENSE OF THEIR WORLD AND EMPOWER THEM TO USE DATA PERSONALLY AND PROFESSIONALLY. FIRST, THE PROJECT ENVISIONS THAT PROVIDING STUDENTS WITH RESOURCES TO REPRESENT AND VISUALIZE MULTIDIMENSIONAL DATA IN WAYS THAT BUILD ON NOVICE INTUITIONS WILL ALLOW THEM MORE AGENCY IN TRANSFORMING DATA STRUCTURES TO ANSWER THEIR OWN QUESTIONS. SECOND, THE PROJECT POSITS THAT WORKING COLLABORATIVELY TO BUILD A MULTIDIMENSIONAL DATASET CAN HELP STUDENTS DEVELOP RICH ASSOCIATIONS, WHICH CONTRIBUTE TO ROBUST AND FLEXIBLE MENTAL MODELS OF DATA STRUCTURE THAT STUDENTS CAN THEN APPLY TO DATASETS MORE BROADLY. RESEARCH METHODS INCLUDE THINK-ALOUD INTERVIEWS AND INSTRUCTIONAL SESSIONS WITH SMALL GROUPS OF STUDENTS TO EXPLORE THEIR INTUITIVE NOTIONS ABOUT DATA STRUCTURE AND HOW THESE INTUITIVE NOTIONS CAN BE LEVERAGED TO OFFER SUPPORT FOR VISUALIZING AND TRANSFORMING DATA. PROJECT RESEARCH WILL RESULT IN A) THEORETICAL INSIGHTS INTO HOW NOVICES INTUITIVELY REPRESENT AND INTERACT WITH MULTIDIMENSIONAL DATA; B) DESIGN PRINCIPLES FOR CONSTRUCTING USER INTERFACES AND EDUCATIONAL EXPERIENCES THAT CAN SUPPORT STUDENT UNDERSTANDING AND USE OF MULTIDIMENSIONAL DATASETS; AND C) TESTED EXAMPLES OF SOFTWARE USER INTERFACES AND INSTRUCTIONAL ACTIVITIES THAT EXEMPLIFY THE DESIGN PRINCIPLES. THIS PROJECT IS SUPPORTED BY NSF'S EHR CORE RESEARCH (ECR) PROGRAM. THE ECR PROGRAM EMPHASIZES FUNDAMENTAL STEM EDUCATION RESEARCH THAT GENERATES FOUNDATIONAL KNOWLEDGE IN THE FIELD. INVESTMENTS ARE MADE IN CRITICAL AREAS THAT ARE ESSENTIAL, BROAD AND ENDURING: STEM LEARNING AND STEM LEARNING ENVIRONMENTS, BROADENING PARTICIPATION IN STEM, AND STEM WORKFORCE DEVELOPMENT. THE PROGRAM SUPPORTS THE ACCUMULATION OF ROBUST EVIDENCE TO INFORM EFFORTS TO UNDERSTAND, BUILD THEORY TO EXPLAIN, AND SUGGEST INTERVENTION AND INNOVATIONS TO ADDRESS PERSISTENT. 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.

DIP: DATA SCIENCE GAMES - STUDENT IMMERSION IN DATA SCIENCE USING GAMES FOR LEARNING IN THE COMMON ONLINE DATA ANALYSIS PLATFORM

YOUTHQUAKE: ENGAGING URBAN STUDENTS IN A COMPUTATIONAL GEOLOGY EXPERIENCE TO FORECAST EARTHQUAKE HAZARDS AND MANAGE RISKS FOR THEIR COMMUNITY -THIS PROJECT WILL CONTRIBUTE TO THE EARTH SCIENCE EDUCATION COMMUNITY'S UNDERSTANDING OF HOW ENGAGING STUDENTS WITH COMPUTATIONAL ACTIVITIES AND PRIORITIZING THEIR KNOWLEDGE, PERSONAL EXPERIENCES, AND COMMUNITY VALUES CAN BROADEN THE PARTICIPATION OF DIVERSE STUDENTS IN GEOSCIENCE. THE YOUTHQUAKE PROJECT WILL ENGAGE HISPANIC AND AFRICAN AMERICAN MIDDLE SCHOOL STUDENTS IN STOCKTON, CALIFORNIA, IN AUTHENTIC INVESTIGATIONS OF THEIR COMMUNITY'S EARTHQUAKE HAZARDS, RISKS, AND PREPAREDNESS USING PRACTICES OF PROFESSIONAL GEOSCIENTISTS. THROUGH A PARTNERSHIP AMONG TEACHERS, GEOSCIENTISTS, EDUCATIONAL RESEARCHERS, TECHNOLOGY AND CURRICULUM DEVELOPERS, AND A WORKFORCE AND DIVERSITY SPECIALIST, THE PROJECT WILL CO-DESIGN A FOUR-WEEK COMPUTATIONAL GEOSCIENCE CURRICULUM. STUDENTS WILL (1) EXPLORE THEIR COMMUNITY'S LIKELIHOOD OF EXPERIENCING A DAMAGING EARTHQUAKE, (2) DETERMINE THEIR COMMUNITY'S CURRENT POLICIES AND RESOURCES FOR EARTHQUAKE PREPAREDNESS, (3) INVESTIGATE WHAT CAUSES EARTHQUAKES BASED ON REAL-WORLD DATA AND COMPUTATIONAL MODELS OF LAND MOTION ALONG FAULTS, AND (4) CREATE EARTHQUAKE HAZARD MAPS USING AN INTUITIVE BLOCK-BASED PROGRAMMING ENVIRONMENT THAT IMPORTS SEISMIC DATA AND GENERATES MAP-BASED VISUALIZATION OUTPUTS. THE PROJECT PLANS TO WORK WITH 10 MIDDLE SCHOOL TEACHERS AND APPROXIMATELY 1,120 MIDDLE SCHOOL STUDENTS. THE FINDINGS WILL GENERATE EVIDENCE-BASED TEACHING STRATEGIES THAT PROMOTE STUDENTS' UNDERSTANDING OF EARTHQUAKE HAZARDS, RISK, AND MITIGATION AS WELL AS THEIR COMPUTATIONAL GEOSCIENCE IDENTITIES AND CAREER AWARENESS. THE MATERIALS GENERATED THROUGH DESIGN AND DEVELOPMENT WILL BE MADE AVAILABLE FOR FREE TO ALL FUTURE LEARNERS, TEACHERS, AND RESEARCHERS BEYOND THE PARTICIPANTS OUTLINED IN THE PROJECT. THE GOAL OF THE YOUTHQUAKE PROJECT IS TO ENGAGE HISPANIC AND AFRICAN AMERICAN MIDDLE SCHOOL STUDENTS IN STOCKTON, CALIFORNIA, IN AUTHENTIC COMPUTATIONAL GEOSCIENCE INVESTIGATIONS OF EARTHQUAKE HAZARDS IN ORDER TO INCREASE THEIR INTEREST IN, AND IDENTITY WITH, COMPUTATIONAL GEOSCIENCE CAREERS. A MULTIDISCIPLINARY PARTNERSHIP AMONG YOUTHQUAKE TEACHERS, GEOSCIENTISTS, EDUCATIONAL RESEARCHERS, TECHNOLOGY AND CURRICULUM DEVELOPERS, AND A WORKFORCE AND DIVERSITY SPECIALIST WILL CO-DESIGN A FOUR-WEEK COMPUTATIONAL GEOSCIENCE CURRICULUM. THE CURRICULUM ACTIVITIES WILL BE SITUATED IN THE LOCAL COMMUNITY CONTEXT SO STUDENTS CAN: 1) EXPLORE THEIR NEIGHBORHOOD'S LIKELIHOOD OF EXPERIENCING A DAMAGING EARTHQUAKE AND RELATED PREPAREDNESS, 2) INVESTIGATE GPS DATA AND USE COMPUTATIONAL MODELS OF LAND MOTION ALONG THE FAULTS AROUND THEIR COMMUNITY, AND 3) CREATE COMPUTATIONAL VISUALIZATIONS OF EARTHQUAKE HAZARD MAPS. TWO CYCLES OF DESIGN?BASED RESEARCH WILL BE CONDUCTED TO DEVELOP THE YOUTHQUAKE CURRICULUM AND ASSESSMENT MATERIALS. A MIXED-METHODS RESEARCH DESIGN WILL BE APPLIED TO ANALYZE PRE-POST TESTS, SURVEYS, EMBEDDED ASSESSMENTS, AND WHOLE CLASS AND STUDENT VIDEOS. PROJECT RESEARCH WILL GENERATE KNOWLEDGE ABOUT CURRICULUM DESIGN AND TEACHING STRATEGIES THAT PROMOTE STUDENTS' ENGAGEMENT WITH COMPUTATION-MEDIATED SCIENCE PRACTICES AS WELL AS COMPUTATIONAL GEOSCIENCE IDENTITY AND CAREER INTERESTS. SEVERAL EQUITY STRATEGIES WILL BE INVESTIGATED, INCLUDING: (1) USING CONTEXTUAL SCAFFOLDS TO HELP STUDENTS BRIDGE REAL-WORLD PROBLEMS WITH THEIR DIVERSE FORMS OF SCIENCE KNOWLEDGE AND EXPERIENCES, (2) ENGAGING STUDENTS IN AUTHENTIC INVESTIGATIONS AND PRACTICES OF CAREER PROFESSIONALS, (3) BUILDING ON STUDENTS' CULTURAL ASSETS AND STRENGTHS DERIVED BY BELONGING TO DIFFERENT COMMUNITIES, AND (4) EMPOWERING STUDENTS TO BECOME EPISTEMIC AGENTS IN SHAPING THEIR KNOWLEDGE AND PRACTICE. THE OUTCOMES OF THE PROJECT WILL INCLUDE EVIDENCE-BASED KNOWLEDGE AND AN EXEMPLARY STUDENT TECHNOLOGY EXPERIENCE THAT ADDRESSES THESE EQUITY STRATEGIES. THIS PROJECT IS FUNDED BY THE INNOVATIVE TECHNOLOGY EXPERIENCES FOR STUDENTS AND TEACHERS (ITEST) PROGRAM, WHICH SUPPORTS PROJECTS THAT BUILD UNDERSTANDINGS OF PRACTICES, PROGRAM ELEMENTS, CONTEXTS AND PROCESSES CONTRIBUTING TO INCREASING STUDENTS' KNOWLEDGE AND INTEREST IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) AND INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) CAREERS. THIS PROJECT IS ALSO FUNDED BY THE DISCOVERY RESEARCH PREK-12 PROGRAM (DRK-12), WHICH SEEKS TO SIGNIFICANTLY ENHANCE THE LEARNING AND TEACHING OF STEM BY PREK-12 STUDENTS AND TEACHERS, THROUGH RESEARCH AND DEVELOPMENT OF INNOVATIVE RESOURCES, MODELS AND TOOLS. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

RHODE ISLAND INFORMATION TECHNOLOGY EXPERIENCES FOR STUDENTS AND TEACHERS (RI-ITEST)

WATERSHED AWARENESS USING TECHNOLOGY AND ENVIRONMENTAL RESEARCH FOR SUSTAINABILITY (WATERS)

GENICONNECT: GAME-BASED LEARNING, MENTORING, AND LABORATORY EXPERIENCES - A MODEL FOR INDUSTRY-AFTERSCHOOL PARTNERSHIPS

STRATEGIES: WATER SCIENCE: SUPPORTING COLLABORATIVE INQUIRY, ENGINEERING, AND CAREER EXPLORATION WITH WATER

NEXT STEP LEARNING: BRIDGING SCIENCE EDUCATION AND CLEANTECH CAREERS WITH INNOVATIVE TECHNOLOGIES

COLLABORATIVE RESEARCH: MODEL MY WATERSHED - TEACHING ENVIRONMENTAL SUSTAINABILITY

COLLABORATIVE RESEARCH: LARGE-SCALE RESEARCH ON ENGINEERING DESIGN BASED ON BIG LEARNER DATA LOGGED BY A CAD TOOL

THE PELEHONUAMEA PROJECT: CONNECTING INDIGENOUS HAWAIIAN HISTORY AND COMPUTATIONAL GEOSCIENCE IN TEACHING VOLCANISM -COMPUTATIONAL GEOSCIENCE IS USED FOR VOLCANIC RISK ASSESSMENT AND HAZARD MITIGATION FOR HAWAIIANS. HOWEVER, FEW STUDENTS IN HAWAI?I HAVE THE OPPORTUNITY TO USE COMPUTER SCIENCE AND COMPUTATIONAL THINKING FOR AUTHENTIC SCIENTIFIC INQUIRY IN GEOSCIENCE. TO ADDRESS THE NEED FOR INCREASED LEARNING OPPORTUNITIES THAT ENGAGE INDIGENOUS HAWAIIAN STUDENTS IN A LOCALLY RELEVANT CURRICULUM THAT MEETS BOTH STATE SCIENCE AND COMPUTER SCIENCE, THE PROJECT BRINGS TOGETHER STEM EDUCATION RESEARCHERS, MIDDLE SCHOOL TEACHERS, STUDENTS, COMMUNITY MEMBERS, AND GEOSCIENTISTS IN A RESEARCH-PRACTICE PARTNERSHIP TO CO-DESIGN A TECHNOLOGY-RICH INTEGRATED GEOSCIENCE AND COMPUTER SCIENCE CURRICULUM FOCUSED ON VOLCANIC RISKS AND HAZARDS. A UNIQUE ASPECT OF THIS PROJECT IS THAT IT LEVERAGES AND AMPLIFIES THE VOICES OF INDIGENOUS HAWAIIAN MIDDLE SCHOOL STUDENTS AND THEIR FAMILIES IN THE CURRICULUM CO-DESIGN PROCESS, THUS CONTRIBUTING TO A SENSE OF OWNERSHIP OF AND INVESTMENT IN STEM LEARNING. SPECIFICALLY, THE PROJECT INVOLVES CO-DESIGNING A CURRICULUM MODULE THAT INTEGRATES HAWAIIAN ORAL HISTORIES AND CURRENT LIVED EXPERIENCES OF VOLCANIC ERUPTIONS WITH WESTERN SCIENTIFIC KNOWLEDGE ABOUT VOLCANOLOGY. MIDDLE SCHOOL STUDENTS WILL USE BLOCK CODING TO CONDUCT SIMULATION-BASED INVESTIGATIONS ABOUT VOLCANIC HAZARDS AND RISKS. THE PROJECT WILL RESEARCH HOW EXPERIENCING A CULTURALLY- AND GEOGRAPHICALLY-RELEVANT INTEGRATED GEOSCIENCE AND COMPUTER SCIENCE CURRICULUM MODULE AFFECTS STUDENTS? ATTITUDE TOWARDS COMPUTER SCIENCE AND COMPUTATIONAL THINKING, AND TO WHAT EXTENT STUDENTS BUILD COMPUTER SCIENCE AND GEOSCIENCE KNOWLEDGE. THE PROJECT GOAL IS TO BROADEN INDIGENOUS HAWAIIAN STUDENTS? SENSE OF AGENCY AND EDUCATIONAL RELEVANCE IN COMPUTING AND GEOSCIENCE TO BETTER PREPARE THEM FOR DIVERSE JOB OPPORTUNITIES IN STEM FIELDS. THIS PROJECT EXPANDS ON AN EXISTING RESEARCH-PRACTICE PARTNERSHIP TO INCLUDE MIDDLE SCHOOL STUDENTS IN THE CO-DESIGN OF A TECHNOLOGY-RICH INTEGRATED GEOSCIENCE AND COMPUTER SCIENCE CURRICULUM MODULE FOCUSED ON VOLCANIC RISKS AND HAZARDS. THE CO-DESIGN EFFORT ENGAGES ALL MEMBERS OF THE PARTNERSHIP IN CURRICULUM DESIGN, AND HAWAIIAN STUDENTS? ETHNOGRAPHIC STUDIES ARE AT THE CENTER OF THIS EFFORT. THROUGH A VARIETY OF CO-DESIGN ACTIVITIES, STUDENTS WILL SHARE ETHNOGRAPHIC STORIES CAPTURING HAWAIIAN HISTORICAL AND LIVED KNOWLEDGE ABOUT VOLCANIC ERUPTIONS, AND THE PROJECT TEAM WILL ENGAGE WITH STUDENTS TO ALIGN THEIR ETHNOGRAPHIC STORIES WITH THE COMPUTATIONAL GEOSCIENCE ACTIVITIES PLANNED. THE STUDENTS? STORIES WILL CONTEXTUALIZE THE COMPUTER SCIENCE, COMPUTATIONAL THINKING, AND GEOSCIENCE LEARNING. THE PROJECT BUILDS UPON PREVIOUSLY DEVELOPED SOFTWARE TO CREATE A COMPUTATIONAL MODEL THAT WILL ALLOW STUDENTS TO USE VISUAL BLOCK-BASED CODING TO MODEL LAVA ERUPTIONS FROM THE MAUNA LOA VOLCANO. STUDENTS WILL USE COMPUTATIONAL THINKING SKILLS AND COMPUTER SCIENCE PRACTICES TO MODEL AND EXPLORE THE ENVIRONMENTAL VARIABLES THAT INFLUENCE THE VOLCANIC LAVA FLOW SYSTEM, DEFINE THE RELATIONSHIPS AMONG PERTINENT ENVIRONMENTAL FACTORS, CREATE VISUALIZATIONS OF LAVA FLOW FROM A VOLCANIC VENT, AND ANALYZE THE DATA PRODUCED BY THE MODEL. THROUGH TWO CYCLES OF DESIGN-BASED IMPLEMENTATION RESEARCH, THE PROJECT EXPLORES HOW THE CO-DESIGN PROCESS SUPPORTS STUDENTS? SENSE OF AGENCY AND EDUCATIONAL RELEVANCE, HOW A CULTURALLY- AND GEOGRAPHICALLY-RELEVANT INTEGRATED COMPUTER SCIENCE GEOSCIENCE CURRICULUM MODULE CAN AFFECT STUDENTS? ATTITUDE TOWARDS COMPUTER SCIENCE AND COMPUTATIONAL THINKING, AND TO WHAT EXTENT STUDENTS BUILD COMPUTER SCIENCE, COMPUTATIONAL THINKING, AND GEOSCIENCE KNOWLEDGE. SITUATED IN THE DESIGN-BASED IMPLEMENTATION RESEARCH APPROACH, THE PROJECT EMPLOYS CULTURAL-HISTORICAL ACTIVITY THEORY AND USES A MIXED METHODS APPROACH TO DATA COLLECTION AND ANALYSIS, INCLUDING OBSERVATIONS, INTERVIEWS, A COMPUTATIONAL GEOSCIENCE REASONING MEASURE, STUDENT LOG DATA INCLUDING THEIR USE OF BLOCK CODING, AND INSTRUMENTS TO ASSESS HOW STUDENTS PERCEIVE PERSONAL, CONTEXTUAL, AND FUTURE RELEVANCE OF COMPUTATIONAL GEOSCIENCE CONTENT. THIS PROJECT IS FUNDED THROUGH THE COMPUTER SCIENCE FOR ALL: RESEARCH AND RPPS PROGRAM. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

CONTEXTUALIZING DATA EDUCATION VIA PROJECT-BASED LEARNING -THIS DATAPBL PROJECT IS WORKING TO DEVELOP, IMPLEMENT, AND RESEARCH THE INTRODUCTION OF DATA EXPERIENCES AND PRACTICES INTO A SERIES OF INTERDISCIPLINARY, MIDDLE SCHOOL PROJECT-BASED LEARNING MODULES. DATA FILLS ALL ASPECTS OF OUR LIVES, AND DATA SCIENCE HAS BECOME A VITAL INTERDISCIPLINARY ENDEAVOR. TO SUCCEED IN THE FUTURE, STUDENTS MUST SEE DATA AS A TOOL THEY CAN WIELD TO ADDRESS RELEVANT ISSUES ACROSS DISCIPLINES. STUDENTS NEED OPPORTUNITIES TO APPLY DATA SCIENCE PRACTICES TO APPROPRIATELY REALISTIC DATASETS FROM CONTEXTS MEANINGFUL TO THEM, AND TO HAVE OPPORTUNITIES TO DEMONSTRATE THEIR SKILLS AND KNOWLEDGE AUTHENTICALLY. PROJECT-BASED LEARNING (PBL) APPROACHES HAVE CULTIVATED A GROWING BASE OF CLASSROOMS DEDICATED TO SUPPORTING SUCH SITUATIONS VIA AUTHENTIC, INTERDISCIPLINARY LEARNING EXPERIENCES. CO-DESIGNING THESE MODULES WITH MIDDLE SCHOOL TEACHERS AND PILOTING THEM IN URBAN, LOW-INCOME SCHOOLS IN NEW YORK CITY AND CHICAGO, THIS PROJECT EXAMINES HOW INTERDISCIPLINARY DATA EDUCATION CAN PROVIDE OPPORTUNITIES FOR STUDENTS TO TAKE MORE CONTROL OF THEIR OWN LEARNING AND DEVELOP POSITIVE IDENTITIES RELATED TO DATA, THROUGH INTEGRATION WITH SOCIAL STUDIES AND SCIENCE TOPICS. CURRICULUM MODULES AND TEACHING RESOURCES PRODUCED BY THE PROJECT SERVE AS GUIDES FOR SUBSEQUENT EFFORTS AT INTEGRATING DATA SCIENCE CONCEPTS INTO TEACHING AND LEARNING IN VARIOUS SUBJECT AREAS. THIS DESIGN-BASED RESEARCH PROJECT INTEGRATES DATA-FOCUSED LEARNING INTO INTERDISCIPLINARY PBL IN WAYS THAT PREPARE MARGINALIZED LEARNERS FOR THE FUTURE. THE PROJECT DEVELOPS DESCRIPTIVE CASE STUDIES INVESTIGATING THREE QUESTIONS: (1) IN IMPLEMENTATIONS OF THE DATAPBL CURRICULUM, WHAT INTERDISCIPLINARY DATA PRACTICES DO STUDENTS PARTICIPATE IN, AND UNDER WHAT CONDITIONS? (2) UNDER WHAT CONDITIONS DO STUDENTS MANIFEST AGENCY IN THE COURSE OF THEIR DATA-INFUSED PBL? AND (3) HOW DO ASPECTS OF THE EXPERIENCED PROJECTS CONTRIBUTE TO DEVELOPING POSITIVE IDENTITIES RELATED TO DATA? THROUGH THIS CASE STUDY ANALYSIS, THE PROJECT PROVIDES A THICK DESCRIPTION OF HOW AGENCY AND IDENTITY DEVELOP DURING DATAPBL PROJECTS IN THE PARTICIPATING CLASSES. THE PROJECT APPLIES QUALITATIVE COMPARATIVE ANALYSIS TO GENERATE CROSS-CASE PATTERNS AND ILLUSTRATE THE MULTIPLE PATHWAYS AVAILABLE TO STUDENTS IN REACHING THE DESIRED OUTCOMES. IN COMBINATION WITH THE CASE STUDIES, THIS WORK ILLUMINATES HOW THE LEARNING ENVIRONMENT FOSTERS THE AIMS OF THE PROJECT. THE DISCOVERY RESEARCH PREK-12 PROGRAM (DRK-12) SEEKS TO SIGNIFICANTLY ENHANCE THE LEARNING AND TEACHING OF SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS (STEM) BY PREK-12 STUDENTS AND TEACHERS, THROUGH RESEARCH AND DEVELOPMENT OF INNOVATIVE RESOURCES, MODELS AND TOOLS. PROJECTS IN THE DRK-12 PROGRAM BUILD ON FUNDAMENTAL RESEARCH IN STEM EDUCATION AND PRIOR RESEARCH AND DEVELOPMENT EFFORTS THAT PROVIDE THEORETICAL AND EMPIRICAL JUSTIFICATION FOR PROPOSED PROJECTS. 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.

DIP: COLLABORATIVE RESEARCH: MIXED-REALITY LABS: INTEGRATING SENSORS AND SIMULATIONS TO IMPROVE LEARNING

SIMULATIONS FOR PERFORMANCE ASSESSMENTS THAT REPORT ON KNOWLEDGE AND SKILLS (SPARKS)

EXPLORING DATA BY VOICE: MAKING DATA EXPLORATION ACCESSIBLE FOR BLIND AND LOW-VISION LEARNERS USING AI -DATA SCIENCE HAS BECOME ESSENTIAL IN MODERN SOCIETY, WITH GROWING CAREER OPPORTUNITIES AND WIDESPREAD ADOPTION IN EDUCATIONAL CURRICULA. HOWEVER, BLIND AND LOW-VISION (BLV) STUDENTS ARE SIGNIFICANTLY UNDERSERVED IN THIS FIELD, OFTEN LACKING THE TOOLS NECESSARY FOR MEANINGFUL ENGAGEMENT WITH DATA. THIS THREE-YEAR PROJECT, A COLLABORATION BETWEEN THE CONCORD CONSORTIUM AND PERKINS SCHOOL FOR THE BLIND, ADDRESSES THE CRITICAL NEED FOR ACCESSIBLE DATA SCIENCE TOOLS IN K-12 EDUCATION. LEVERAGING A CUTTING-EDGE LARGE LANGUAGE MODEL (LLM) FROM GENERATIVE AI TECHNOLOGIES, AND PARTNERS? EXPERTISE IN EDUCATIONAL TECHNOLOGY AND BLV LEARNING INNOVATIONS, THE PROJECT TEAM WILL CREATE A MULTIMODAL DATA EXPLORATION ENVIRONMENT. BY ENABLING BLV STUDENTS TO INTERACT WITH DATA THROUGH VOICE COMMANDS, SONIFICATION, AND AI-GENERATED AUDIBLE DESCRIPTIONS, RESEARCHERS AIM TO TRANSFORM THE EDUCATIONAL EXPERIENCE AND BROADEN PARTICIPATION IN STEM. THE PROJECT TEAM WILL RESEARCH AND DEVELOP AN AI-POWERED AGENT EMBEDDED IN THE NSF FUNDED COMMON ONLINE DATA ANALYSIS PLATFORM (CODAP), A FREE, OPEN SOURCE, DATA ANALYSIS APPLICATION DESIGNED TO ENGAGE STUDENTS IN DATA EXPLORATION. THE AI-POWERED AGENT WILL PROVIDE THE INTERFACE BETWEEN THE USER, THE GENERATIVE AI MODEL, AND CODAP. IT WILL INTERPRET BLV USERS? VOICE COMMANDS TO PERFORM DATA TRANSFORMATIONS, GENERATE DATA REPRESENTATIONS, FACILITATE NON-SEQUENTIAL NAVIGATION AND EXPLORATION OF DATA REPRESENTATIONS, AND PROVIDE VERBAL AND SONIFIED DESCRIPTIONS OF DATA REPRESENTATIONS. THE PROJECT WILL EMPLOY AN ITERATIVE DEVELOPMENT PROCESS THAT INCLUDES CO-DESIGN SESSIONS WITH BLV USERS AND TESTING WITH EXPERIENCED ACCESSIBILITY RESEARCHERS, AND WILL INVESTIGATE TWO RESEARCH QUESTIONS: (1) IN WHAT WAYS CAN GENERATIVE AI-BASED TECHNOLOGIES BE LEVERAGED TO FACILITATE ACCESSIBLE INTERACTION WITH DATA FOR BLV USERS? (2) WHAT EFFECT DOES THE AVAILABILITY OF INTERACTIVE AND GENERATIVE TECHNOLOGIES HAVE ON BLV STUDENTS? ABILITY TO ENGAGE WITH AND MAKE MEANING OF DATASETS? THE RESEARCH TEAM WILL DEVELOP AUTOMATED TESTS MEASURING LLM RESPONSES FOR FAITHFULNESS, ANSWER RELEVANCE, AND CONTEXT RELEVANCE. USER INTERACTION WITH THE AI-POWERED AGENT WILL BE LOGGED. STUDENT SCREENCAST RECORDINGS, AND TRANSCRIPTS OF PROTOTYPE TESTING BY THE ACCESSIBILITY EXPERTS AND STUDENTS WILL BE TRIANGULATED WITH THE LOGGED DATA AND ANALYZED USING BOTH DEDUCTIVE AND INDUCTIVE CODES. THE OUTPUT OF THE PROJECT INCLUDES THE WEB-BASED, AI-POWERED AGENT EMBEDDED IN CODAP. SOURCE CODE AND LLM TRAINING MATERIALS INCLUDING PROMPTS, RETRIEVAL DATA AND FINE-TUNING DATA, WILL BE MADE PUBLICLY AVAILABLE IN GITHUB REPOSITORIES. RESEARCH FINDINGS AND PRODUCTS WILL BE DISSEMINATED AT CONFERENCES AND IN JOURNALS ON ACCESSIBILITY, AI AND LEARNING SCIENCES RESEARCH. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

MAPPING TIME: OPENING FRONTIERS FOR STUDENT EXPLORATION OF TIME-BASED GEOSPATIAL DATASETS -GEOSPATIAL DATA IS CENTRAL TO UNDERSTANDING AND ADDRESSING GLOBAL CHALLENGES, FROM NATURAL DISASTERS TO THE SPREAD OF DISEASE, AND TO CHANGES IN GLOBAL COMMERCE AND DISTRIBUTION OF RESOURCES. FLUENCY IN TIME-BASED GEOSPATIAL ANALYSIS IS INCREASINGLY ESSENTIAL IN SCIENCE, TECHNOLOGY, MATHEMATICS, AND ENGINEERING PROFESSIONS. YET THIS ANALYSIS IS HIGHLY COMPLEX, AND HIGH SCHOOL STUDENTS OFTEN LACK ACCESSIBLE TOOLS AND SUPPORT TO ENGAGE WITH SUCH DATA TO DEVELOP FLUENCY IN ANALYSIS. THIS PROJECT TEAM IS COMPOSED OF LEARNING SCIENTISTS, EDUCATIONAL TECHNOLOGY DEVELOPERS, COGNITIVE SCIENTISTS, GEOSPATIAL EDUCATORS, AND HIGH SCHOOL TEACHERS EXPERIENCED IN GEOSPATIAL ANALYSIS INSTRUCTION. LEVERAGING EMERGING RESEARCH IN INTERFACES AND ANALYSIS TECHNIQUES FOR VISUALIZING AND ANALYZING TIME-BASED GEOSPATIAL DATASETS, THE PROJECT WILL DESIGN, DEVELOP, AND TEST TECHNOLOGIES THAT MAKE TIME-BASED GEOSPATIAL DATA APPROACHABLE BY HIGH SCHOOL LEARNERS, AND WILL EQUIP STUDENTS WITH CRITICAL DATA LITERACY SKILLS NEEDED FOR FUTURE ACADEMIC AND CAREER SUCCESS. THIS PROJECT WILL ADOPT A DESIGN-BASED RESEARCH APPROACH TO DEVELOP THE MAPPING TIME EXPLORER; A NOVEL VISUAL ANALYTICS SYSTEM AIMED AT INTEGRATING AND ADAPTING IDENTIFIED USER INTERFACE (UI) APPROACHES AND GEOSPATIAL ANALYSIS TECHNIQUES INTO A NOVICE-FRIENDLY SOFTWARE SUITE FOR THE EXPLORATION OF TIME-BASED GEOSPATIAL DATASETS. THE PROJECT WILL CONDUCT EARLY-STAGE RESEARCH IN TECHNOLOGY AND LEARNING INNOVATION TO EXPLORE TWO SETS OF TECHNOLOGY INNOVATION RESEARCH QUESTIONS: 1) HOW CAN EMERGING UI AFFORDANCES AND DESIGNS BE LEVERAGED FOR USE BY HIGH SCHOOL STUDENTS FOR VISUALIZING AND EXPLORING TIME-BASED GEOSPATIAL DATA, AND 2) HOW CAN EMERGING METHODOLOGIES FOR PROCESSING AND ANALYZING TIME-BASED GEOSPATIAL DATA BE LEVERAGED FOR USE BY HIGH SCHOOL STUDENTS? IN PARALLEL, THE PROJECT WILL INVESTIGATE TWO SETS OF LEARNING INNOVATION QUESTIONS: 1) HOW CAN EMERGING UI AFFORDANCES AND DESIGNS WITHIN INQUIRY-BASED CLASSROOM ACTIVITIES ENABLE HIGH SCHOOL STUDENTS TO EXPLORE AND ANALYZE TIME-BASED GEOSPATIAL DATA, AND 2) WHICH EMERGENT METHODOLOGIES FOR PROCESSING TIME-BASED GEOSPATIAL DATA OFFER PROMISE FOR HIGH SCHOOL STUDENTS' LEARNING? THE PROJECT WILL PUBLISH AND PRESENT RESEARCH ON TECHNOLOGY DESIGN AND STUDENT LEARNING AND MAKE PROJECT SOFTWARE PUBLICLY AVAILABLE VIA OPEN-SOURCE LICENSES. THIS PROJECT IS FUNDED BY THE RESEARCH ON INNOVATIVE TECHNOLOGIES FOR ENHANCED LEARNING (RITEL) PROGRAM THAT SUPPORTS EARLY-STAGE EXPLORATORY RESEARCH IN EMERGING TECHNOLOGIES FOR TEACHING AND LEARNING. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

ELECTRON TECHNOLOGIES: MODELING PICO WORLDS FOR NEW CAREERS

TEACHING TEAMWORK: ELECTRONICS INSTRUCTION IN A COLLABORATIVE ENVIRONMENT

SEPARATING THE SIGNAL FROM THE NOISE: PROMOTING ALASKAN STUDENTS' INQUIRY WITH GEOGRAPHICALLY RELEVANT SEISMIC DATA AND MACHINE LEARNING TECHNIQUES -THIS PROJECT WILL CONTRIBUTE TO THE EARTH SCIENCE EDUCATION COMMUNITY'S UNDERSTANDING OF HOW ENGAGING STUDENTS IN AUTHENTIC COMPUTER SCIENCE EXPERIENCES, INCLUDING INNOVATIVE METHODS SUCH AS MACHINE LEARNING, CAN DEEPEN STUDENTS' MOTIVATION AND LEARNING OF GEOSCIENCE CONCEPTS. THE SEISMICML PROJECT WILL ENGAGE MIDDLE SCHOOL STUDENTS IN ANCHORAGE, ALASKA, IN AUTHENTIC INVESTIGATIONS OF THEIR COMMUNITY'S NATURAL AND HUMAN-CAUSED SEISMIC EVENTS USING PRACTICES OF PROFESSIONAL GEOSCIENTISTS. THROUGH A PARTNERSHIP AMONG TEACHERS, GEOSCIENTISTS, EDUCATIONAL RESEARCHERS, TECHNOLOGY AND CURRICULUM DEVELOPERS, AND SCIENCE ADMINISTRATORS, THE PROJECT WILL CREATE A ONE-WEEK SEISMOLOGY CURRICULUM CENTERED AROUND AN INNOVATIVE BLOCK PROGRAMMING INTERFACE CALLED DATAFLOW. WITHIN THE CURRICULUM, STUDENTS WILL (1) EXPLORE THE OCCURRENCE OF EARTHQUAKES IN THE COMMUNITY BY INSTALLING SCIENTIFIC GRADE SEISMOMETERS IN THEIR SCHOOL, (2) USE MACHINE LEARNING TO IDENTIFY AND CLASSIFY SEISMIC EVENTS, (3) CREATE DATA VISUALIZATIONS OF SEISMIC EVENTS REGISTERED AT THEIR SCHOOL, AND (4) CONSTRUCT BLOCK PROGRAMS THAT IMPORT REAL-TIME SEISMIC DATA TO FIND PATTERNS IN SEISMIC EVENTS OVER DIFFERENT TIME PERIODS AND ACROSS DIFFERENT REGIONS. THE PROJECT WILL PRODUCE EVIDENCE-BASED TEACHING STRATEGIES THAT PROMOTE STUDENTS' ABILITY TO CONDUCT AUTHENTIC COMPUTATIONAL SCIENCE INVESTIGATIONS. THE GOAL OF THE SEISMICML PROJECT IS TO ENGAGE ALASKAN MIDDLE SCHOOL STUDENTS IN CONTEXTUALIZED INQUIRY INVESTIGATIONS WITH LOCAL SEISMIC DATA TO HELP THEM UNDERSTAND APPLICATIONS OF COMPUTER SCIENCE AND MACHINE LEARNING IN MODERN SCIENCE. TWO CYCLES OF DESIGN-BASED RESEARCH WILL BE CONDUCTED TO DEVELOP THE SEISMICML CURRICULUM AND DATAFLOW PROGRAM. A MIXED METHODS RESEARCH DESIGN WILL BE APPLIED TO ANSWER THE FOLLOWING RESEARCH QUESTIONS: TO WHAT EXTENT DOES USING THE COMPUTATIONALLY INTEGRATED SEISMIC CURRICULUM BUILD STUDENTS' COMPUTATIONAL PRACTICES AND GEOSCIENCE CONTENT KNOWLEDGE? WHAT ARE THE NOVEL AFFORDANCES OF INTEGRATING GEOGRAPHICALLY RELEVANT DATA, GEOSCIENTIFIC CONCEPTS, AND AUTHENTIC COMPUTER SCIENCE AND MACHINE LEARNING PRACTICES FOR ENGAGING MIDDLE SCHOOL STUDENTS IN MEANINGFUL SEISMIC INVESTIGATIONS? IS STUDENT ENGAGEMENT WITH AN AUTHENTIC COMPUTATIONALLY INTEGRATED EARTH SCIENCE CURRICULUM ASSOCIATED WITH IMPROVED ATTITUDES, PERCEIVED RELEVANCE, AND SCIENCE LEARNING OUTCOMES? WHAT TYPES OF TEACHER, CURRICULAR, AND COMPUTATION-RELATED SUPPORTS ARE NECESSARY TO ENGAGE STUDENTS IN COMPUTATIONALLY INTEGRATED SEISMIC INVESTIGATIONS? DATA SOURCES INCLUDE RECORDINGS OF CLASSROOM DISCOURSE, PRE- AND POST-SURVEYS, EMBEDDED ASSESSMENTS, DATAFLOW SNAPSHOTS, AND TEACHER INTERVIEWS. PROJECT RESEARCH WILL GENERATE KNOWLEDGE ABOUT CURRICULUM DESIGN AND TEACHING STRATEGIES THAT PROMOTE STUDENTS' ENGAGEMENT IN COMPUTATION-MEDIATED SCIENCE PRACTICES AUTHENTIC TO PROFESSIONAL SEISMOLOGISTS' WORK. BY DEMONSTRATING THE EFFECTIVENESS OF EMBEDDING COMPUTER SCIENCE AND MACHINE LEARNING INTO SPECIFIC DISCIPLINARY MIDDLE SCHOOL COURSES, THIS PROJECT WILL PRODUCE A REPLICABLE PEDAGOGICAL MODEL FOR INCLUDING MACHINE LEARNING IN OTHER STEM CONTEXTS, INCLUDING ALGEBRA, PHYSICS, AND CAREER AND TECHNICAL COURSES. ALL PROJECT MATERIALS WILL BE MADE AVAILABLE FOR FREE THROUGH OPEN-SOURCE AND OPEN-CONTENT LICENSING TO ALL FUTURE LEARNERS, TEACHERS, AND RESEARCHERS BEYOND THE PARTICIPANTS OUTLINED IN THE PROJECT. RESEARCH FINDINGS WILL BE DISSEMINATED AT CONFERENCES AND IN RESEARCH AND PRACTITIONER JOURNALS. THE PROJECT IS SUPPORTED BY THE COMPUTER SCIENCE FOR ALL (CSFORALL) PROGRAM, WHICH AIMS TO PROVIDE ALL U.S. STUDENTS WITH THE OPPORTUNITY TO PARTICIPATE IN COMPUTER SCIENCE AND COMPUTATIONAL THINKING EDUCATION IN THEIR SCHOOLS. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

SCIENCE AND ENGINEERING EDUCATION FOR INFRASTRUCTURE TRANSFORMATION

SENSING SCIENCE: HEAT AND TEMPERATURE READINESS FOR EARLY ELEMENTARY STUDENTS

HIGH ADVENTURE SCIENCE

COLLABORATIVE RESEARCH: SIMBUILDING: TEACHING BUILDING SCIENCE WITH SIMULATION GAMES

A TECHNOLOGY EXEMPLAR: POST-TEXTBOOK UDL MATERIALS

EXP: PAPER MECHATRONICS: ADVANCING ENGINEERING EDUCATION THROUGH COMPUTATIONALLY ENHANCED CHILDREN'S PAPERCRAFTS

EXP: LINKING COMPLEX SYSTEMS: PROMOTING REASONING WITHIN AND ACROSS INTERCONNECTED COMPLEX SYSTEMS

A LEARNING ECOSYSTEM FOR TEACHING HIGH SCHOOL STUDENTS MACHINE LEARNING CONCEPTS AND DATA SCIENCE SKILLS IN HEALTHCARE AND MEDICINE -HEALTHCARE IS RAPIDLY CHANGING INTO A MULTIDISCIPLINARY FIELD. DATA SCIENCE AND ARTIFICIAL INTELLIGENCE (AI) HAVE BECOME INTEGRAL FOR HEALTHCARE AND MEDICAL SERVICES. MACHINE LEARNING (ML), A BRANCH OF AI, IS BROADLY APPLICABLE FOR DEVELOPING PREDICTIVE MODELS THAT DRIVE RESEARCH, DEVELOPMENT AND HEALTHCARE PRACTICES. UNINTENTIONAL BIAS WITHIN THE DATASETS AND COMPUTER PROGRAMS USED FOR ML CREATES HEALTHCARE OUTCOMES WHICH BENEFIT SOME PEOPLE MORE THAN OTHERS. THIS PROJECT WILL DEVELOP AN INNOVATIVE AND INCLUSIVE LEARNING AND TEACHING ECOSYSTEM FOR HIGH SCHOOL STUDENTS. THE ECOSYSTEM CONSISTS OF EDUCATIONAL AGENCIES AND TEACHERS, CROSS-DISCIPLINARY EXPERTISE FROM DATA SCIENTISTS AND MEDICAL CLINICIANS, COMMUNITY MEMBERS AND COLLEGE STUDENTS FROM DIVERSE BACKGROUND AS MENTORS. AUTHENTIC CROSS-CULTURAL DISCUSSIONS AMONGST COMMUNITY MEMBERS AND STUDENTS WILL BE A KEY COMPONENT OF STUDENTS? LEARNING EXPERIENCE. THE ECOSYSTEM WILL PROVIDE A DATA SCIENCE AND ML LABORATORY COURSE AND AN ANNUAL DATATHON. COMPUTER SCIENCE TEACHERS WILL FACILITATE THE COURSE, AND WILL ALSO RECEIVE PROFESSIONAL DEVELOPMENT IN PROBLEM-BASED DATA SCIENCE APPROACHES. STUDENTS IN THE COURSE WILL EXPLORE STUDENT-LED, INQUIRY-BASED STRATEGIES ON HOW TO NAVIGATE AND VISUALIZE LARGE HEALTHCARE SETS USING THE SAME PROGRAMMING LANGUAGES AND TOOLS THAT DATA SCIENTISTS USE. DURING THE DATATHON, STUDENTS WILL TEAM WITH THEIR LOCAL COMMUNITY MEMBERS AND SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) TEACHERS TO SOLVE AUTHENTIC DATA-DRIVEN HEALTHCARE ISSUES WHICH ARE IMPORTANT AND PERSONAL TO THEM. COMMUNITY MEMBERS WILL SHARE THEIR EXPERIENCES TO ENSURE ALL VOICES ARE HEARD. DATATHON PARTICIPANTS WILL BE INTRODUCED TO CULTURALLY-RESPONSIVE METHODS. THE PROJECT IS 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. DURING THE PROJECT PERIOD, RESEARCHERS WILL DEVELOP AND STUDY A SEMESTER-LONG PROGRAM THAT ENGAGES UP TO 1000 RHODE ISLAND HIGH SCHOOL STUDENTS, WITH AN EMPHASIS ON RECRUITING RACIAL MINORITIES AND YOUNG WOMEN FROM 12 TITLE 1 SCHOOLS. THE RESEARCHERS WILL INVESTIGATE HOW STUDENTS ENGAGE IN THE PROGRAM AND DATATHON, THE USABILITY AND SUSTAINABILITY OF THIS PROGRAM, AND THE ENACTMENT OF THE INNOVATIVE LEARNING ECOSYSTEM. THE FOLLOWING QUESTIONS WILL GUIDE THIS STUDY: 1) HOW DO THE DATA LABORATORY AND DATATHON CONTRIBUTE TO STUDENT LEARNING AND EFFICACY IN DATA SCIENCE, AND THEIR INTEREST IN DATA SCIENCE AND HEALTHCARE CAREERS? 2) WHAT ARE TEACHERS? PERSPECTIVES ABOUT THE USABILITY AND EFFECTIVENESS, INCLUDING CHALLENGES, OF THE MATERIALS, CURRICULUM, AND SUPPORTS? 3) HOW DO TEACHERS TAKE UP AND ENACT THE ACTIVITIES AND TOOLS TO SUPPORT STUDENT LEARNING AND INTERESTS IN DATA SCIENCE? RESEARCHERS WILL COLLECT AND ANALYZE DATA USING MIXED METHODS, INCLUDING DATA FROM A DIGITAL LEARNING PLATFORM, SURVEYS, INTERVIEWS, ASSESSMENTS, AND OBSERVATIONS. THE OUTCOME WILL INCLUDE A NOVEL PEDAGOGY FOR TEACHING HIGH SCHOOL STUDENTS ABOUT RAPIDLY EVOLVING TECHNOLOGIES. DELIVERABLES WILL CONSIST OF ANNUAL PROFESSIONAL DEVELOPMENT FOR THE TEACHERS; A PUBLIC WEBSITE FOR ALL RHODE ISLAND DISTRICT LEADERS, TEACHERS, AND PARENTS; A VETTED DATA SCIENCE AND ML LABORATORY COURSE; AND DESIGNS OF THE MULTIDISCIPLINARY, CROSS-CULTURAL DATATHON. THESE WILL BE FREELY SHARED AND PROMOTED ONLINE, PRESENTED AT PROFESSIONAL CONFERENCES, AND PUBLISHED AS RESEARCH ARTICLES IN PEER-REVIEWED LITERATURE. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

CONCORD CONSORTIUM COLLECTION

COLLABORATIVE RESEARCH: INTEGRATING LANGUAGE-BASED AI ACROSS THE HIGH SCHOOL CURRICULUM TO CREATE DIVERSE PATHWAYS TO AI-RICH CAREERS -ARTIFICIAL INTELLIGENCE (AI) IS TRANSFORMING NUMEROUS INDUSTRIES AND GENERATING ENORMOUS WEALTH. K-12 IS THE CRITICAL STAGE FOR YOUTH TO DEVELOP KNOWLEDGE OF AND INTEREST IN AI. THIS PROJECT WILL LEVERAGE THE INTERDISCIPLINARITY OF AI TO CREATE LEARNING OPPORTUNITIES FOR SECONDARY STUDENTS FROM DIVERSE BACKGROUNDS. FOCUSING ON NATURAL LANGUAGE-BASED AI, THIS PROJECT WILL DEVELOP AND RESEARCH A NOVEL AI ACROSS THE CURRICULUM PROGRAM THAT INTEGRATES AI CONCEPTS AND PRACTICES INTO THE EXISTING HIGH SCHOOL CURRICULUM. THE PROJECT TEAM WILL DEVELOP AND TEST A TWO-HOUR INTRODUCTORY MODULE AND THREE FIVE-HOUR MODULES FOR MATHEMATICS, ENGLISH LANGUAGE ARTS (ELA), AND HISTORY, AS WELL AS A 60-HOUR PROFESSIONAL DEVELOPMENT PROGRAM FOR TEACHERS TO DEVELOP THE COMPETENCIES REQUIRED TO IMPLEMENT THE MODULES. TEACHERS IN MATH, ELA, AND HISTORY WILL IMPLEMENT THE MODULES IN A COORDINATED FASHION TO OFFER LEARNING EXPERIENCES THAT ARE COHERENT ACROSS THE DIFFERENT DISCIPLINES TO THEIR STUDENTS. DURING THE PROJECT, 12 TEACHERS AND 900 STUDENTS WILL DIRECTLY BENEFIT FROM PARTICIPATION IN THE PROGRAM. THE OUTPUT OF THE PROJECT WILL ADVANCE NATIONAL PROSPERITY THROUGH AI WORKFORCE DEVELOPMENT BY ENABLING HIGH SCHOOLS TO PROVIDE HIGH-QUALITY AI EDUCATION TO ALL STUDENTS, ESPECIALLY AFRICAN AMERICANS, LATINX, AND FEMALES, WHO ARE THE UNDERREPRESENTED AND UNDERSERVED GROUPS IN THE FIELD OF AI. THE PROJECT WILL BE LED BY AN INTERDISCIPLINARY TEAM OF AI DEVELOPERS AND EDUCATORS, STEM AND HUMANITIES EDUCATORS, LEARNING SCIENTISTS AND DESIGNERS, AND EXPERTS ON DIVERSITY, EQUITY, AND INCLUSION AT THE CONCORD CONSORTIUM, CARNEGIE MELLON UNIVERSITY, AND NORTH CAROLINA STATE UNIVERSITY. THE TEAM WILL PARTNER WITH THE SAN JOAQUIN COUNTY OFFICE OF EDUCATION IN CALIFORNIA AND THE MARYLAND CENTER FOR COMPUTING EDUCATION AND WORK CLOSELY WITH TWO SCHOOL DISTRICTS, ONE IN CA AND ONE IN MD, THAT SERVE STUDENT POPULATIONS UNDERREPRESENTED AND UNDERSERVED IN THE FIELD OF AI. RESEARCHERS WILL ADDRESS THREE RESEARCH QUESTIONS: 1) HOW DO STUDENTS? SOCIAL AND DISCIPLINARY IDENTITIES SHAPE THEIR PARTICIPATION IN LEARNING OF AI KNOWLEDGE AND AI-RICH CAREERS? GUIDED BY THE INTERSECTIONAL IDENTITY THEORY, THE PROJECT WILL CAPTURE EIGHT FOCAL STUDENTS? LEARNING PROCESSES WITH REPEATED INTERVIEWS, VIDEO, AUDIO, AND SCREENCAST RECORDINGS, AND COMPUTER LOGS. THESE DATA WILL BE ANALYZED USING THE PERSONAL NARRATIVES FRAMEWORK AND ETHNOMETHODOLOGICAL AND CONVERSATION-ANALYTIC APPROACHES. 2) WHAT AND HOW ARE NEW IDEAS GENERATED BY TEACHERS AS THEY SEEK TO COORDINATE THEIR EFFORTS TO INTEGRATE AI ACROSS THE CURRICULUM? BASED ON THE COMMUNITY OF PRACTICE THEORY, THE PROJECT WILL CAPTURE TEACHERS? IDEA GENERATION AND TRANSACTION PROCESSES WITH PROFESSIONAL DEVELOPMENT (PD) RECORDINGS, ONLINE COMMUNICATIONS, AND INTERVIEWS. THESE DATA WILL BE ANALYZED USING THE IDEA AUTHORSHIP FRAMEWORK. 3) TO WHAT EXTENT, FOR WHOM, AND UNDER WHAT CONDITIONS DOES THE AI ACROSS THE CURRICULUM PROGRAM SUPPORT STUDENTS TO DEVELOP KNOWLEDGE OF AND INTEREST IN AI-RICH CAREERS? THE DEMOGRAPHIC AND ACADEMIC BACKGROUNDS OF 900 STUDENTS AND 12 TEACHERS WILL BE COLLECTED VIA SURVEYS TO DETERMINE THE IMPACT OF THIS APPROACH. AN AI & MACHINE LEARNING CORE CONCEPTS QUESTIONNAIRE AND AN AI-RICH CAREERS QUESTIONNAIRE WILL BE ADMINISTERED BEFORE AND AFTER THE CURRICULUM. THESE DATA WILL BE ANALYZED QUANTITATIVELY TO DETERMINE TO WHAT EXTENT, FOR WHOM, AND UNDER WHAT CONDITIONS THE MODULES ARE BENEFICIAL. THROUGH RESEARCH PUBLICATIONS AND PROFESSIONAL LEARNING RESOURCES, THE PROJECT WILL INCREASE THE CAPACITY OF EDUCATORS AND RESEARCHERS TO ADVANCE AI EDUCATION. ALL TECHNOLOGIES, CURRICULUM MODULES, ASSESSMENTS, AND PD MATERIALS WILL BE 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.

GENIVILLE: EXPLORING THE INTERSECTION OF SCHOOL AND SOCIAL MEDIA

DESIGNING INTERACTIVE VISUALIZATIONS OF NEURAL PATHWAYS IN LANGUAGE-BASED AI FOR SECONDARY STUDENTS TO EXPLORE INTERPRETABILITY OF AI AND HUMAN-MACHINE COLLABORATION -ARTIFICIAL INTELLIGENCE (AI) IS TRANSFORMING NUMEROUS INDUSTRIES AND CATALYZING SCIENTIFIC DISCOVERIES AND ENGINEERING INNOVATIONS. TO PREPARE TO ENTER AN AI-READY WORKFORCE, YOUNG PEOPLE MUST BE INTRODUCED TO CORE AI CONCEPTS AND PRACTICES EARLY TO DEVELOP FUNDAMENTAL UNDERSTANDINGS AND PRODUCTIVE ATTITUDES. NEURAL NETWORKS, A KEY APPROACH IN AI DEVELOPMENT, HAVE BEEN INTRODUCED TO SECONDARY STUDENTS USING VARIOUS APPROACHES. HOWEVER, MORE WORK IS NEEDED TO ADDRESS THE INTERPRETABILITY OF NEURAL NETWORKS AND HUMAN-MACHINE COLLABORATION IN THE DEVELOPMENT PROCESS. THIS EXPLORATORY PROJECT WILL DEVELOP AND TEST A DIGITAL LEARNING TOOL FOR SECONDARY STUDENTS TO LEARN HOW TO INTERPRET NEURAL NETWORKS AND COLLABORATE WITH THE ALGORITHM TO IMPROVE AI SYSTEMS. THE LEARNING TOOL WILL ALLOW STUDENTS TO INTERACT WITH COMPLEX CONCEPTS VISUALLY AND DYNAMICALLY. IT WILL ALSO LEVERAGE STUDENTS? KNOWLEDGE AND INTUITION OF NATURAL LANGUAGES BY CONTEXTUALIZING NEURAL NETWORKS IN NATURAL LANGUAGE PROCESSING SYSTEMS. THE PROJECT TEAM INCLUDES LEARNING EXPERIENCE DESIGNERS AND TECHNOLOGY DEVELOPERS FROM THE CONCORD CONSORTIUM, COMPUTER SCIENTISTS FROM CARNEGIE MELLON UNIVERSITY, EDUCATIONAL RESEARCHERS FROM NORTH CAROLINA STATE UNIVERSITY, CURRICULUM SPECIALISTS AND TEACHER EDUCATORS FROM MISSISSIPPI STATE UNIVERSITY CENTER FOR CYBER EDUCATION, AND USABILITY AND FEASIBILITY EVALUATORS FROM WESTED. TWO MIDDLE SCHOOL TEACHERS FROM MASSACHUSETTS AND MISSISSIPPI AND OVER 50 EIGHTH GRADE STUDENTS WILL BE DIRECTLY IMPACTED THROUGH THEIR PARTICIPATION AS CO-DESIGNERS OR TESTERS. THIS PROJECT WILL INVESTIGATE THE DESIGN OF LEARNING TOOLS AND LEARNING EXPERIENCES FOR MIDDLE SCHOOL STUDENTS TO ENGAGE WITH NEURAL PATHWAYS AND HUMAN-MACHINE COLLABORATION IN AI DEVELOPMENT. USING DESIGN-BASED RESEARCH AND PARTICIPATORY DESIGN METHODS, THE PROJECT WILL ADDRESS THE RESEARCH QUESTION: WHAT ARE THE CHARACTERISTICS OF LEARNING TOOLS THAT CAN SUPPORT MIDDLE SCHOOL STUDENTS IN DEVELOPING AN UNDERSTANDING OF NEURAL PATHWAYS IN LANGUAGE-BASED AI AND COMPETENCIES IN HUMAN-MACHINE COLLABORATION IN AI DEVELOPMENT? THE PROJECT TEAM WILL (1) DEVELOP AND TEST INTERACTIVE VISUALIZATIONS OF NEURAL PATHWAYS FOR STUDENTS TO INVESTIGATE NEURAL PATHWAYS WITH UNIGRAMS AND WORD EMBEDDING AS THE INPUT LAYERS; (2) ITERATIVELY ENACT AND IMPROVE THE DESIGN WITH FIVE STUDENT VOLUNTEERS AND TWO MIDDLE SCHOOL TEACHERS PARTICIPATING AS CO-DESIGNERS AND TESTERS; (3) CONDUCT CLASSROOM TESTING WITH THE TWO CO-DESIGN TEACHERS IN THEIR CLASSROOMS (WITH APPROXIMATELY 50 STUDENTS). IN BOTH LAB AND CLASSROOM TESTS, PROJECT STAFF WILL DEVELOP INSTRUCTIONS AND LEARNING ACTIVITIES, FACILITATE TESTING SESSIONS, AND COLLECT OBSERVATION, INTERVIEW, SURVEY, AND VIDEO/SCREENCAST DATA. THE DATA WILL BE ANALYZED QUALITATIVELY AND QUANTITATIVELY TO INFORM THE REVISION AND REFINEMENT OF BOTH THEORY AND DESIGN. THE DEVELOPED LEARNING TOOL AND EXEMPLARY LEARNING ACTIVITIES WILL BE MADE FREELY AVAILABLE AND CONTRIBUTE TO K-12 AI EDUCATION RESOURCES AND KNOWLEDGE BASE THAT BENEFIT ALL STUDENTS, ESPECIALLY THOSE FROM DEMOGRAPHIC GROUPS UNDERREPRESENTED IN THE COMPUTING FIELD, TO DEVELOP THEIR TALENT AND INTEREST IN AI AND COMPUTER SCIENCE. THIS PROJECT IS FUNDED BY THE DISCOVERY RESEARCH PREK-12 (DRK-12) PROGRAM, WHICH SEEKS TO SIGNIFICANTLY ENHANCE THE LEARNING AND TEACHING OF SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS (STEM) BY PREK-12 STUDENTS AND TEACHERS, THROUGH RESEARCH AND DEVELOPMENT OF INNOVATIVE RESOURCES, MODELS AND TOOLS. PROJECTS IN THE DRK-12 PROGRAM BUILD ON FUNDAMENTAL RESEARCH IN STEM EDUCATION AND PRIOR RESEARCH AND DEVELOPMENT EFFORTS THAT PROVIDE THEORETICAL AND EMPIRICAL JUSTIFICATION FOR PROPOSED PROJECTS. 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.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

THE SCIENCE OF ATOMS AND MOLECULES: ENABLING THE NEW SECONDARY SCIENCE CURRICULUM

POSE: PHASE I: OPEN DATA EXPLORATION TOOLS FOR K-12 EDUCATION -DATA FLUENCY IS A CRITICAL 21ST CENTURY SKILL. TO LEARN THE FOUNDATIONS OF DATA SCIENCE, STUDENTS MUST ENGAGE IN RICH DATA EXPLORATION OF ROBUST DATASETS BEGINNING FROM THE EARLY GRADES ONWARD. RECOGNIZING THIS PIVOTAL ROLE OF DATA SCIENCE IN MODERN EDUCATION AND ITS POTENTIAL TO EQUIP STUDENTS WITH CRITICAL ANALYTICAL SKILLS, THIS INITIATIVE SEEKS TO SOLIDIFY AND EXTEND THE REACH OF THE COMMON ONLINE DATA ANALYSIS PLATFORM (CODAP)?A TOOL ALREADY EMBRACED BY EDUCATORS WORLDWIDE FOR ITS USER-FRIENDLY, VISUAL INTERFACE TAILORED TO K-12 LEARNERS. THE PROJECT?S PRIMARY GOAL IS TO BEGIN THE PROCESS OF ESTABLISHING A SUSTAINABLE OPEN-SOURCE ECOSYSTEM TO ENSURE THAT CODAP REMAINS A FREE, ROBUST RESOURCE FOR EXPLORING DATA. BY DOING SO, IT AIMS TO ADDRESS THE TECHNOLOGICAL NEEDS OF K-12 EDUCATION, FACILITATING ACCESS TO A QUALITY DATA SCIENCE TOOL SPECIFICALLY DESIGNED FOR THE CLASSROOM. THE OPEN DATA EXPLORATION TOOLS FOR K-12 EDUCATION PROJECT WILL ENHANCE DATA SCIENCE EDUCATION IN K-12 SCHOOLS THROUGH THE DEVELOPMENT OF AN OPEN-SOURCE ECOSYSTEM SUPPORTING THE SUSTAINABILITY AND EXPANSION OF CODAP. THE PROJECT AIMS TO: (1) IDENTIFY, SCOPE, AND ENGAGE CODAP?S CURRENT AND POTENTIAL USER COMMUNITY, INCLUDING DIRECT CODE CONTRIBUTORS, PLUGIN DEVELOPERS, INTEGRATORS, AND END-USER CONTRIBUTORS, SUCH AS EDUCATORS, CURRICULUM DEVELOPERS, AND TRANSLATORS TO CLARIFY THEIR CAPABILITIES AND NEEDS; (2) EXPLORE CODAP?S POTENTIAL FOR ESTABLISHING NEW USER COMMUNITIES WITHIN UNEXPECTED OR CURRENTLY UNDISCOVERED DOMAINS, INCLUDING EDUCATION ADMINISTRATORS, SCIENCE OR CITIZEN SCIENCE COMMUNITIES, INDUSTRY/SMALL BUSINESS USERS, OR OTHER INFORMAL DATA EXPLORATION USERS; (3) IDENTIFY AND SMOKE-TEST A DISTRIBUTED DEVELOPMENT INFRASTRUCTURE FOR SUPPORTING DIFFERENT COMMUNITIES INCLUDING CODAP PLUGIN DEVELOPERS, DATASET CONTRIBUTORS, AND CONTENT DEVELOPERS INCLUDING REFINING EXISTING INFRASTRUCTURE AND PRACTICES FOR DISTRIBUTED CODE DEVELOPMENT; (4) IDENTIFY APPROPRIATE ORGANIZATIONAL, GOVERNANCE, AND COORDINATION MODELS SUITED FOR SUPPORTING A ROBUST, SUSTAINABLE CODAP ECOSYSTEM THAT ACCOMMODATES REPRESENTATION OF GOALS FROM USERS ACROSS THE ECOSYSTEM AND ENSURES ONGOING QUALITY CONTROL, PRIVACY, AND SECURITY; AND (5) EXPLORE AVENUES FOR ENSURING A SUSTAINABLE ECOSYSTEM FOR CODAP, INCLUDING COMMERCIAL OPPORTUNITIES SUCH AS PROFESSIONAL DEVELOPMENT SERVICES, POTENTIAL FOUNDATION SUPPORT, OR PARTNERSHIPS WITH EDUCATIONAL TECHNOLOGY OR INDUSTRY SUPPORTERS. THIS PROJECT IS CO-FUNDED BY THE INNOVATIVE TECHNOLOGY EXPERIENCES FOR STUDENTS AND TEACHERS (ITEST) PROGRAM, WHICH SUPPORTS PROJECTS THAT BUILD UNDERSTANDINGS OF PRACTICES, PROGRAM ELEMENTS, CONTEXTS AND PROCESSES CONTRIBUTING TO INCREASING STUDENTS' KNOWLEDGE AND INTEREST IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) AND INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) CAREERS. 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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

EAGER: CYBERLEARNING: TOWARDS VIRTUAL WORLDS THAT AFFORD KNOWLEDGE INTEGRATION ACROSS PROJECT CHALLENGES AND DISCIPLINES

PILOTING GRAPH LITERACY ACTIVITIES IN MAINE

RAPID: MAKING THE TRANSITION TO REMOTE SCIENCE TEACHING AND LEARNING

RAPID: THE SCIENCE OF ATOMS AND MOLECULES PROJECT

CHANGE MAKERS: CROWDSOLVING THE ENERGY CHALLENGE THROUGH CYBER-ENABLED OUT-OF-SCHOOL CITIZEN SCIENCE PROGRAMS

COLLABORATIVE RESEARCH: VISUALIZING CHEMISTRY WITH INFRARED IMAGINING

CONFERENCE: A LEARNING PROGRESSION FOR K-12 DATA SCIENCE EDUCATION -IN TODAY'S INCREASINGLY DATA-RICH WORLD, DATA SCIENCE EDUCATION IS VITAL NOT ONLY FOR WORK IN STEM FIELDS BUT ALSO FOR ALL CITIZENS. ALTHOUGH IT IS INCREASINGLY CLEAR THAT DATA SCIENCE EDUCATION AT THE K-12 LEVEL IS VITAL, MUCH DEBATE STILL EXISTS ABOUT THE FORM AND FOCUS IT SHOULD ASSUME IN THE CLASSROOM. THE PROPOSED WORKSHOP WILL GATHER A DIVERSE GROUP OF LEADING RESEARCHERS IN THE FIELD OF DATA SCIENCE EDUCATION TO DEVELOP A COHESIVE RESEARCH FRAMEWORK TO DEFINE AND GUIDE THIS QUICKLY GROWING FIELD. THIS FRAMEWORK WILL FOCUS ON WHAT LEARNERS NEED TO KNOW AND BE ABLE TO DO WITH DATA STARTING WITH THE EARLIEST LEARNERS AND GOING THROUGH HIGH SCHOOL. WORKSHOP PARTICIPANTS WILL ALSO IDENTIFY THE KEY GRAND CHALLENGES FOR DATA SCIENCE EDUCATION AND SUGGEST THE MOST VALUABLE AREAS FOR FUTURE RESEARCH. IN DOING SO, THE OUTCOME OF THE WORKSHOP WILL SUPPORT RESEARCHERS, EDUCATORS, DEVELOPERS, AND POLICYMAKERS, BOLSTERING THE COHERENCE OF FUTURE EFFORTS TOWARDS SUPPORTING COMPREHENSIVE DATA SCIENCE EDUCATION IN GRADES K-12. ESTABLISHING AND CHARACTERIZING CURRENT RESEARCH IN DATA SCIENCE EDUCATION IS CRITICAL TO GUIDING ALL ASPECTS OF THIS QUICKLY EMERGING FIELD. TO ADDRESS THIS NEED, THIS PROJECT BRINGS TOGETHER STAKEHOLDERS FROM ACROSS THE FIELD OF K-12 DATA SCIENCE EDUCATION, FIRST IN A SMALLER STEERING COMMITTEE AND FOCUSED PRE-WORK GROUPS AND THEN FOR A MULTIPLE-DAY IN-PERSON KNOWLEDGE BUILDING SESSION, TO GRAPPLE WITH A SERIES OF CONNECTED QUERIES POSITIONED AT THE CENTER OF THE FIELD'S CURRENT NEEDS. VIA ORGANIZED GUIDED DISCUSSIONS THE WORKSHOP WILL PROPOSE A SUMMARY OF THE PROGRESS MADE SO FAR IN DSE RESEARCH, IDENTIFY PLACES WHERE THE LARGEST GAPS REMAIN, AND HIGHLIGHT THE AREAS THAT PROVIDE THE MOST PROMISING GROUND FOR INTERCONNECTION. THE WORKSHOP WILL THEN EMPLOY THE SUMMARY OF EXISTING RESEARCH TO SUGGEST A LEARNING PROGRESSIONS FRAMEWORK FOR K-12 DATA SCIENCE EDUCATION AIMED TO BENEFIT A BROAD RANGE OF STAKEHOLDERS AND APPLICATIONS. THE WORKSHOP WILL ADOPT AN APPROACH THAT BOUNDS THE COMPONENTS INVOLVED IN DATA SCIENCE EDUCATION, PROVIDING A FRAMEWORK ELUCIDATING STRANDS OF LEARNING THAT COMPRISE THE DOMAIN WITH EACH IDENTIFIED STRAND DELIBERATELY PROVIDING ENTRY POINTS SPANNING GRADES K-12. THIS FRAMEWORK WILL BE SOLID ENOUGH TO INFORM WORK ACROSS BOTH RESEARCH AND DEVELOPMENT, YET FLEXIBLE ENOUGH TO EVOLVE AND INCORPORATE THE MANY NEW FINDINGS CERTAIN TO ARISE DURING THE WORKSHOP ACTIVITIES. THE RESULTING FRAMEWORK WILL SERVE AS GUIDANCE FOR IDENTIFYING FUTURE RESEARCH PRIORITIES AND SUGGESTIONS TO SUPPORTERS, FUNDERS, AND IMPLEMENTING STAKEHOLDERS, INCLUDING POLICY- AND DECISION-MAKERS AT LOCAL AND REGIONAL LEVELS. THIS PROJECT IS FUNDED BY THE INNOVATIVE TECHNOLOGY EXPERIENCES FOR STUDENTS AND TEACHERS (ITEST) PROGRAM, WHICH SUPPORTS PROJECTS THAT BUILD UNDERSTANDINGS OF PRACTICES, PROGRAM ELEMENTS, CONTEXTS, AND PROCESSES CONTRIBUTING TO INCREASING STUDENTS' KNOWLEDGE AND INTEREST IN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) AND INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) CAREERS. 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.

COLLABORATIVE RESEARCH: CONSTRUCTIVE CHEMISTRY: PROBLEM-BASED LEARNING THROUGH MOLECULAR MODELING

CAP: BUILDING PARTNERSHIPS FOR EDUCATION AND SPEECH RESEARCH

EMPOWERING INFORMAL EDUCATORS TO PREPARE FUTURE GENERATIONS IN WIRELESS RADIO COMMUNICATIONS WITH MOBILE RESOURCES