Given the growth of technology in the 21st century and the growing demands for computer science skills, computational thinking has been increasingly included in K-12 STEM (Science, Technology, Engineering and Mathematics) education. Computational thinking (CT) is relevant to integrated STEM and has many common practices with other STEM disciplines. Previous studies have shown synergies between CT and engineering learning. In addition, many researchers believe that the more children are exposed to CT learning experiences, the stronger their programming abilities will be. As programming is a
We explored the potential of science to facilitate social inclusion with teenagers who had interrupted their studies before the terms set for compulsory education. The project was carried out from 2014 to 2018 within SISSA (International School for Advanced Studies), a scientific and higher education institution in physics, mathematics and neurosciences, and was focused on the production of video games using Scratch. The outcomes are encouraging: through active engagement, the participants have succeeded in completing complex projects, taking responsibilities and interacting with people
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TEAM MEMBERS:
Simona CerratoFrancesca RizzatoLucia TealdiElena Canel
Computational Thinking (CT) is a relatively new educational focus and a clear need for learners as a 21st century skill. This proposal tackles this challenging new area for young learners, an area greatly in need of research and learning materials. The Principal Investigators will develop and implement integrated STEM+C museum exhibits and integrate CT in their existing engineering design based PictureSTEM curriculum for K-2 students. They will also pilot assessments of the CT components of the PictureSTEM curriculum. This work will make a unique contribution to the available STEM+C learning materials and assessments. There are few such materials for the kindergarten to second grade (K-2) population they will work with. They will research the effects of the curriculum and the exhibits with a mixed methods approach. First, they will collect observational data and conduct case studies to discover the important elements of an integrated STEM+C experience in both the formal in-school setting with the curriculum and in the informal out-of-school setting with families interacting with the museum exhibits. This work will provide a novel way to understand the important question of how in- and out-of-school experiences contribute to the development of STEM and CT thinking and learning. Finally, they will collect data from all participants to discover the ways that their activities lead to increases in STEM+C knowledge and interest.
The Principal Investigators will build on an integrated STEM curriculum by integrating CT and develop integrated museum exhibits. They base both activities on engineering design implemented through challenge based programming activities. They will research and/or develop assessments of both STEM+C integrated thinking and CT. Their research strategy combines Design Based Research and quantitative assessment of the effectiveness of the materials for learning CT. In the first two years of their study, they will engage in iterations on the design of the curriculum and the exhibits based on observation and case-study data. There will be 16 cases that draw from each grade level and involve data collection for the case student in both schools and museums. They will also use this work to illuminate what integrated STEM+C thinking and learning looks like across formal and informal learning environments. Based in some part on what they discover in this first phase, they will conduct the quantitative assessments with all (or at least most) students participating in the study
This exploratory learning research and design project will study how to use emerging technologies to help document practices in maker-based learning experiences. Despite its established potential for consolidating learning and sense-making, project documentation is often overlooked, not prioritized or seen as burdensome and therefore not integrated into the learning experiences. The project team seeks to understand and address with practice partners the barriers to documentation by systematically exploring how to physically embed and incorporate smart tools and documentation practices into learning environments, specifically creative hands-on learning spaces, like makerspaces. The goal is to understand how to scaffold learners to become more aware, reflective and attentive to their progress towards learning outcomes by embedding supportive tools physically in space as the actions unfold. Making and maker-based learning experiences offer tremendous opportunities to more fully engage diverse learners in STEM education and build a workforce prepared for innovation. Documentation of these learning experiences, both as an authentic practice that professionals engage in as well as an assessment practice for instruction, is often not supported. The project will create open source documentation for solutions and develop supporting case studies, web resources and guides to facilitate easy uptake and adoption of promising approaches.
This proposal will make significant research contributions in three ways: (1) develop and iteratively test a suite of embedded "smart" tools designed to scaffold, manage and trace process documentation practices; (2) study the integration of these tools in formal and informal activities and programs settings and characterize their influence on instruction and the assessment of learning outcomes; (3) establish a set of rubrics based on learner data streams to aid instruction and mark learner progress. Improving documentation practices and the assessment of learning outcomes will advance making as a core STEM educational activity. Through a better understanding of why and how to place networked documentation tools sensitive to space, time and context cues, the threshold for enactment and scaffolded usage can be lowered in a broader range of settings. Ultimately, this exploratory project will not only develop an integrated set of situated documentation tools, but also help us develop hypotheses for how documentation as a mediating process productively supports learning.
The Discovery Research K-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 (RMTs). 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. The Multimedia Immersion (MI) project is will develop, pilot, and evaluate a nine-week STEM-rich multimedia production course for high school students. MI will make important contributions to the field through its efforts to design and evaluate the promises and challenges of a nine-week multimedia curriculum in multiple urban high schools. The MI course will engage teams of students to develop a personally and socially relevant storyline that guides their use of accessible audio and video technologies to create a five-minute animated video. To develop student STEM experience and provide technical support, the project will provide guidance and learning experiences in engineering (e.g., criteria, constraints, optimization, tradeoffs), science (e.g. sound, light, energy, mechanics) and multimedia technologies (e.g., computer based audio production, video editing and visualizations through animatics (i.e., shooting a succession of storyboards with a soundtrack). animatics).
Because the curriculum situates engineering and science learning in the context of multimedia production, there are natural synergies with several existing high school courses including engineering design, audio/video media production, and multimedia technology. Although these courses are typically electives in high school, developing a 5-minute animated short on a topic of interest may encourage girls and students from underrepresented groups to select this course over other electives. MI will impact 10 teachers and approximately 250 high school students per year. The project will result in the following resources: nine-week curricular unit (multimedia, science, engineering); assessments to monitor student learning of science, engineering and technology (design logs); and research on changes in student knowledge, interest, and a nine-week curricular unit (multimedia, science, engineering). Project resources will be disseminated to teachers, researchers, and curriculum and professional development providers via conference presentations, publications, and online webinars.
The MI project builds on student familiarity and interest in music, video and technology to promote an: (1) understanding of engineering design and physics and an (2) an appreciation of the fundamental role of STEM in popular culture. Project evaluation will be conducted using student surveys and an examination of work products in conjunction with implementation challenges and successes to generate evidence for the feasibility and utility of a high school multimedia course that explicitly addresses science and engineering learning. Project evaluation will use student design logs as a window into student design processes and conceptual understanding. Student design logs are an essential feature of MI curriculum design. With an appropriate structure, these design logs can inform teaching, afford an opportunity for students to reflect on their own work, and provide evidence of student thinking and learning for assessment purposes. Using student design logs as a window into students? design process and conceptual understanding is an important contribution to the engineering education community which has few options for measuring student knowledge in ways that are consistent with the hands-on, iterative nature of the design process.
Data are the workhorses of the scientific endeavor and their use is rapidly evolving (Haendel, Vasilevsky, and Wirz 2012). Ask almost any scientist about their work, and the conversation will involve the data they collect and analyze. The use of data in science is often captured in science classrooms as an ill-defined link between math and science that may not reflect authentic data practices (Tanis Ozcelik and McDonald 2013). Students often find themselves collecting data to confirm obvious conclusions within highly structured labs, and data become a way for students to demonstrate the
This project, an NSF INCLUDES Design and Development Launch Pilot, managed by the University of Nevada, Reno, addresses the grand challenge of increasing underrepresentation regionally in the advanced manufacturing sector. Using the state's Learn and Earn Program Advanced Career Pathway (LEAP) as the foundation, science, technology, engineering and mathematics (STEM) activities will support and prepare Hispanic students for the region's workforce in advanced manufacturing which includes partnerships with Truckee Meadows Community College (TMCC), the state's Governor's Office of Economic Development, Charles River Laboratories, Nevada Established Program to Stimulate Competitive Research (Nevada EPSCoR) and the K-12 community.
The expected outcomes from the project will inform the feasibility, expandability and transferability of the LEAP framework in diversifying the state's workforce locally and the STEM workforce nationally. Formative and summative evaluation will be conducted with a well-matched comparison group. Dissemination of project results will be disseminated through the Association for Public Land-Grant Universities (APLU), STEM conferences and scholarly journals.
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TEAM MEMBERS:
David ShintaniJulie EllsworthKarsten HeiseRobert StachlewitzRegina Tempel
The University of Texas at Austin's Texas Advanced Computing Center, Chaminade University of Honolulu (CUH), and the Georgia Institute of Technology will lead this NSF INCLUDES Design and Development Launch Pilot (DDLP) to establish a model for data science preparation of Native Hawaiian and Pacific Islander (NHPI) students at the high school and undergraduate levels. The project is premised on the promise of NHPI communities gaining access to, and the ability to work with, large data sets to tackle emerging problems in the Pacific. Such agency over "big data" sets that are relevant to Pacific issues, and contemporary skills in data science, analytics and visualization have the potential to be transformative for community improvement efforts. The effort has the potential to advance knowledge, instructional pedagogy and practices to improve NHPI high school and undergraduate students performance in and attraction to STEM education and careers.
The project team will work to: 1) Increase interest and proficiency in data science and visualization among NHPI high school and undergraduate students through a summer immersion experience that bridges computation and culture; 2) Build data science capacity at an NHPI serving undergraduate institution (CUH) through creation of a certificate program; and 3) Develop and expand partnerships with other organizations with related goals working with NHPI populations. The month-long summer training for 20 NHPI college students, and five NHPI high school students, takes place at CUH and focuses on data science, visualization, and virtual reality, including working on problem sets that require data science approaches and incorporate geographically, socially- and culturally-relevant research themes.
This NSF INCLUDES Design and Development Launch Pilot (named ALCSE-INCLUDES) project will develop and implement an innovative computer science (CS) education model that will provide all 8th grade students in 3 districts in Alabama's 'Black Belt' with exciting and structured hands-on activities intended to make CS learning enjoyable. The course will use an educational style called "learning CS by making" where students will create a CS-based product (such as a robot) and understand the concepts that make the product work. This hands-on approach has the potential to motivate diverse student populations to pursue higher level CS courses and related disciplines during and after high school, and to join the CS workforce, which is currently in need of more qualified workers.
ALCSE-INCLUDES Launch Pilot will unite the efforts of higher education institutions, K-12 officials, Computer Science (CS)-related industry, and community organizations to pursue a common agenda: To develop, implement, study, and evaluate a scalable and sustainable prototype for CS education at the middle school level in the Alabama Black Belt (ABB) region. The ABB is a region with a large African-American, low-income population; thus, the program will target individuals who have traditionally had little access to CS education. The prototype for CS education will be piloted with 8th grade students in 3 ABB schools, using a set of coordinated and mutually reinforcing activities that will draw from the strengths of all members of the ALCSE Alliance. The future scaled-up version of the program will implement the prototype in the 73 middle schools that comprise ALL 19 school districts of the ABB. The program's main innovation is to provide CS education using a makerspace, a dedicated area equipped with grade-appropriate CS resources, in which students receive mentored and structured hands-on activities. The goal is to engage ALL students, in learning CS through making, an evidence-based pedagogical approach expected to reinforce skills and promote deep interest in CS.
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TEAM MEMBERS:
Shaik JeelaniBruce CrawfordMohammed QaziJeffrey GrayJacqueline Brooks
resourceprojectProfessional Development, Conferences, and Networks
Aligning for Impact: Computer Science Pathways Across Contexts [CS-PAC] is an NSF INCLUDES Design and Development Launch Pilot. It broadens participation of students who are underrepresented in computer science by using the convening and policy-making power of the Georgia State Department of Education to coalesce school district leaders to implement K-12 computer science education. The project provides a national model for how to work toward systemic change. With the State Department of Education's coordination, several school districts will collaboratively seek improvements in their own student participation rates. The coordination of data reporting and analysis, resources, communications, and policy promote more equitable participation in computer science education. Research emerging from this project informs other states about how to collaboratively shape computer science education policy and policy implementation.
Using a Collective Impact approach to systemic change, the project creates sustainable institutional change at the community, state, and national levels. Qualitative and quantitative data provide descriptions about how to utilize alignment strategies within Collective Impact in three different contexts: rural, suburban, and urban. Outcomes utilize a regression discontinuity analysis to justify successful implementation as well as qualitative analysis of implementation efforts that were deemed most effective by all stakeholders. The project outputs directly affect over 88,000 students across five districts and indirectly affect over 1.7 million in Georgia alone. The culminating project goal is the development of a coherent framework for aligning K-12 computer science education pathways.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches and resources for use in a variety of settings. This Research in Service to Practice project will address the issues around Informal Education of rural middle school students who have high potential regarding academic success in efforts to promote computer and IT knowledge, advanced quantitative knowledge, and STEM skills. Ten school districts in rural Iowa will be chosen for this study. It is anticipated that new knowledge on rural informal education will be generated to benefit the Nation's workforce. The specific objectives are to understand how informal STEM learning shapes the academic and psychosocial outcomes of rural, high-potential students, and to identify key characteristics of successful informal STEM learning environments for rural, high-potential students and their teachers. The results of this project will provide new tools for educators to increase the flow of underserved students into STEM from economically-disadvantaged rural settings.
The President's Council of Advisors on Science and Technology predicts a rapid rise in the number of STEM jobs available in the next decade, describing an urgent need for students' educational opportunities to prepare them for this workforce. In 2014, 62% of CEOs of major US corporations reported challenges filling positions requiring advanced computer and information technology knowledge. The project team will use a mixed methods approach, integrating comparative case study and mixed effects longitudinal methods, to study the Excellence program. Data sources include teacher interviews, classroom observations, and student assessments of academic aptitude and psychosocial outcomes. The analysis and evaluation of the program will be grounded in understanding the local efforts of school districts to build curriculum responsive to the demands of their high-potential student body. The project design, and subsequent analysis plan, utilizes a mixed methods approach, incorporating case study and longitudinal quantitative methods to analyze naturalistic data and build robust evidence for the implementation and impact of this program. This project will provide significant insights in how best to design, implement, and support informal out-of-school learning environments to broaden participation in the highest levels of STEM education and careers for under-resourced rural students.
As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches and resources for use in a variety of settings. In this exploratory Change Makers project, the Concord Consortium will develop, test, and evaluate a citizen science program that leverages innovative technology, such that youth engage directly with energy issues through scientific inquiry. The project will create the Infrared Street View, a citizen science program that aims to produce a thermal version of Google's Street View using an affordable infrared camera attached to a smartphone. The infrared camera serves as a high-throughput data acquisition instrument that collects thousands of temperature data points each time a picture is taken. Youth will collect massive geotagged thermal data that have considerable scientific and educational value for visualizing energy usage and improving energy efficiency at all levels. The Infrared Street View program will provide a Web-based platform for youth and anyone interested in energy efficiency to view and analyze the aggregated data to identify possible energy losses. By sharing their scientific findings with stakeholders, youth will make changes to the way energy is being used. The project will start with school, public, and commercial buildings in selected areas where performing thermal scan of the buildings and publishing their thermal images for educational and research purposes are permitted by school leaders, town officials, and property owners. In collaboration with high schools and out-of-school programs in Massachusetts, this project will conduct pilot-tests with approximately 200 students.
To contribute to advancing learning, the study will probe three research questions: 1) Under what circumstances can technology bridge out-of-school and classroom science learning and improve learning on both sides? 2) To what extent can unobtrusive assessment based on data mining support research and evaluation of student learning in out-of-school settings? and 3) To what extent can instructional intelligence built into the app used in the program help students learn in out-of-school programs and improve the quality of data they contribute to the citizen science project? Data sources for investigating these questions include students' interaction data with the app logged behind the scenes and the images they have taken, as well as results based on traditional assessments from a small number of participants. Throughout the project, staff will widely disseminate project products and findings through the Internet, science fairs, conferences, publications, and partner networks. An eight-member Advisory Board consisting of cleantech experts, science educators, and educational researchers will oversee and evaluate this project.
The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by designing and building new kinds of learning technologies and studying their possibilities for fostering learning and challenges to using them effectively. This project brings together two approaches to help K-12 students learn programming and computer science: open-ended learning environments, and computer-based learning analytics, to help create a setting where youth can get help and scaffolding tailored to what they know about programming without having to take tests or participate in rigid textbook exercises for the system to know what they know.
The project proposes to use techniques from educational data mining and learning analytics to process student data in the Alice programming environment. Building on the assessment design model of Evidence-Centered Design, student log data will be used to construct a model of individual students' computational thinking practices, aligned with emerging standards including NGSS and research on assessment of computational thinking. Initially, the system will be developed based on an existing corpus of pair-programming log data from approximately 600 students, triangulating with manually-coded performance assessments of programming through game design exercises. In the second phase of the work, curricula and professional development will be created to allow the system to be tested with underrepresented girls at Stanford's CS summer workshops and with students from diverse high schools implementing the Exploring Computer Science curriculum. Direct observation and interviews will be used to improve the model. Research will address how learners enact computational thinking practices in building computational artifacts, what patters of behavior serve as evidence of learning CT practices, and how to better design constructionist programming environments so that personalized learner scaffolding can be provided. By aligning with a popular programming environment (Alice) and a widely-used computer science curriculum (Exploring Computer Science), the project can have broad impact on computer science education; software developed will be released under a BSD-style license so others can build on it.
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TEAM MEMBERS:
Shuchi GroverMarie BienkowskiJohn Stamper