Computer Science

From Access to Sustainability: Investigating Ways to Foster Sustainable Use of Computational Modeling in K-12 Science Classrooms

This project investigates how to support sustained engagement in computational modeling in middle school classrooms in two ways: 1) Design and develop an accessible modeling toolkit and accompanying thematically linked curricular units; and, 2) Examine how this toolkit and curriculum enable students to become sophisticated modelers and integrate modeling with other scientific practices such as physical experimentation and argumentation.

Award Number: 
2010413
Funding Period: 
Wed, 07/15/2020 to Fri, 06/30/2023
Full Description: 

Modeling is a core scientific activity in which a difficult-to-observe phenomenon is represented, e.g., visually or in a computer program. Research has shown that sustained experience with modeling contributes to sophisticated understanding, learning, and engagement of scientific practices. Computational modeling is a promising way to integrate computation and science learning. Yet computational modeling is not widely adopted in science classrooms over sustained periods of time because of difficulties such as the time required for students to become adept modelers, the need to better integrate computational modeling with other scientific practices, and the need for teachers to experience agency in using these modeling tools. This Design and Development project investigates how to support sustained engagement in computational modeling in middle school classrooms in two ways: 1) Design and develop an accessible modeling toolkit and accompanying thematically linked curricular units; and, 2) Examine how this toolkit and curriculum enable students to become sophisticated modelers and integrate modeling with other scientific practices such as physical experimentation and argumentation. The project will contribute to the conversation around how to support students and teachers to incorporate computational modeling together with valued scientific practices into their classrooms for sustained periods. For three years, the project will work with six sixth and seventh grade teachers and approximately 400 students.

Through iterative cycles of design-based research, the project will design a computational modeling tool and six curricular units for sixth and seventh-grade students. The team will work closely with two teacher co-designers to design and develop each of the six curricular units. The goal is to investigate: 1) How students become sophisticated modelers as they shift from using phenomenon-level primitives to unpacking and modifying these primitives for extended investigations; 2) How classroom norms around computational modeling develop over time. Specifically, how do student models become objects for classroom reflection and how students integrate modeling into other practices such as explanation and argumentation; 3) How data from physical experiments support students in constructing and refining models; and, 4) How sustained engagement supports students' conceptual learning and learning to model using computing tools. The team will collect and analyze video and written data, as well as log files and pre/posttests, to examine how communities of students and teachers adopt computational modeling as an integral practice in science learning. For video and text analysis, the team will use qualitative coding to detect patterns before, during, and after the activities. For the examination of logfiles from the software, the project will use learning analytics techniques such as the classification and clustering of students' sequences of actions. Finally, the team will also conduct pre/post-tests on both content and meta-modeling skills, analyzing the results with standard statistical tests.

Assessing College-Ready Computational Thinking (Collaborative Research: Brown)

The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.

Award Number: 
2010265
Funding Period: 
Tue, 09/01/2020 to Sat, 08/31/2024
Full Description: 

Because of the growing need for students to be college and career ready, high-quality assessments of college readiness skills are in high demand. To realize the goal of preparing students for college and careers, assessments must measure important competencies and provide rapid feedback to teachers. It is necessary to go beyond the limits of multiple-choice testing and foster the skills and thinking that lie at the core of college and career ready skills, such as computational thinking. Computational thinking is a set of valuable skills that can be used to solve problems, design systems, and understand human behavior, and is thus essential to developing a more STEM-literate public. Computational thinking is increasingly seen as a fundamental analytical skill that everyone, not just computer scientists, can use. The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.

The project will address a set of research questions focused on 1) clarifying computational thinking constructs, 2) usability, reliability of validity of assessment items and the information they provide, 3) teachers' use of assessments, and 4) relationships to student performance. The study sample of 2,700 used for the pilot and field tests will include all levels of students in 10th through 12th grade and first year college students (both community college and university level). The target population is students in schools which are implementing the College Readiness Program (CRP) of the National Mathematics and Science Institute. In the 2020-21 academic year 54 high schools across 11 states (CA, GA, FL, ID, LA, NC, NM, OH, TX, VA, and WA) will participate. This will include high school students in Advanced Placement classes as well as non-Advanced Placement classes.  The team will use the BEAR Assessment System to develop and refine assessment materials. This system is an integrated approach to developing assessments that seeks to provide meaningful interpretations of student work relative to cognitive and developmental goals. The researchers will gather empirical evidence to develop and improve the assessment materials, and then gather reliability and validity evidence to support their use. In total, item response data will be collected from several thousand students. Student response data will be analyzed using multidimensional item response theory models.

Assessing College-Ready Computational Thinking (Collaborative Research: Wilson)

The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.

Award Number: 
2010314
Funding Period: 
Tue, 09/01/2020 to Sat, 08/31/2024
Full Description: 

Because of the growing need for students to be college and career ready, high-quality assessments of college readiness skills are in high demand. To realize the goal of preparing students for college and careers, assessments must measure important competencies and provide rapid feedback to teachers. It is necessary to go beyond the limits of multiple-choice testing and foster the skills and thinking that lie at the core of college and career ready skills, such as computational thinking. Computational thinking is a set of valuable skills that can be used to solve problems, design systems, and understand human behavior, and is thus essential to developing a more STEM-literate public. Computational thinking is increasingly seen as a fundamental analytical skill that everyone, not just computer scientists, can use. The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.

The project will address a set of research questions focused on 1) clarifying computational thinking constructs, 2) usability, reliability of validity of assessment items and the information they provide, 3) teachers' use of assessments, and 4) relationships to student performance. The study sample of 2,700 used for the pilot and field tests will include all levels of students in 10th through 12th grade and first year college students (both community college and university level). The target population is students in schools which are implementing the College Readiness Program (CRP) of the National Mathematics and Science Institute. In the 2020-21 academic year 54 high schools across 11 states (CA, GA, FL, ID, LA, NC, NM, OH, TX, VA, and WA) will participate. This will include high school students in Advanced Placement classes as well as non-Advanced Placement classes.  The team will use the BEAR Assessment System to develop and refine assessment materials. This system is an integrated approach to developing assessments that seeks to provide meaningful interpretations of student work relative to cognitive and developmental goals. The researchers will gather empirical evidence to develop and improve the assessment materials, and then gather reliability and validity evidence to support their use. In total, item response data will be collected from several thousand students. Student response data will be analyzed using multidimensional item response theory models.

Reaching Across the Hallway: An Interdisciplinary Approach to Teaching Computer Science in Rural Schools

This project will develop, test, and refine a "train-the-trainer" professional development model for rural teacher-leaders. The project goal is to design and develop a professional development model that supports teachers integrating culturally relevant computer science skills and practices into their middle school social studies classrooms, thereby broadening rural students' participation in computer science.

Lead Organization(s): 
Award Number: 
2010256
Funding Period: 
Wed, 07/01/2020 to Sun, 06/30/2024
Full Description: 

Strengthening computer science (CS) and computational thinking (CT) education is a national priority with particular attention to increasing the number of teachers prepared to deliver computer science courses. For rural schools, that collectively serve more than 10 million students, it is especially challenging. Rural schools find it difficult to recruit and retain STEM teachers that are prepared to teach computer science and computational thinking. This project will develop, test, and refine a "train-the-trainer" professional development model for rural teacher-leaders. The project will build teachers' self-efficacy to deliver computer science concepts and practices into middle school social studies classrooms. The project is led by CodeVA (a statewide non-profit in Virginia), in partnership with TERC (a STEM-focused national research institution) and the University of South Florida College of Education, and in collaboration with six rural school districts in Virginia. The project goal is to design and develop a professional development model that supports teachers integrating culturally relevant computer science skills and practices into their middle school social studies classrooms, thereby broadening rural students' participation in computer science. The professional development model will be designed and developed around meeting rural teachers, where they are, geographically, economically, and culturally. The model will also be sustainable and will work within the resource constraints of the rural school district. The model will also be built on strategies that will broadly spread CS education while building rural capacity.

The project will use a mixed-methods research approach to understand the model's potential to build capacity for teaching CS in rural schools. The research design is broken down into four distinct phases; planning/development prototyping, piloting and initial dissemination, an efficacy study, and analysis, and dissemination. The project will recruit 45 teacher-leaders and one district-level instructional coach, 6th and 7th-grade teachers, and serve over 1900 6th and 7th-grade students. Participants will be recruited from the rural Virginia school districts of Buchanan, Russell, Charlotte, Halifax, and Northampton. The research question for phase 1 is what is each district's existing practice around computer science education (if any) and social studies education? Phases 2, 3 and 4 research will examine the effectiveness of professional development on teacher leadership and the CS curricular integration. Phase 4 research will examine teacher efficacy to implement the professional development independently, enabling district teachers to integrate CS into their social studies classes. Teacher data sources for each phase include interviews with administrators and teachers, teacher readiness surveys, observations, an examination of artifacts, and CS/CT content interviews. Student data will consist of classroom observation and student attitude surveys. Quantitative and qualitative data will be triangulated to address each set of research questions and provide a reliability check on findings. Qualitative data, such as observations/video, and interview data will be analyzed through codes that represent expected themes and patterns related to teachers' and coaches' experiences. Project results will be communicated through presentations at conferences such as Special Interest Group on Computer Science Education, the Computer Science Teachers Association (CSTA), the National Council for Social Studies (NCSS), and the American Educational Research Association. Lesson plans will be made available on the project website, and links will be provided through publications and newsletters such as the NCSS Middle-Level Learner, NCSS Social Education, CSTA the Voice, the NSF-funded CADREK12 website and the NSF-funded STEM Video Showcase.

Internet of Things Pedagogical Ecosystem for Integrated Computer Science and Software Engineering Education for Grades 9-12

This project aims to develop, implement, and evaluate an Internet of Things (IoT) based educational curriculum and technology that provides grades 9-12 students with Computer Science (CS) and Software Engineering (SE) education.

Award Number: 
2010259
Funding Period: 
Wed, 07/01/2020 to Fri, 06/30/2023
Full Description: 

The Internet of Things (IoT) technology connects physical devices such as industrial machines, vehicles, kitchen appliances, medical devices to the internet to enable users, businesses, and computers to make data driven decisions. The IoT is a rapidly improving, transformative field that is bound to positively impact global job markets and industries. With continued advancement in science and technology comes the need to educate K-12 students in emerging technologies to better prepare them for future academic and professional pursuits. This project aims to develop, implement, and evaluate an Internet of Things (IoT) based educational curriculum and technology that provides grades 9-12 students with Computer Science (CS) and Software Engineering (SE) education. At its core, the IoT technology uses inexpensive microcomputers that run code to collect, analyze, and share data with other devices or users. Due to this inherent integration between hardware and software, IoT has the potential to serve as an excellent platform for teaching CS and SE to high school students. Grades 9-12 teachers and students from diverse and varied socioeconomic backgrounds will participate in this curricular experience through their STEM/CS/Engineering classes. Broad dissemination through online platforms, summer camps, and museums will be used to share content, testimonials, teaching strategies, and best practices to a wide audience in the K-12 education community. Over three hundred high school students and 27 teachers will be engaged directly in-class or via outreach activities. The skills and knowledge gained as part of this curricular experience will provide strong college and career readiness to high school students.

The proposed IoT pedagogical ecosystem features an innovative approach to bringing CS and SE education to grades 9-12 by immersing students in the technical challenges of building web-connected physical computing systems. This project will focus on identifying critical elements for effective instructional design for CS and SE education by understanding student and teacher motivation. A key innovation of this effort will be the low-cost, IoT-hardware kits for project-based learning to create a hands-on experience in the classroom. The curriculum will involve real-world projects inspired by the National Academy of Engineering grand challenges that have direct applications in the industry (e.g., urban infrastructure, wearable technology, connected vehicles, connected health, and cybersecurity). Continuous and methodical assessment via rubrics and focus groups will enable data collection on students' CS/SE/IoT knowledge and skills, teamwork skills, and overall engagement. Rigorous quantitative statistical analysis (parametric and non-parametric) and qualitative methods (first cycle and second cycle coding) will be used to answer three research questions: 1) What is the impact of IoT-based projects on students' CS, SE, and hardware skills and knowledge? 2)What is the effect of IoT-based projects on students' engagement and teamwork skills? 3) What factors of instructional design promote/hinder engagement? This project will cumulatively provide an evidence-based understanding of how effective IoT is as a means to provide high school students with critical and modern CS/SE skills and knowledge.

Exploring Early Childhood Teachers' Abilities to Identify Computational Thinking Precursors to Strengthen Computer Science in Classrooms

This project will explore PK-2 teachers' content knowledge by investigating their understanding of the design and implementation of culturally relevant computer science learning activities for young children. The project team will design a replicable model of PK-2 teacher professional development to address the lack of research in early computer science education.

Lead Organization(s): 
Award Number: 
2006595
Funding Period: 
Tue, 09/01/2020 to Thu, 08/31/2023
Full Description: 

Strengthening computer science education is a national priority with special attention to increasing the number of teachers who can deliver computer science education in schools. Yet computer science education lacks the evidence to determine how teachers come to think about computational thinking (a problem-solving process) and how it could be integrated within their day-to-day classroom activities. For teachers of pre-kindergarten to 2nd (PK-2) grades, very little research has specifically addressed teacher learning. This oversight challenges the achievement of an equitable, culturally diverse, computationally empowered society. The project team will design a replicable model of PK-2 teacher professional development in San Marcos, Texas, to address the lack of research in early computer science education. The model will emphasize three aspects of teacher learning: a) exploration of and reflection on computer science and computational thinking skills and practices, b) noticing and naming computer science precursor skills and practices in early childhood learning, and c) collaborative design, implementation and assessment of learning activities aligned with standards across content areas. The project will explore PK-2 teachers' content knowledge by investigating their understanding of the design and implementation of culturally relevant computer science learning activities for young children. The project includes a two-week computational making and inquiry institute focused on algorithms and data in the context of citizen science and historical storytelling. The project also includes monthly classroom coaching sessions, and teacher meetups.

The research will include two cohorts of 15 PK-2 teachers recruited from the San Marcos Consolidated Independent School District (SMCISD) in years one and two of the project. The project incorporates a 3-phase professional development program to be run in two cycles for each cohort of teachers. Phase one (summer) includes a 2-week Computational Making and Inquiry Institute, phase two (school year) includes classroom observations and teacher meetups and phase three (late spring) includes an advanced computational thinking institute and a community education conference. Research and data collection on impacts will follow a mixed-methods approach based on a grounded theory design to document teachers learning. The mixed-methods approach will enable researchers to triangulate participants' acquisition of new knowledge and skills with their developing abilities to implement learning activities in practice. Data analysis will be ongoing, interweaving qualitative and quantitative methods. Qualitative data, including field notes, observations, interviews, and artifact assessments, will be analyzed by identifying analytical categories and their relationships. Quantitative data includes pre to post surveys administered at three-time points for each cohort. Inter-item correlations and scale reliabilities will be examined, and a repeated measures ANOVA will be used to assess mean change across time for each of five measures. Project results will be communicated via peer-reviewed journals, education newsletters, annual conferences, family and teacher meetups, and community art and culture events, as well as on social media, blogs, and education databases.

Pandemic Learning Loss in U.S. High Schools: A National Examination of Student Experiences

As a result of the COVID-19 pandemic, schools across much of the U.S. have been closed since mid-March of 2020 and many students have been attempting to continue their education away from schools. Student experiences across the country are likely to be highly variable depending on a variety of factors at the individual, home, school, district, and state levels. This project will use two, nationally representative, existing databases of high school students to study their experiences in STEM education during the COVID-19 pandemic.

Lead Organization(s): 
Award Number: 
2030436
Funding Period: 
Fri, 05/15/2020 to Fri, 04/30/2021
Full Description: 

As a result of the COVID-19 pandemic, schools across much of the U.S. have been closed since mid-March of 2020 and many students have been attempting to continue their education away from schools. Student experiences across the country are likely to be highly variable depending on a variety of factors at the individual, home, school, district, and state levels. This project will use two, nationally representative, existing databases of high school students to study their experiences in STEM education during the COVID-19 pandemic. The study intends to ascertain whether students are taking STEM courses in high school, the nature of the changes made to the courses, and their plans for the fall. The researchers will identify the electronic learning platforms in use, and other modifications made to STEM experiences in formal and informal settings. The study is particularly interested in finding patterns of inequities for students in various demographic groups underserved in STEM and who may be most likely to be affected by a hiatus in formal education.

This study will collect data using the AmeriSpeak Teen Panel of approximately 2,000 students aged 13 to 17 and the Infinite Campus Student Information System with a sample of approximately 2.5 million high school students. The data sets allow for relevant comparisons of student experiences prior to and during the COVID-19 pandemic and offer unique perspectives with nationally representative samples of U.S. high school students. New data collection will focus on formal and informal STEM learning opportunities, engagement, STEM course taking, the nature and frequency of instruction, interactions with teachers, interest in STEM, and career aspirations. Weighted data will be analyzed using descriptive statistics and within and between district analysis will be conducted to assess group differences. Estimates of between group pandemic learning loss will be provided with attention to demographic factors.

This RAPID award is made by the DRK-12 program in the Division of Research on Learning. The Discovery Research PreK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics by preK-12 students and teachers, through the research and development of new innovations and approaches. 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 the 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.

 

 

 

 

Developing a Suite of Standards-based Instructionally Supportive Tools for Middle School Computer Science

This project will develop a set of educative resources, assessment tools and teacher professional development (PD) activities to support teachers in developing knowledge of CS standards and improving their instructional pedagogy. Teachers will learn to use formative assessments related to these standards to determine student understanding. Improved CS instruction that is responsive to the needs and challenges of the student population is particularly critical in school districts with a large population of students who are typically underserved and under-represented in computer science.

Lead Organization(s): 
Award Number: 
2010591
Funding Period: 
Fri, 05/15/2020 to Sun, 04/30/2023
Full Description: 

As computing has become an integral part of the world and the workforce, demand for computer science (CS) education in K-12 classrooms is growing. States and school districts in the U.S. are increasing CS course offerings, increasing the need for teachers with CS content and teaching knowledge. However, many CS teachers are not originally certified to teach computer science and often lack the necessary tools, resources, and training. This project will develop a set of educative resources, assessment tools and teacher professional development (PD) activities to support teachers in developing knowledge of CS standards and improving their instructional pedagogy. Teachers will learn to use formative assessments related to these standards to determine student understanding. Improved CS instruction that is responsive to the needs and challenges of the student population is particularly critical in school districts with a large population of students who are typically underserved and under-represented in computer science. The project, a partnership between SRI International and the Milwaukee Public School District, will provide professional development experiences tied to standards instead of a specific curriculum in order to support diverse teachers teaching a variety of computer science curricula using different programming languages. Teachers will receive training via a combination of virtual webinars and face-to-face instruction. Teachers will have opportunities to evaluate their own teaching and measure their students' progress towards the standards.

The research will examine how these teacher professional development activities can help improve CS content and pedagogical knowledge for teachers. The team will use a mixed-methods design to answer three research questions: 1) How can CS standards-aligned educative instructional supports be designed to be informative and useful to middle school CS teachers using different CS curricula and what professional development (PD) do teachers need to be able to use and benefit from these educative instructional supports? 2) What are the different ways in which teachers adapt and use the standards-aligned educative resources and instructionally supportive CS assessment tools in their CS classes? 3) How can standards-aligned instructional supports and teacher PD improve middle school teachers' CS pedagogical content knowledge and improve their implementation of standards-aligned CS instruction? To answer research question one, the team will use an Evidence-Centered Design approach to systematically unpack each standard and develop aligned instructionally supportive assessments and scoring guides. Data analysis for research question one includes qualitative analysis of student cognitive interviews to determine students' proficiencies and challenges, analysis of teacher PD surveys, inter-rater reliability analysis of teacher and researcher scores on assessments, psychometric analysis of student responses for reliability and validity evidence, analysis of classroom observations of teachers responding to data from assessments, and analysis of teacher interviews providing feedback on the usefulness of the PD provided and the assessment tasks and scoring guides that have been developed. For research questions two and three, the project will collect and analyze data from multiple sources, including teacher interviews, classroom observations, teacher PCK (pedagogical content knowledge) surveys, and teacher logs to determine the impacts of the project. Data analysis for questions two and three will include analysis of shifts in teacher PCK between the start of year two and the end of year three, qualitative analysis of observations of teachers' instructional practices, and analysis of teacher interviews reflecting on individual formative assessment practices and decisions. The project will recruit 16 teachers of varying experience levels. Additionally, upto 450 middle school students will be recruited with a significant number of female, African-American, and Hispanic students represented in the sample. Project evaluation will examine the overall achievement of program goals and objectives. Project results will be disseminated widely at national conferences and through submissions to refereed journals. The project resources and instructionally supportive tools including PD Webinars will be made available online to school districts and teachers.

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.

CAREER: Promoting Equitable and Inclusive STEM Contexts in High School

This project focuses on fostering equitable and inclusive STEM contexts with attention to documenting and reducing adolescents' experiences of harassment, bias, prejudice and stereotyping. This research will contribute to understanding of the current STEM educational climates in high schools and will help to identify factors that promote resilience in the STEM contexts, documenting how K-12 educators can structure their classrooms and schools to foster success of all students in STEM classes.

Award Number: 
1941992
Funding Period: 
Sat, 02/01/2020 to Fri, 01/31/2025
Full Description: 

This project focuses on fostering equitable and inclusive STEM contexts with attention to documenting and reducing adolescents' experiences of harassment, bias, prejudice and stereotyping. An important barrier to persistence in STEM fields for marginalized groups, including women and ethnic minorities, relates to a culture in many STEM organizations, such as academic institutions, that fosters discrimination, harassment and prejudicial treatment of those from underrepresented groups. This research will contribute to understanding of the current STEM educational climates in high schools and will help to identify factors that promote resilience in the STEM contexts, documenting how K-12 educators can structure their classrooms and schools to foster success of all students in STEM classes. Further, this work will explore how to create schools where students stand-up for each other and support each other so that any student who is interested will feel welcome in STEM classes and programs.

This research aims to examine cultures of discrimination and harassment in STEM contexts with attention to: 1) assessing STEM climates in high schools in order to identify the character of discrimination and harassment, 2) understanding how youth think about these instances of bias and discrimination; 3) identifying pathways to resilience for underrepresented youth pursuing STEM interests, and 4) testing an intervention to promote bystander intervention from those who witness discrimination and harassment in STEM contexts. This research will take an intersectional approach recognizing that those who are marginalized by multiple dimensions of their identity may experience STEM contexts differently than those who are marginalized by one dimension of their identity. Because adolescence is a critical developmental period during which youth are forming their attitudes, orientations and lifelong behaviors, this research will attend to issues of bias and discrimination well before individuals enter college STEM classrooms or the STEM workforce: namely, during high school. Further, this work will examine the creation of equitable STEM climates in both college-preparation classes as well as workforce development STEM programs offered though or in partnership with high schools. This research will provide clear evidence to document the current culture of STEM contexts in high schools, using mixed methods, including surveys, qualitative interviews and longitudinal measurement. Further, the project will involve development and implementation of an intervention, which will provide the first test of whether bystander intervention can be fostered in STEM students and will involve training STEM students in key 21st century skills, such as social-cognitive capacities and interpersonal skills, enabling them to speak up and support peers from marginalized backgrounds when they observe discrimination and harassment.

CAREER: Job Embedded Education on Computational Thinking for Rural STEM Discipline Teachers

This project will develop a professional development model that allows rural secondary teachers to learn and develop computational thinking related teaching skills with long-term support and scaffolds in place to both build their knowledge and the long-term capacity of their school districts.

Lead Organization(s): 
Award Number: 
1942500
Funding Period: 
Sat, 02/01/2020 to Fri, 01/31/2025
Full Description: 

This project will develop a new way of engaging teachers in professional learning that is situated in their classrooms while they perform the tasks of their paid employment. Traditional professional development structures frequently place financial and professional pressures on teachers, which limits participation. Rural teachers in particular may have fewer opportunities due to barriers of distance, limited resources, and lack of available staff. In addition, they often rely on the income from second jobs to meet their financial obligations, meaning they are unable to take advantage of optional professional development opportunities offered after school hours, on weekends, or during summers because they cannot afford the lost income or travel time. Further, they are most likely to be underqualified and most likely to spend their entire teaching careers at their first district, prospectively teaching multiple generations of students from their community. The state of Hawaii has a high proportion of such rural schools and a shortage of STEM teachers, especially in the area of computer science. This project will investigate a professional development model using fading scaffolds (support that is gradually reduced over time) as part of participants' paid summer school teaching. Through this model, 20 rural teachers will learn to integrate computational thinking, coding, and science content while working with students from their own communities, with 10 becoming master teachers supporting others throughout the state. Improving teachers' ability to prepare students to benefit from opportunities in STEM and computing will advance students' opportunities for future prosperity.

This CAREER project will develop a professional development model that allows rural secondary teachers to learn and develop computational thinking related teaching skills with long-term support and scaffolds in place to both build their knowledge and the long-term capacity of their school districts. Using a design-based research approach, this project entails extensive participant interviews, video observations, and analysis of classroom artifacts. Cultural-historical activity theory analysis will be applied both collectively and within a comparative case study format to understand individual teacher development within the context of their own content and classrooms over time. These data will inform subsequent iterative design decisions to revise strategies and materials for greater meaningfulness and utility in supporting teachers' implementation of computer science and computational thinking applications. This project will enhance academic achievement of approximately 1000 students (predominantly Pacific Islanders, a group largely underrepresented in STEM fields with a unique cultural identity) in meeting the Next Generation Science Standards and Hawaii's computer science education standards.

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