Although there has been an increase in efforts to introduce computer science and computational thinking (CS/CT) into secondary schools, most initiatives have not been designed to develop related knowledge and skills necessary for elementary in-service teachers. This issue is particularly important as states begin to adopt CS standards for K-12 with little to no support for implementation of the standards. At the same time, students with the most common disabilities need to have opportunities to learn the content and practices outlined those CS standards. The project will address this problem by generating, working in partnership with a local school division, Norfolk City Public Schools, a usable, comprehensive, effective, and appealing model of professional development (PD) to support CS integration in elementary instruction for all learners, with an emphasis on supporting students with high-incidence disabilities. In developing PD for integration of CS standards in elementary grades and creating resources to support teachers in this integration, this project will work with more than 75 elementary teachers in the partner district. Of the nearly 10,000 current K-5th grade students in NCPS in any given year, these teachers will, conservatively, teach 1,500 students or 15% of the student population yearly. The PD model will also be extended into other school divisions in Virginia through its relationship with CodeVA. Finally, PD and research-partnership strategies will be disseminated through online resources (i.e., video library, online training modules), presentations at local and national conferences, and peer reviewed manuscripts.
Faculty from George Mason University and Old Dominion University created a Researcher Practitioner Partnership with personnel from Norfolk City Public Schools (NCPS) that will use a Design Based Implementation Research (DBIR) process to refine an effective PD model to support elementary teachers in inclusive classrooms in integrating recently-mandated CS standards into math, science, and literacy instruction in ways accessible to students with high-incidence disabilities (e.g. learning disabilities, emotional or behavioral disorders, mild intellectual disability, high functioning autism, and attention-deficit hyperactivity disorder). Theoretically and conceptually, the research will contribute to pedagogical strategies and approaches for integrating computer science and understanding how elementary teachers understand CS standards and approach CS integration. The Universal Design for Learning instructional framework will guide the implementation team and partner educators to design instruction to meet the needs of all learners, including those with disabilities, by addressing barriers to learning. The research will examine CS sequencing through grade-appropriate progressions by drawing on the expert insights of elementary classroom teachers. The project will also develop disciplinary literacy through CS as students use various strategies to read, write, and communicate their understanding within and among various disciplines. Combined, these efforts will help answer the overarching question: How do multiple stakeholders collaboratively refine and develop effective and sustainable PD on the integration of computer science in K-5 inclusive classrooms to support students with high incidence disabilities? The project will collect data via interviews with teachers, field notes from observations, teacher assessment & survey results, verbal protocol data, teacher lesson plans, video data, and student work samples across 6-week iterative cycles as part of the DBIR process. Analysis of interviews, observations, lesson plans, and verbal protocol think-alouds in each cycle will rely on the constant-comparative qualitative method. Analysis of data from pre-post measures will include descriptive statistics and paired-sample t-test to measure the growth of teachers through the PD.
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.
