Teaching computational thinking to exceptional learners: lessons from two inclusive classrooms

Background and Context: Computational Thinking (CT) is a skill all students should learn. This requires using inclusive approaches to teach CT to a wide spectrum of students. However, strategies for teaching CT to students with exceptionalities are not well studied. Objective: This study draws on lessons learned in two fourth-grade classrooms - one an inclusive general education classroom including students with and without disabilities, the other an inclusive GATE classroom including students with and without giftedness - to illustrate how CT frameworks can inform inclusive CS instruction. Method: A comparative case study design integrating content analysis and first and second cycle coding of data was used to analyze teachers' instructional strategies using a CT framework. Data included transcriptions of audio-recorded classroom lessons, field notes, and conversations with teachers and students. Findings: While each teacher used different strategies, both were effective in developing students' CT. Explicit instruction provided students receiving special education services with needed structure for the complex tasks inherent to computing. Peer feedback facilitated independent computational practice opportunities for students receiving GATE. Implications: This study highlights how inclusive instructional practices can be assessed using a CT framework and leveraged to maximize learning and access to CT curricula for learners with exceptionalities.