The research questions we’ll be following (see below) address whether students enrolled in the Science+C courses demonstrate higher levels of science knowledge and computational thinking skills than students who are enrolled in the same science topic courses but without computational enhancement. Note that the research will be studying the effectiveness of the Science+C curriculum–not evaluating teachers’ and students’ performance.
Teachers and students: Science+C teachers will receive specialized, year-long professional development to increase their capacity to integrate computational models into their biology, chemistry, and physics curricula. In addition, the PD will help them decode and explain how scientific ideas are embedded within the models. Students participating in this enhanced science pathway will gain computer science and computational thinking skills that can benefit them in future endeavors, both college and career. These will be in the intervention group. Importantly, additional teachers and their students will participate in the research study as the comparison group. The comparison group will engage in regular, “business-as-usual” science teaching and learning.
Tools of the Research: The curriculum itself will be used as a tool for both building knowledge and facilitating learning, where students are encouraged to take more control of their own learning process. Our research team will collect data about the curriculum from students and teachers in both the intervention and comparison groups in the fall (baseline) and in the spring (year-end), through unit assessments that will also provide valuable information for the teachers on where students are in their learning. Data analyses will determine if the intervention group acquired computational thinking and science skills and knowledge above and beyond what the comparison group did over the course of the school year.
Science knowledge will be measured through a modified Trends in International Mathematics and Science Study (TIMSS) assessment, which combines multiple choice question items from recent TIMSS released items. We will measure gains in computational thinking using the Knowledge and Skills in Computational Thinking (KS-CT) tool. The KS-CT was developed and validated through the NSF-funded New Mexico Computer Science for All (NM-CSforAll) project. It is a 30-item multiple-choice questionnaire that measures CT skills, including modeling and simulation, programming, tracing, debugging, and decoding. Last, we will be integrating Massachusetts standardized test results (Massachusetts Comprehensive Assessment System – MCAS) in biology, chemistry, and physics to study the impact on student scores.
