My problem of practice is to to examine how artificial intelligence and natural language understanding might be used to build conversation-based assessments that allow stakeholders to gauge how well students can construct explanations, defend claims, and analyze data, more. In the context of examining how to assess student knowledge in a three-dimensional science classroom, I hope to explore ways that new technologies may broaden our perspective of what constitutes an assessment, as well as how such assessments may provide actionable data about what students genuinely know and can accomplish. The use of emerging technologies within this context may very well lead to a consistent, scalable assessment option.
As a practitioner standing squarely at the crossroads of science instruction and technology integration in the classroom, I am uniquely suited to explore a design-based technology problem of practice. I plan to document an iterative design process in which I will be designing, prototyping, piloting, and redesigning an interactive, artificially intelligent form of assessment. In doing so, I hope to explore both the possibilities and limitations of such assessments and ultimately contribute to the conversations about how to assess that which cannot be distilled into traditional multiple choice questions.
This strand will serve as a general summary of my background in two key areas: 1) the productive, useful leveraging of educational technologies and 2) science instruction that situates young people as scientists in constructivist, inquiry-based classrooms. I've divided Strand A into the following sections with the purpose of thoroughly exploring the pieces of my journey as an educator and graduate student that have led me to the above problem of practice.