replication and up-scaling • A way to describe “invisible” work in education practice • A way to make it clear that we need to “design across levels of a system”
design areas Make visible existing infrastructures Plan for possible points of infrastructuring Rally for coherence-making activities Orchestrate meta-design and capacity building Evaluate infrastructures continually
Data Science Education Vision • Integrate data science across subject areas • Foreground justice in data science practices Partnership • Synergies with district goals • Co-design workshops with teachers Technology • The DataX platform
key social actors and spheres of design activities • Users à Active, creative designers • Design before-use and design in-use In DataX project: • Teachers as co-designers • Design components including curriculum, technology, and pedagogies
for possible points of infrastructuring • When an infrastructure is intentionally worked on • Moments of breakdowns • Anticipate future needs for repair In DataX project: • Make plans to observe the resistances • Anticipate significant refinement after pilots (Pipek & Wulf, 2009)
for coherence- making activities • Increase the fit between innovation and organizational practice • Encourage perpetual reconfiguration of power structures In DataX project: • Work with district interests in culturally responsive teaching, NGSS, etc. • Integrate data science in science and social studies in a non-competing way Photo Credit
meta-design and capacity building • Designing for design • Involve everyone in theoretical work • Cultivate a sense of empowerment In DataX project: • Digital systems for collaboration with teachers • Teacher PD opportunities Photo Credit
conversation http://ki.pubpub.org/ and many others … • To critique the IMPROV framework • To investigate innovations from an infrastructuring lens • To infrastructure new innovations