“…At the same time, the builders highlighted thoughts and trends seen elsewhere, including wanting to collect as much data as possible (Williamson, 2017), a focus on computational approaches at times over theory-building (Wise & Cui, 2018), and celebrating big data as bringing better science, better education and rapid innovation (Crawford, 2014). We did not, however, find a uniform zeal for data collection at all costs, predictive analytics as an automatic service, and algorithmic processing over human insight, major concerns about the future of big data science (Williamson, Builders see themselves as caring about learners being seen and empowered as human beings and at the same time as being aware of the limitations of the technologies they are building to be able to do that and yet they keep building because they believe in the opportunity for better science and service at scale.…”