Social scientists and educators have long recognized that educations and careers are sequential phenomena, but until very recently it has been difficult for them to observe these sequences at scale.
Digital technologies change that. Online platforms make it possible to observe how thousands or millions of students process the same courses and curriculums. Aggregate data describing career trajectories of entire populations can give insight for identifying talent and navigating transitions. Parsing these data is now highly tractable by computation.
Social science needs to catch up. Doing so will require (a) shared heuristics for computationally reducing sequences into tractable types (b) attention to the contextual, iterative and extra-rational features of human consideration and choice. I report on progress toward (a) and assemble a toolkit for (b) from classic and contemporary insights of organization science, decision theory and social psychology.
Mitchell L Stevens is Professor of Education and (by courtesy) Sociology at Stanford University, where he also co-leads the Stanford Pathways Lab. He studies educational decision making, the quantification of academic performance, and the political economy of higher education in the US and worldwide.
The author of award-winning studies of home education and selective college admissions, his most recent books are Remaking College: The Changing Ecology of Higher Education and Seeing the World: How US Universities Make Knowledge in a Global Era. With Martin Kurzweil, he co-convened the projects An Applied Science for Working Learners and Responsible Use of Student Data in Higher Education.
He has written scholarly articles for a variety of academic journals and editorial for The Chronicle of Higher Education, Inside Higher Education, The New York Times, and other venues.
Mitchell will present a paper titled "Pathways: Building a Social Science of Sequences in Schools and Labor Markets" (partly attached).
The seminar will be held in English.
Major information: Elisa Villani (e.villani@unibo.it).