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Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. [Linda Casola served as the Rapporteur for this report. Additional support for this report was received from the Gordon and Betty Moore Foundation.]

This paper describes the improvement of a series of lab courses in electrical engineering at the University of Twente in Enschede, the Netherlands. Five differing courses of lab classes (measuring instruments and network analysis, basic digital circuits, basic circuits of electronics, electronic functions, and physics measuring methods and systems) seemed unrelated to students, although in all classes one of the main objectives was to learn to experiment in a systematic way. Faculty, teaching assistants, and administrators in the department seemed unable to change the situation. A systematic approach to change was developed and implemented that focused on four aspects of professional behavior: rational use of knowledge; personal directed interaction with people; operationally obtaining some results; and fulfilling conditions by provision with means. This led to changes in the procedures used in lab write-ups and student notebooks, the development of a general lab guide, and regular meetings among faculty and teaching assistants in the five courses. An appendix contains the framework for lab write-ups. (MDM)