Deep Learning in Introductory Physics

A volume in Science & Engineering Education Sources

Deep Learning in Introductory Physics: Exploratory Studies of ModelâBased Reasoning is concerned with
the broad question of how students learn physics in a modelâcentered classroom. The diverse,
creative, and sometimes unexpected ways students construct models, and deal with intellectual
conflict, provide valuable insights into student learning and cast a new vision for physics teaching.
This book is the first publication in several years to thoroughly address the “coherence versus
fragmentation” debate in science education, and the first to advance and explore the hypothesis that
deep science learning is regressive and revolutionary. Deep Learning in Introductory Physics also contributes to a growing literature
on the use of history and philosophy of science to confront difficult theoretical and practical issues in science teaching, and
addresses current international concern over the state of science education and appropriate standards for science teaching and
learning.
The book is divided into three parts. Part I introduces the framework, agenda, and educational context of the book. An initial study
of student modeling raises a number of questions about the nature and goals of physics education. Part II presents the results of
four exploratory case studies. These studies reproduce the results of Part I with a moreâdiverse sample of students; under new
conditions (a public debate, peer discussions, and group interviews); and with new research prompts (modelâbuilding software,
bridging tasks, and elicitation strategies). Part III significantly advances the emergent themes of Parts I and II through historical
analysis and a review of physics education research.