Active-learning strategies can improve science, technology, engineering, and mathematics (STEM) undergraduates’ abilities to learn fundamental concepts and skills. However, the results instructors achieve vary substantially. One explanation for this is that instructors commonly implement active learning differently than intended. An important factor affecting how instructors implement active learning is knowledge of teaching and learning. We aimed to discover knowledge that is important to effective active learning in large undergraduate courses. We developed a lesson-analysis instrument to elicit teacher knowledge, drawing on the theoretical construct of teacher noticing. We compared the knowledge used by expert (n = 14) and novice (n = 29) active-learning instructors as they analyzed lessons. Experts and novices differed in what they noticed, with experts more commonly considering how instructors hold students accountable, topic-specific student difficulties, whether the instructor elicited and responded to student thinking, and opportunities students had to generate their own ideas and work. Experts were also better able to support their lesson analyses with reasoning. This work provides foundational knowledge for the future design of preparation and support for instructors adopting active learning. Improving teacher knowledge will improve the implementation of active learning, which will be necessary to widely realize the potential benefits of active learning in undergraduate STEM.

Vol. 17, No. 1

March 01, 2018

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Downloads: 1350

Citations: 33

History

Submitted: 11 August 2017

Revised: 13 November 2017

Accepted: 8 December 2017

Information

© 2018 A. J. Auerbach et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Thank you to our research participants, including those who were part of pilot studies, without whom this work would not be possible. We also owe a debt of gratitude to the instructors who were willing to have their classroom filmed and shown to other college instructors. Thank you to the University of Georgia BERG group, especially Julie Stanton and Jennifer Thompson, for their continuous feedback and support. Thanks also to our lab colleagues for inspiration, feedback, and support. Thank you to undergraduate assistants who contributed to this project, including Logan Gin, Aarushi Lal, Adebimpe Atanda, and Andrew Potocko. Thank you to the monitoring editor and anonymous reviewers for insightful feedback that helped us improve our manuscript. Partial support for this work was provided by the National Science Foundation’s Improving Undergraduate STEM (IUSE) program under award No. 1504904. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Partial funding was provided by the University of Georgia Office of STEM Education mini-grant.

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