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Many conversations surrounding improvement of large-enrollment college science, technology, engineering & mathematics (STEM) courses focus primarily (or solely) on changing instructional practices. By reducing dynamic, complex learning environments to collections of teaching methods, we neglect other meaningful parts of a course ecosystem (e.g., curriculum, assessments). Here, we advocate extending STEM education reform conversations beyond “active versus passive learning.” We argue communities of researchers and instructors would be better served if what we teach and assess was discussed alongside how we teach. To enable nuanced conversations about the characteristics of learning environments that support students in explaining phenomena, we defined a model of college STEM learning environments which attends to the intellectual work emphasized and rewarded on exams (i.e., assessment emphasis), what is taught in whole-class meetings (i.e., instructional emphasis), and how those meetings are enacted (i.e., instructional practices). We subsequently characterized three distinct chemistry courses and qualitatively examined the characteristics of chemistry learning environments that effectively supported students in explaining why a beaker of water warms as a white solid dissolves. Furthermore, we quantitatively investigated the extent to which measures of incoming preparation explained variance in students’ explanations relative to enrollment in each learning environment. Our findings demonstrate that learning environments that effectively supported learners in explaining dissolution emphasized how and why salts dissolve in-class and on assessments. Changing teaching methods in an otherwise traditionally structured course (i.e., a course organized by topics that primarily assesses math and recall) did not appear to impact the sophistication of students’ explanations. Additionally, we observed that learning environment enrollment explained substantially more of the variance observed in students’ explanations than measures of precollege math preparation. This finding suggests that emphasizing and rewarding the construction of causal accounts for phenomena in-class and on assessments may support more equitable achievement.
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This content will become publicly available on February 26, 2027
Not simply “active”: identifying types of active-learning tasks in introductory biology
ABSTRACT Active learning is a phrase that lacks clear definition, which has hampered researchers’ efforts to investigate the nuances of effectiveness and instructors’ efforts to capitalize on potential benefits for students. One way to advance our understanding of “active learning” is assessing by the type of intellectual work that in-class activities require of students. We systematically analyzed in-class work opportunities created for students in 55 introductory biology courses around the United States, each of which used active learning. We did so by adapting an observation approach grounded in the ICAP framework and analyzing classroom videos in 15-s segments. Instructors devoted about a quarter of class time to student work time, on average, but this varied widely. About half of these student work opportunities focused on recall, and half required students to generate answers beyond what had been presented to them, which can foster deeper learning and better transfer than recall alone. The ratio of these levels of intellectual work varied considerably across courses. We also tested whether course- and instructor-level factors predicted the amount and level of active-learning opportunities and found no significant relationships. This work provides a striated definition of active learning that will be useful to researchers studying active-learning outcomes and instructors aiming to harness learning benefits for their students.
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- Award ID(s):
- 1845886
- PAR ID:
- 10678668
- Editor(s):
- Fonseca, Antonio Pedro
- Publisher / Repository:
- American Society for MIcrobiology
- Date Published:
- Journal Name:
- Journal of Microbiology & Biology Education
- ISSN:
- 1935-7877
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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