Implementing recommendations for introductory biology by writing a new textbook

Abstract

We redesigned the undergraduate introductory biology course by writing a new textbook (Integrating Concepts in Biology [ICB]) that follows first principles of learning. Our approach emphasizes primary data interpretation and the utility of mathematics in biology, while de-emphasizing memorization. This redesign divides biology into five big ideas (information, evolution, cells, emergent properties, homeostasis), addressing each at five levels of organization (molecules, cells, organisms, populations, ecological systems). We compared our course outcomes with two sections that used a traditional textbook and were taught by different instructors. On data interpretation assessments administered periodically during the semester, our students performed better than students in the traditional sections (p = 0.046) and exhibited greater improvement over the course of the semester (p = 0.015). On factual content assessments, our students performed similarly to students in the other sections (p = 0.737). Pre- and postsemester assessment of disciplinary perceptions and self-appraisal indicate that our students acquired a more accurate perception of biology as a discipline and may have developed a more realistic evaluation of their scientific abilities than did the control students (p < 0.05). We conclude that ICB improves critical thinking, metacognition, and disciplinary perceptions without compromising content knowledge in introductory biology.

Figure 1.

Structural organization of ICB and course content with five big ideas (green pentagons) and five levels of size scale for each big idea.

Figure 2.

Timeline for administration of assessments described in this study. A full set of assessment questions is available in the Supplemental Material.

Figure 3.

Content knowledge testing. In the Fall of 2010, students in all three sections answered 16 multiple-choice questions as part of graded tests. In April 2011, the same students were asked a subset of the same questions. Percent correct is the average of student scores. Error bars represent SE of the mean.

Figure 4.

Data interpretation testing. In the Fall of 2010, students in all three sections took an ungraded assessment of data interpretation skills during laboratory sessions. (A) Percent correct is the average of aggregate student scores in ICB or traditional sections. Error bars represent SE of the mean. Main effect of teaching approach was significant (p = 0.046), with significant differences in performance on both quiz 3 and quiz 4, as indicated. (B) Regression models of performance on data interpretation assessments are shown as linear trend lines. Data points displayed are the same averages depicted in part A, but the regression lines are based on individual student scores. p values denote the likelihood that scores remained unchanged over time (i.e., if trend line had zero slope).