students to discover the required steps themselves by constructing
a flowchart of the experimental manipulations – and instead
prompt them through a series of steps in the calculations. The
prompts (PowerPoint slides given in Appendix D) then became a
scaffolding, which the instructor shared with colleagues. One colleague implemented the switch; the other did not. Subsequently,
in the analysis of a complex midterm question, we observed a
marked difference between sections that was directly correlated
with exposure to the scaffolding (Figure 3). To eliminate the possibility that this difference was due to a baseline difference in students’ inherent abilities, pre-assessment mean scores were also
compared with a one-way ANOVA and revealed no significant difference between the three sections (p = 0.798). These data are consistent with the idea that in inquiry-based learning, students require
more guidance to successfully navigate complex data analysis problems, a process that requires higher-order cognitive skills encompassing the application of knowledge and critical thinking and
involving deep conceptual understanding (Zoller, 1993).
Finally, in 2015 and 2016 the instructor who taught at least
one section of this course each year also made a conscious effort
to engage in more non-content dialogue with students (Seidel et
al., 2015). This included building rapport with students and
within student teams, sharing personal experiences in research,
explaining pedagogical choices, and clarifying expectations. As a
result, this instructor realized a full recovery from our implementation dip. Other instructors, who have not been consistently
assigned to this course, have seen improvements since the implementation dip, but not a full recovery.
Our experiences underscore the value of evidence-based curriculum
development and revision ( i.e., scientific teaching; Handelsman
et al., 2004). In addition to using evidence-based pedagogies, our
use of assessment data to drive interventions in the learning process
were crucial in our recovery from an implementation dip (Fulan,
2007). Our experiences also attest to an essential feature of guided
inquiry: since different levels of guidance are needed at different
stages, its success is dependent on high-quality student–faculty
and student–student partnerships. Our experiences demonstrate
the importance of persistence in scientific teaching practices in
order to find the appropriate level of guidance. In terms of
educational theory, our scaffolding reduces the extraneous cognitive load (challenges posed by instructional choices), making
it easier for students to manage the intrinsic cognitive load
(imposed by the complexity of the calculations), and resulting
in a higher germane cognitive load that facilitates effective learning (Sweller, 1988).
Reading the literature about inquiry-based learning, it is easy to
get the impression that “if you build it, they will come.” But perhaps the comparison between traditional didactic teaching and
inquiry-based learning is more like dancing. Instead of insisting
that the role of the instructor is to lead and the role of the students
is to follow, the reality is that each has to constantly pay close
attention to the other. For the dance to be beautiful, both have to
practice working together. If one dancer tries to do it all, then there
is no dance. “It takes two to tango.”
This project was funded by the National Science Foundation (TUES
grant no. 1140767). We are indebted to our biology department
colleagues for their contributions in the planning and implementation of the revised lab curricula. We also thank our Calvin College
collaborators – Paul Moes and Randall Pruim – for assistance with
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