Designing Activities to Teach Higher-Order Skills: How Feedback and Constraint Affect Learning of Experimental Design.

Active learning approaches to biology teaching, including simulation-based activities, are known to enhance student learning, especially of higher-order skills; nonetheless, there are still many open questions about what features of an activity promote optimal learning. Here we designed three versions of a simulation-based tutorial called Understanding Experimental Design that asks students to design experiments and collect data to test their hypotheses. The three versions vary the experimental design task along the axes of feedback and constraint, where constraint measures how much choice students have in performing a task. Using a variety of assessments, we ask whether each of those features affects student learning of experimental design. We find that feedback has a direct positive effect on learning. We further find that small changes in constraint have only subtle and mostly indirect effects on learning. This work suggests that designers of tools for teaching higher-order skills should strive to include feedback to increase impact and may feel freer to vary the degree of constraint within a range to optimize for other features such as the ability to provide immediate feedback and time-on-task.

Designing a Simulation Lab: The Process that Led to Action Potentials Explored and Extended, Two Simulation-Based Neurobiology Labs.

Simulations have long played an important role in neurobiology education. This paper describes the design-research process that led to development of two popular simulation-based neurobiology modules used in undergraduate biology classes. Action Potentials Explored, and the more in-depth and quantitative Action Potentials Extended, are the third generation of neurobiology teaching simulations the author has helped develop. The paper focuses on how we used the idea of constraining simulations as a way of tuning the modules to different student populations. Other designers of interactive educational materials may also find constraint a useful lens through which to view designs.

Automated Writing Assessments Measure Undergraduate Learning after Completion of a Computer-Based Cellular Respiration Tutorial.

The focus of biology education has shifted from memorization to conceptual understanding of core biological concepts such as matter and energy relationships. To examine undergraduate learning about matter and energy, we incorporated constructed-response (CR) questions into an interactive computer-based tutorial. The objective of this tutorial is to teach students about matter and energy and help dispel common misconceptions through the context of cellular respiration. We used a constructed-response classifier (CRC) tool to categorize ideas in responses to three CR questions and measure changes in student thinking about cellular respiration. Our data set includes 841 undergraduates from 19 geographically diverse institutions including two-year colleges, primarily undergraduate institutions, and research-intensive colleges and universities. We found students from all institution types included more scientific ideas in CRs post-tutorial. Students used an average of 2.1 ideas in CRs and frequently used both scientific and developing ideas. We found this mixed thinking persisted after the tutorial regardless of institution type. Students' multiple-choice (MC) selections were correlated with their CRs, but CRs revealed more mixed thinking than would be inferred from MC responses. Our study shows a CRC tool can measure student learning after a computer-based tutorial and provides more complete information than MC responses.

A new assessment to monitor student performance in introductory neurophysiology: Electrochemical Gradients Assessment Device.

The basis for understanding neurophysiology is understanding ion movement across cell membranes. Students in introductory courses recognize ion concentration gradients as a driving force for ion movement but struggle to simultaneously account for electrical charge gradients. We developed a 17-multiple-choice item assessment of students' understanding of electrochemical gradients and resistance in neurophysiology, the Electrochemical Gradients Assessment Device (EGAD). We investigated the internal evidence validity of the assessment by analyzing item characteristic curves of score probability and student ability for each question, and a Wright map of student scores and ability. We used linear mixed-effect regression to test student performance and ability. Our assessment discriminated students with average ability (weighted likelihood estimate: -2 to 1.5 Θ); however, it was not as effective at discriminating students at the highest ability (weighted likelihood estimate: >2 Θ). We determined the assessment could capture changes in both assessment scores (model r2 = 0.51, P < 0.001, n = 444) and ability estimates (model r2 = 0.47, P < 0.001, n = 444) after a simulation-based laboratory and course instruction for 222 students. Differential item function analysis determined that each item on the assessment performed equitably for all students, regardless of gender, race/ethnicity, or economic status. Overall, we found that men scored higher (r2 = 0.51, P = 0.014, n = 444) and had higher ability scores (P = 0.003) on the EGAD assessment. Caucasian students of both genders were positively correlated with score (r2 = 0.51, P < 0.001, n = 444) and ability (r2 = 0.47, P < 0.001, n = 444). Based on the evidence gathered through our analyses, the scores obtained from the EGAD can distinguish between levels of content knowledge on neurophysiology principles for students in introductory physiology courses.

Short lesson plan associated with increased acceptance of evolutionary theory and potential change in three alternate conceptions of macroevolution in undergraduate students.

Undergraduates commonly harbor alternate conceptions about evolutionary biology; these alternate conceptions often persist, even after intensive instruction, and may influence acceptance of evolution. We interviewed undergraduates to explore their alternate conceptions about macroevolutionary patterns and designed a 2-h lesson plan to present evidence that life has evolved. We identified three alternate conceptions during our interviews: that newly derived traits would be more widespread in extant species than would be ancestral traits, that evolution proceeds solely by anagenesis, and that lineages must become more complex over time. We also attempted to measure changes in the alternate conceptions and levels of acceptance of evolutionary theory in biology majors and nonmajors after exposure to the lesson plan. The instrument used to assess understanding had flaws, but our results are suggestive of mixed effects: we found a reduction in the first alternate conception, no change in the second, and reinforcement of the third. We found a small, but significant, increase in undergraduate acceptance of evolutionary theory in two trials of the lesson plan (Cohen's d effect sizes of 0.51 and 0.19). These mixed results offer guidance on how to improve the lesson and show the potential of instructional approaches for influencing acceptance of evolution.

Time to evolve? Potential evolutionary responses of fraser river sockeye salmon to climate change and effects on persistence.

Evolutionary adaptation affects demographic resilience to climate change but few studies have attempted to project changes in selective pressures or quantify impacts of trait responses on population dynamics and extinction risk. We used a novel individual-based model to explore potential evolutionary changes in migration timing and the consequences for population persistence in sockeye salmon Oncorhynchus nerka in the Fraser River, Canada, under scenarios of future climate warming. Adult sockeye salmon are highly sensitive to increases in water temperature during their arduous upriver migration, raising concerns about the fate of these ecologically, culturally, and commercially important fish in a warmer future. Our results suggest that evolution of upriver migration timing could allow these salmon to avoid increasingly frequent stressful temperatures, with the odds of population persistence increasing in proportion to the trait heritability and phenotypic variance. With a simulated 2°C increase in average summer river temperatures by 2100, adult migration timing from the ocean to the river advanced by ∼10 days when the heritability was 0.5, while the risk of quasi-extinction was only 17% of that faced by populations with zero evolutionary potential (i.e., heritability fixed at zero). The rates of evolution required to maintain persistence under simulated scenarios of moderate to rapid warming are plausible based on estimated heritabilities and rates of microevolution of timing traits in salmon and related species, although further empirical work is required to assess potential genetic and ecophysiological constraints on phenological adaptation. These results highlight the benefits to salmon management of maintaining evolutionary potential within populations, in addition to conserving key habitats and minimizing additional stressors where possible, as a means to build resilience to ongoing climate change. More generally, they demonstrate the importance and feasibility of considering evolutionary processes, in addition to ecology and demography, when projecting population responses to environmental change.

Evaluating two approaches to helping college students understand evolutionary trees through diagramming tasks.

To understand evolutionary theory, students must be able to understand and use evolutionary trees and their underlying concepts. Active, hands-on curricula relevant to macroevolution can be challenging to implement across large college-level classes where textbook learning is the norm. We evaluated two approaches to helping students learn macroevolutionary topics. Treatment 1 is a laboratory for the software program EvoBeaker designed to teach students about evolutionary trees. We tested Treatment 1 among nine college-level biology classes and administered pre/posttests to assess learning gains. We then sought to determine whether the learning gains from Treatment 1 were comparable to those derived from an alternate hands-on treatment, specifically the combination of a prerecorded lecture on DVD and paper-based activity based on Goldsmith's Great Clade Race (Treatment 2). Comparisons of pre- and posttests among participants using either Treatment 1 or 2 show large learning gains on some misconceptions and skills beyond knowledge gained from reading standard textbook entries. Both treatments performed equivalently in overall learning gains, though both had areas where they performed better or worse. Furthermore, gains among students who used Treatment 1 representing a wide range of universities suggest that outcomes are potentially applicable to a variety of "real-world" biology classes.

How effective are simulated molecular-level experiments for teaching diffusion and osmosis?

Diffusion and osmosis are central concepts in biology, both at the cellular and organ levels. They are presented several times throughout most introductory biology textbooks (e.g., Freeman, 2002), yet both processes are often difficult for students to understand (Odom, 1995; Zuckerman, 1994; Sanger et al., 2001; and results herein). Students have deep-rooted misconceptions about how diffusion and osmosis work, especially at the molecular level. We hypothesized that this might be in part due to the inability to see and explore these processes at the molecular level. In order to investigate this, we developed new software, OsmoBeaker, which allows students to perform inquiry-based experiments at the molecular level. Here we show that these simulated laboratories do indeed teach diffusion and osmosis and help overcome some, but not all, student misconceptions.

Ingeneue: a versatile tool for reconstituting genetic networks, with examples from the segment polarity network.

Here we describe a software tool for synthesizing molecular genetic data into models of genetic networks. Our software program Ingeneue, written in Java, lets the user quickly turn a map of a genetic network into a dynamical model consisting of a set of ordinary differential equations. We developed Ingeneue as part of an ongoing effort to explore the design and evolvability of genetic networks. Ingeneue has three principal advantages over other available mathematical software: it automates instantiation of the same network model in each cell in a 2-D sheet of cells; it constructs model equations from pre-made building blocks corresponding to common biochemical processes; and it automates searches through parameter space, sensitivity analyses, and other common tasks. Here we discuss the structure of the software and some of the issues we have dealt with. We conclude with some examples of results we have achieved with Ingeneue for the Drosophila segment polarity network.

Robustness, flexibility, and the role of lateral inhibition in the neurogenic network.

BACKGROUND: Many gene networks used by developing organisms have been conserved over long periods of evolutionary time. Why is that? We showed previously that a model of the segment polarity network in Drosophila is robust to parameter variation and is likely to act as a semiautonomous patterning module. Is this true of other networks as well? RESULTS: We present a model of the core neurogenic network in Drosophila. Our model exhibits at least three related pattern-resolving behaviors that the real neurogenic network accomplishes during embryogenesis in Drosophila. Furthermore, we find that it exhibits these behaviors across a wide range of parameter values, with most of its parameters able to vary more than an order of magnitude while it still successfully forms our test patterns. With a single set of parameters, different initial conditions (prepatterns) can select between different behaviors in the network's repertoire. We introduce two new measures for quantifying network robustness that mimic recombination and allelic divergence and use these to reveal the shape of the domain in the parameter space in which the model functions. We show that lateral inhibition yields robustness to changes in prepatterns and suggest a reconciliation of two divergent sets of experimental results. Finally, we show that, for this model, robustness confers functional flexibility. CONCLUSIONS: The neurogenic network is robust to changes in parameter values, which gives it the flexibility to make new patterns. Our model also offers a possible resolution of a debate on the role of lateral inhibition in cell fate specification.

Variation Thresholds for Extinction and Their Implications for Conservation Strategies.

We examine the degree to which fitting simple dynamic models to time series of population counts can predict extinction probabilities. This is both an active branch of ecological theory and an important practical topic for resource managers. We introduce an approach that is complementary to recently developed techniques for estimating extinction risks (e.g., diffusion approximations) and, like them, requires only count data rather than the detailed ecological information available for traditional population viability analyses. Assuming process error, we use four different models of population growth to generate snapshots of population dynamics via time series of the lengths commonly available to ecologists. We then ask to what extent we can identify which of several broad classes of population dynamics is evident in the time series snapshot. Along the way, we introduce the idea of "variation thresholds," which are the maximum amount of process error that a population may withstand and still have a specified probability of surviving for a given length of time. We then show how these thresholds may be useful to both ecologists and resource managers, particularly when dealing with large numbers of poorly understood species, a common problem faced by those designing biodiversity reserves.