To transform undergraduate biology education, faculty need to provide opportunities for students to engage in the process of science. The rise of research approaches using next-generation (NextGen) sequencing has been impressive, but incorporation of such approaches into the undergraduate curriculum remains a major challenge. In this paper, we report proceedings of a National Science Foundation–funded workshop held July 11–14, 2011, at Juniata College. The purpose of the workshop was to develop a regional research coordination network for undergraduate biology education (RCN/UBE). The network is collaborating with a genome-sequencing core facility located at Pennsylvania State University (University Park) to enable undergraduate students and faculty at small colleges to access state-of-the-art sequencing technology. We aim to create a database of references, protocols, and raw data related to NextGen sequencing, and to find innovative ways to reduce costs related to sequencing and bioinformatics analysis. It was agreed that our regional network for NextGen sequencing could operate more effectively if it were partnered with the Genome Consortium for Active Teaching (GCAT) as a new arm of that consortium, entitled GCAT-SEEK(quence). This step would also permit the approach to be replicated elsewhere.

This study evaluates the impact of an independent postmidterm question analysis exercise on the ability of students to answer subsequent exam questions on the same topics. It was conducted in three sections (∼400 students/section) of introductory biology. Graded midterms were returned electronically, and each student was assigned a subset of questions answered incorrectly by more than 40% of the class to analyze as homework. The majority of questions were at Bloom's application/analysis level; this exercise therefore emphasized learning at these higher levels of cognition. Students in each section answered final exam questions matched by topic to all homework questions, providing a within-class control group for each question. The percentage of students who correctly answered the matched final exam question was significantly higher (p < 0.05) in the Topic Analysis versus Control Analysis group for seven of 19 questions. We identified two factors that influenced activity effectiveness: 1) similarity in topic emphasis of the midterm–final exam question pair and 2) quality of the completed analysis homework. Our data suggest that this easy-to-implement exercise will be useful in large-enrollment classes to help students develop self-regulated learning skills. Additional strategies to help introductory students gain a broader understanding of topic areas are discussed.

Few, if any, educational interventions intended to increase underrepresented minority (URM) graduate students in biological and behavioral sciences are informed by theory and research on career persistence. Training and Education to Advance Minority Scholars in Science (TEAM-Science) is a program funded by the National Institute of General Medical Sciences at the University of Wisconsin–Madison with the twin goals of increasing the number of URM students entering and completing a PhD in BBS and increasing the number of these students who pursue academic careers. A framework for career development in graduate research training is proposed using social cognitive career theory. Based on this framework, TEAM-Science has five core components: 1) mentor training for the research advisor, 2) eight consensus-derived fundamental competencies required for a successful academic career, 3) career coaching by a senior faculty member, 4) an individualized career development plan that aligns students’ activities with the eight fundamental competencies, and 5) a strengths, weaknesses, opportunities, and threats personal career analysis. This paper describes the theoretical framework used to guide development of these components, the research and evaluation plan, and early experience implementing the program. We discuss the potential of this framework to increase desired career outcomes for URM graduate trainees in mentored research programs and, thereby, strengthen the effectiveness of such interventions on participants’ career behaviors.

The C.R.E.A.T.E. (Consider, Read, Elucidate hypotheses, Analyze and interpret data, Think of the next Experiment) method uses intensive analysis of primary literature in the undergraduate classroom to demystify and humanize science. We have reported previously that the method improves students’ critical thinking and content integration abilities, while at the same time enhancing their self-reported understanding of “who does science, and why.” We report here the results of an assessment that addressed C.R.E.A.T.E. students’ attitudes about the nature of science, beliefs about learning, and confidence in their ability to read, analyze, and explain research articles. Using a Likert-style survey administered pre- and postcourse, we found significant changes in students’ confidence in their ability to read and analyze primary literature, self-assessed understanding of the nature of science, and epistemological beliefs (e.g., their sense of whether knowledge is certain and scientific talent innate). Thus, within a single semester, the inexpensive C.R.E.A.T.E. method can shift not just students’ analytical abilities and understanding of scientists as people, but can also positively affect students’ confidence with analysis of primary literature, their insight into the processes of science, and their beliefs about learning.

Our study explored the prospects and limitations of using machine-learning software to score introductory biology students’ written explanations of evolutionary change. We investigated three research questions: 1) Do scoring models built using student responses at one university function effectively at another university? 2) How many human-scored student responses are needed to build scoring models suitable for cross-institutional application? 3) What factors limit computer-scoring efficacy, and how can these factors be mitigated? To answer these questions, two biology experts scored a corpus of 2556 short-answer explanations (from biology majors and nonmajors) at two universities for the presence or absence of five key concepts of evolution. Human- and computer-generated scores were compared using kappa agreement statistics. We found that machine-learning software was capable in most cases of accurately evaluating the degree of scientific sophistication in undergraduate majors’ and nonmajors’ written explanations of evolutionary change. In cases in which the software did not perform at the benchmark of “near-perfect” agreement (kappa > 0.80), we located the causes of poor performance and identified a series of strategies for their mitigation. Machine-learning software holds promise as an assessment tool for use in undergraduate biology education, but like most assessment tools, it is also characterized by limitations.

Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning.

Classroom response systems, or clickers, have become pedagogical staples of the undergraduate science curriculum at many universities. In this study, the effectiveness of clickers in promoting problem-solving skills in a genetics class was investigated. Students were presented with problems requiring application of concepts covered in lecture and were polled for the correct answer. A histogram of class responses was displayed, and students were encouraged to discuss the problem, which enabled them to better understand the correct answer. Students were then presented with a similar problem and were again polled. My results indicate that those students who were initially unable to solve the problem were then able to figure out how to solve similar types of problems through a combination of trial and error and class discussion. This was reflected in student performance on exams, where there was a statistically significant positive correlation between grades and the percentage of clicker questions answered. Interestingly, there was no clear correlation between exam grades and the percentage of clicker questions answered correctly. These results suggest that students who attempt to solve problems in class are better equipped to solve problems on exams.

Biology student mastery regarding the mechanisms of diffusion and osmosis is difficult to achieve. To monitor comprehension of these processes among students at a large public university, we developed and validated an 18-item Osmosis and Diffusion Conceptual Assessment (ODCA). This assessment includes two-tiered items, some adopted or modified from the previously published Diffusion and Osmosis Diagnostic Test (DODT) and some newly developed items. The ODCA, a validated instrument containing fewer items than the DODT and emphasizing different content areas within the realm of osmosis and diffusion, better aligns with our curriculum. Creation of the ODCA involved removal of six DODT item pairs, modification of another six DODT item pairs, and development of three new item pairs addressing basic osmosis and diffusion concepts. Responses to ODCA items testing the same concepts as the DODT were remarkably similar to responses to the DODT collected from students 15 yr earlier, suggesting that student mastery regarding the mechanisms of diffusion and osmosis remains elusive.

This article describes an undergraduate lab exercise that demonstrates the importance of students thinking critically about what they see through a microscope. The students are given growth data from tip-growing organisms that suggest the cells grow in a pulsatile manner. The students then critique this data in several exercises that incorporate aspects of a problem-based learning approach, envisaging growth not just in two dimensions, but in three dimensions. For some cells, what appears to be pulsatile growth could also be explained by growth at a constant rate up and down in the z-axis. Depending on the diffraction pattern generated by the tip of the cell, this movement in the z-axis could go undetected. This raises the possibility that pulsatile growth seen in some species may be an artifact generated by the limitations of the light microscope. Students were subsequently asked to rate their awareness of the need to think critically about what they see through a microscope, using a scale of 1 (unaware) to 5 (very much aware). Prior to doing the lab exercise, the mean rating was 2.7; this increased to 4.4 after the lab. The students also indicated a likelihood of being more critical in their thinking in other aspects of their biology curriculum.