Louise S. Mead

Biology Undergraduates’ Misconceptions about Genetic Drift

This study explores biology undergraduates’ misconceptions about genetic drift. We use qualitative and quantitative methods to describe students’ definitions, identify common misconceptions, and examine differences before and after instruction on genetic drift. We identify and describe five overarching categories that include 16 distinct misconceptions about genetic drift. The accuracy of students’ conceptions ranges considerably, from responses indicating only superficial, if any, knowledge of any aspect of evolution to responses indicating knowledge of genetic drift but confusion about the nuances of genetic drift. After instruction, a significantly greater number of responses indicate some knowledge of genetic drift (p = 0.005), but 74.6% of responses still contain at least one misconception. We conclude by presenting a framework that organizes how students’ conceptions of genetic drift change with instruction. We also articulate three hypotheses regarding undergraduates’ conceptions of evolution in general and genetic drift in particular. We propose that: 1) students begin with undeveloped conceptions of evolution that do not recognize different mechanisms of change; 2) students develop more complex, but still inaccurate, conceptual frameworks that reflect experience with vocabulary but still lack deep understanding; and 3) some new misconceptions about genetic drift emerge as students comprehend more about evolution.

The Genetic Drift Inventory: A Tool for Measuring What Advanced Undergraduates Have Mastered about Genetic Drift

The Genetic Drift Inventory is a multiple true–false format concept inventory consisting of 22 statements. It tests how well upper-division undergraduate biology students grasp four key concepts, while simultaneously testing for the presence of six misconceptions.

Factors influencing minority student decisions to consider a career in evolutionary biology

BackgroundWithout an understanding of evolution, members of the public are unlikely to fully grasp many important issues necessary for the understanding science. In addition, evolutionary science plays an important role in advancing many other STEM disciplines. In stark contrast to the importance of the evolutionary sciences, is its enigmatic acceptance by the general American public. This acceptance is also not uniform within African American, Hispanic, and American Indian populations, who show higher rates of rejection of evolutionary reasoning. In an effort to advance our scientific community, it is imperative that we recruit highly quality students from an ever-increasing diverse population. Thus, the field is failing to attract and maintain the diversity desired in America’s scientific workforce with the above-mentioned minority groups, which are even further underrepresented in evolutionary science.MethodsTo examine why underrepresented minorities may not choose careers in evolutionary sciences, we surveyed 184 people who have chosen to pursue a career in science. The two questions we examined were: (1) what factors influence the career choices of underrepresented minorities (URMs) interested in science? and (2) what factors influence these URM students to choose careers in other sub-disciplines in biology rather than careers in evolutionary science? A survey was created from previously published research, and our analysis examined statistical differences between different racial/ethnic groups.ResultsOur data suggest there are significant differences among racial/ethnic groups in factors that appear to influence their career paths, specifically African Americans and non-Puerto Rican Hispanic/Latino(a)s place greater emphasis on the presence of people of similar racial/ethnic background. Additionally we found differences between the URM groups in terms of their interest in, and understanding of, evolutionary biology; which appears to result in less likelihood of choosing careers in evolutionary science. And for some African Americans, reluctance to pursue evolutionary biology may be tied to holding misconceptions about evolution and higher levels of religiosity.ConclusionsOur current work is preliminary, but once there is a better understanding of why URMs do not pursue evolutionary science, strategic steps can be taken to overcome these barriers. When an inclusive culture is at work, a diverse scientific team becomes capable of producing a broad range of original and engaging ideas not possible among homogenous groups. Educators, researchers, and equality advocates will be able to target the specific causes of underrepresentation in the evolutionary sciences and improve representation of racial and ethnic minorities in evolutionary science, to the ultimate benefit of the greater scientific community and the world at large.

Overcoming Obstacles to Evolution Education: Why Bother Teaching Evolution in High School?

Evolution is a foundational organizing principle of the life sciences, and yet people still argue that it should be taught only in college, urging that it’s not necessary, too controversial, or too difficult to teach evolution in high school. Faced with such arguments, teachers and administrators need to have responses. Moreover, they need to teach evolution so that the coverage of evolution in the K-12 curriculum reflects its central place in biology.

An Avida-ED digital evolution curriculum for undergraduate biology

We present an inquiry-based curriculum based on the digital evolution platform Avida-ED (http://avida-ed.msu.edu). We designed an instructional sequence and lab book consisting of an introduction to Avida-ED and a set of three lessons focused on specific evolutionary concepts. These served to familiarize students with experimental evolution and Avida-ED. Students then developed independent Avida-ED research projects to test their own questions. Curriculum design and implementation occurred over the course or two semesters, with a pilot implementation in the first semester, followed by curriculum revision and full implementation in the second semester. The curriculum was implemented in an undergraduate Introductory Cell and Molecular Biology course at a major research university. Full implementation of the curriculum in semester two involved the use of Avida-ED mainly in the teaching lab in parallel with a bacterial antibiotic resistance experimental research stream, allowing students to draw connections between Avidian digital evolution and the evolution of antibiotic resistance in microbial populations. After carrying out the introductory exercises, students developed independent Avida-ED projects to test their own research questions, and presented their data to researchers in the NSF-funded BEACON Center for the Study of Evolution in Action. Preliminary results of our studies to assess the impacts of an Avida-ED curriculum indicate a positive effect on student learning of evolutionary concepts, particularly in increasing the level of complexity of student explanations about the random nature of mutation.

Exploring the Relationship between Experiences with Digital Evolution and Students' Scientific Understanding and Acceptance of Evolution

Abstract Recent reforms in K-16 science education advocate for the integration of science content and practice. However, engaging students in authentic science practices can be particularly challenging for certain subjects such as evolution. We describe Avida-ED, a research-based platform for digital evolution that overcomes many of the challenges associated with using biological model organisms in the classroom. We then report the findings of a nationwide, multiple-case study on classroom implementation of Avida-ED and its influence on student understanding and acceptance of evolution. We found that engagement in lessons with Avida-ED both supported student learning of fundamental evolution concepts and was associated with an increase in student acceptance of evolution as evidence-based science. In addition, we found a significant, positive association between increased understanding and acceptance. We discuss the implications of supporting reform-based pedagogical practices with tools such as Avida-ED that integrate science content with authentic science practice.

A digital technology-based introductory biology course designed for engineering and other non-life sciences STEM majors

STEM education reform stresses the importance of a comprehensive understanding of science fundamentals and the development of science and engineering practices. As such, many engineering students must complete a core set of courses, including biology; however, this course is often designed for life sciences majors. One solution to this mismatch is to create an introductory biology course targeted to non‐biology STEM majors that introduces students to biology through a computational lens. Avida‐ED is a digital evolution software platform in which populations of digital organisms undergo actual—not simulated—evolutionary change, making evolution come alive through its observation in action. Integrating Avida‐ED provides a unique and novel approach to engaging engineering students in biological concepts within a computational environment, allowing them to exercise science and engineering practices in an authentic research experience. The design of this one‐semester course, “Integrative Biology: From DNA to Populations,” including its incorporation of a digital evolution lab, creates a way for computational science and engineering students to engage with biology within a context that is familiar and interesting.

Comparing Human and Automated Evaluation of Open-Ended Student Responses to Questions of Evolution

Written responses can provide a wealth of data in understanding student reasoning on a topic. Yet they are time- and labor-intensive to score, requiring many instructors to forego them except as limited parts of summative assessments at the end of a unit or course. Recent developments in Machine Learning (ML) have produced computational methods of scoring written responses for the presence or absence of specific concepts. Here, we compare the scores from one particular ML program -- EvoGrader -- to human scoring of responses to structurally- and content-similar questions that are distinct from the ones the program was trained on. We find that there is substantial inter-rater reliability between the human and ML scoring. However, sufficient systematic differences remain between the human and ML scoring that we advise only using the ML scoring for formative, rather than summative, assessment of student reasoning.