The Current Insights feature is designed to introduce life science educators and researchers to current articles of interest in other social science and education journals. In this installment, I highlight three diverse research studies: one exploring classroom talk and how it impacts conceptual learning; one identifying a unique influence on evolution acceptance: statistical understanding; and the last a genetics lesson that reduces racial bias.

As an instructional tool, models can transform the student experience from the static to the dynamic, the flat to the 3D, and the siloed to the integrated. Few practical resources exist to help instructors transition toward model-based classroom practices. The Modeling in the Classroom evidence-based teaching guide provides instructors with a tool kit for incorporating models and modeling into their classrooms (https://lse.ascb.org/evidence-based-teaching-guides/modeling-in-the-classroom). The guide discusses the underpinnings of modeling as a core scientific practice, one that can enable student development of systems thinking skills and understanding of biological concepts. The guide describes a variety of model types, including phylogenetic trees, simulations, animations, diagrams, conceptual models, concept maps, and tactile models supported by summaries of and links to articles and resources. In this paper, we will introduce key findings describing why and how to use models in the classroom. We also describe open research questions needed to address classroom implementation, instructional design, and development of students’ knowledge and skills. It is our hope that the guide will provide a suitable combination of research-based findings and practical suggestions that instructors will be supported and encouraged to thoughtfully incorporate modeling to support learning goals.

We describe the development and initial validity assessment of the 20-item BioCalculus Assessment (BCA), with the objective of comparing undergraduate life science students’ understanding of calculus concepts in different courses with alternative emphases (with and without focus on biological applications). The development process of the BCA included obtaining input from a large network of scientists and educators as well as students in calculus and biocalculus courses to accumulate evidential support of the instrument’s content validity and response processes of test takers. We used the Rasch model to examine the internal structure of scores from students who have experienced calculus instruction in the two methods. The analysis involved three populations (Calculus 1, Calculus 2, and Biocalculus) for which the Calc 1 and Calc 2 students were not exposed to calculus concepts in a life science setting, while the Biocalculus students were presented concepts explicitly with a life science emphasis. Overall, our findings indicate that the BCA has reasonable validity properties, providing a diagnostic tool to assess the relative learning success and calculus comprehension of undergraduate biology majors from alternative methods of instruction that do or do not emphasize life science examples.

Whether students view intelligence as a fixed or malleable trait (i.e., their “mindset”) has significant implications for their responses to failure and academic outcomes. Despite a long history of research on mindset and its growing popularity, recent meta-analyses suggest that mindset does a poor job of predicting academic outcomes for undergraduate populations. Here, we present evidence that these mixed results could be due to ambiguous language on the mindset scale. Specifically, the term “intelligence” is a referent in every item of the mindset scale but is never defined, which could result in differing interpretations and measurement error. Therefore, we conducted an exploratory, qualitative study to characterize how undergraduate students define intelligence and how their definitions may influence how they respond to the mindset scale. We uncovered two distinct ways that undergraduates define intelligence: knowledge and abilities (e.g., ability to learn, solve problems). Additionally, we found that students’ definitions of intelligence can vary across contexts. Finally, we present evidence that students who define intelligence differently also interpret and respond to the items on the mindset scale differently. We discuss implications of these results for the use and interpretation of the mindset scale with undergraduate students.

Evolutionary theory explains a wide range of biological phenomena. Proper understanding of evolutionary mechanisms such as natural selection is therefore an essential goal for biology education. Unfortunately, natural selection has time and again proven difficult to teach and learn, and students’ resulting understanding is often characterized by misconceptions. Previous research has often focused on the importance of certain key concepts such as variation, differential survival, and change in population. However, so-called threshold concepts (randomness, probability, spatial scale, and temporal scales) have also been suggested to be important for understanding of natural selection, but there is currently limited knowledge about how students use these concepts. We sought to address this lack of knowledge by collecting responses to three different natural selection items from 247 university students from Sweden and Germany. Content analysis (deductive and inductive coding) and subsequent statistical analysis of their responses showed that they overall use some spatial scale indicators, such as individuals and populations, but less often randomness or probability in their explanations. However, frequencies of use of threshold concepts were affected by the item context (e.g., the biological taxa and trait gain or loss). The results suggest that the impact of threshold concepts, especially randomness and probability, on natural selection understanding should be further explored.

A desired outcome of education reform efforts is for undergraduates to effectively integrate knowledge across disciplines in order to evaluate and address real-world issues. Yet there are few assessments designed to measure if and how students think interdisciplinarily. Here, a sample of science faculty were surveyed to understand how they currently assess students’ interdisciplinary science understanding. Results indicate that individual writing-intensive activities are the most frequently used assessment type (69%). To understand how writing assignments can accurately assess students’ ability to think interdisciplinarily, we used a preexisting rubric, designed to measure social science students’ interdisciplinary understanding, to assess writing assignments from 71 undergraduate science students. Semistructured interviews were conducted with 25 of those students to explore similarities and differences between assignment scores and verbal understanding of interdisciplinary science. Results suggest that certain constructs of the instrument did not fully capture this competency for our population, but instead, an interdisciplinary framework may be a better model to guide assessment development of interdisciplinary science. These data suggest that a new instrument designed through the lens of this model could more accurately characterize interdisciplinary science understanding for undergraduate students.

When a student explains a biological phenomenon, does the answer reflect only the product of retrieving knowledge or does it also reflect a dynamic process of constructing knowledge? To gain insight into students’ dynamic knowledge, we leveraged three analytic frameworks—structures–behaviors–functions (SBF), mental models (MM), and conceptual dynamics (CD). To assess the stability of student knowledge, we asked undergraduate students to explain the same physiological phenomenon three times—once verbally, once after drawing, and once after interpreting a diagram. The SBF analysis illustrated fine-grained dynamic knowledge between tasks. The MM analysis suggested global stability between tasks. The CD analysis demonstrated local instability within tasks. The first two analyses call attention to differences between students’ knowledge about the parts of systems and their organization. The CD analysis, however, calls attention to similar learning mechanisms that operate differently vis-à-vis external representations. Students with different mental models deliberated localization or where to locate the structures and mechanisms that mediate physiological responses, but students made these deliberations during different tasks and arrived at different conclusions. These results demonstrate the utility of incorporating dynamic approaches to complement other analytic approaches and motivate future research agendas in biology education research.

As research has shown, collaborative peer learning is effective for improving student learning. Peer-led team learning (PLTL) is one well-known collaborative-group approach in which groups are facilitated by trained undergraduate peer leaders. This paper contributes to the literature on peer-leader training by examining how peer leaders for a large introductory science course translate their training into practice during their sessions. By conducting qualitative analysis on annual advice books written by emergent peer leaders, we examined the practiced advice and strategies of these peer leaders as they facilitate PLTL groups in a university-level general chemistry course. These advice books are passed on to future peer instructors, creating a community of practice between new and more experienced peer leaders. From the analysis, we discovered that peer leaders focus on developing robust student–student discussion during complex problem solving by 1) creating a community-oriented social and intellectual environment, 2) adapting their tactics and the collaborative-learning strategies to balance different personalities and promote equal participation among all students, and 3) modifying collaborative group approaches when facilitating their sessions. Also, in their correspondence across cohorts, peer leaders provided near-peer support to one another. These annual books disseminate practiced advice between peer-leader generations and are used during new peer-leader training.

Group activities as part of active-learning pedagogies are thought to be effective in promoting student learning in part because of the quality of discussion they engender in student teams. Not much is known, however, about which instructional factors are most important in achieving productive conversation or how these factors may differ among different collaborative pedagogies. We explored what provokes meaningful group discussions in a university physiology course taught using team-based learning (TBL). We were most interested in discussions that evoke explanations that go beyond statements of basic facts and into disciplinary reasoning. Using transcribed conversations of four randomly selected teams three times throughout the semester, we analyzed three distinct discursive phenomena—conceptual explanations, re-evaluations, and co-construction—that occurred in productive conversations. In this paper, we provide examples from student discussions showing the role of each of these elements in moving students toward conceptual understanding. These phenomena were more likely to occur in response to higher-order questions in Bloom’s taxonomy. Preclass preparation and student accountability as part of TBL may be important factors in this finding. We share implications for practice based on our results.

Recent studies demonstrate that significant learning gains can be achieved when instructors take intentional steps to address the affective components of learning. While such efforts enhance the outcomes of all students, they are particularly beneficial for students from underrepresented groups and can reduce performance gaps. In the present study, we examined whether intentional efforts to address the affective domain of learning (through growth mindset messaging) can synergize with best practices for addressing the cognitive domain (via active-learning strategies) to enhance academic outcomes in biology courses. We compared the impact of this two-pronged approach (known as dual domain pedagogy, or DDP) with that of two other pedagogies (lecture only or active learning only). Our results demonstrate that DDP is a powerful tool for narrowing performance gaps. DDP, but not active learning, eliminated the performance gap observed between Black and white students in response to lecture. While a significant gap between white and Latin@ students was observed in response to active learning (but not lecture), this gap was reduced by DDP. These findings demonstrate that DDP is an effective approach for promoting a more equitable classroom and can foster learning outcomes that supersede those conferred by active learning alone.

One of the foundational assumptions in education is that greater teacher knowledge contributes to greater gains in student knowledge, but empirical evidence in support of this assumption is scarce. Using a U.S. sample of 79 biology teachers and their 2749 high school students, we investigate whether teachers’ subject matter knowledge (SMK) and knowledge of students’ misconceptions (KOSM) in high school life science are associated with students’ posttest performance on multiple-choice test items designed to reveal student misconceptions, after controlling for their pretest scores. We found that students were more likely to answer an item on the posttest correctly if their teachers could answer the question correctly, themselves (SMK). Teachers’ ability to predict students’ most common wrong answer (KOSM) for an item predicted even better student performance. Items for which a particular wrong answer rose above others in popularity saw an even greater benefit for teacher KOSM.

Course-based undergraduate research experiences (CUREs) serve to increase student access to authentic scientific opportunities. Current evidence within the literature indicates that engagement in CUREs promotes students’ science identity development, science self-efficacy, motivation, and ability to “think like a scientist.” Despite the importance of these findings, few studies have examined the behaviors and interactions occurring within CURE and non-CURE settings and the impact of those behaviors on said student outcomes. To address these concerns, we conducted a mixed-methods study to explore student and instructor behaviors in four CURE and four non-CURE introductory biology laboratory sections. Representative video data were collected in each section and coded using the Laboratory Observation Protocol for Undergraduate STEM. In addition, pre/postsemester affective survey data were obtained from CURE and non-CURE participants. Results indicated that CURE students and instructors engaged in more interactive behaviors (e.g., one-on-one dialogue, questioning) than their non-CURE counterparts, a finding confirmed by analyzing behavioral patterns via construction of partial correlation networks. Multiple regression analyses further revealed that both student and instructor interactive behaviors and enrollment in a CURE were strong predictors of pre/postsemester shifts in student motivation, science identity development, collaboration, and perceived opportunities to make relevant scientific discoveries.

The second edition of Entering Research (ER) is a collection of customizable active-learning activities, resources, and assessment and evaluation tools for use in undergraduate and graduate research training programs and courses. Results from two design and development research studies examining the effectiveness of the second edition of the ER curriculum and a 2-day ER facilitator training workshop are reported. Pilot testing of the second edition of the curriculum at 20 sites across the country (42 unique implementations) with 78 facilitators and 565 undergraduate and graduate research trainees provides evidence that the ER activities are clear and complete and that they were effective in helping trainees gain knowledge or improve their ability to do research. Overall, research training program directors and trainees were satisfied with courses and workshops that incorporated activities from ER. Likewise, evaluation data from four ER facilitator training workshops showed that participants valued the workshop and reported significant gains in confidence in their ability to successfully develop and implement a custom ER curriculum. Together, these results provide evidence that the ER curriculum and training workshop warrant further efficacy, effectiveness, and scale-up research.