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Causal mechanistic reasoning is a thinking strategy that can help students explain complex phenomena using core ideas commonly emphasized in separate undergraduate courses, as it requires students to identify underlying entities, unpack their relevant properties and interactions, and link them to construct mechanistic explanations. As a cross-disciplinary group of biologists, chemists, and teacher educators, we designed a scaffolded set of tasks that require content knowledge from biology and chemistry to construct nested hierarchical mechanistic explanations that span three scales (molecular, macromolecular, and cellular). We examined student explanations across seven introductory and upper-level biology and chemistry courses to determine how the construction of mechanistic explanations varied across courses and the relationship between the construction of mechanistic explanations at different scales. We found non-, partial, and complete mechanistic explanations in all courses and at each scale. Complete mechanistic explanation construction was lowest in introductory chemistry, about the same across biology and organic chemistry, and highest in biochemistry. Across tasks, the construction of a mechanistic explanation at a smaller scale was associated with constructing a mechanistic explanation for larger scales; however, the use of molecular scale disciplinary resources was only associated with complete mechanistic explanations at the macromolecular, not cellular scale.

There is emerging recognition that mechanistic reasoning about scientific phenomena as well as developing an interdisciplinary understanding of science are valuable for student success. Our team of chemistry, biology, and teacher education researchers strives to support students in their interdisciplinary learning and engage them in causal mechanistic reasoning (CMR), a thinking strategy that involves identifying underlying entities and their properties and linking these ideas to explain or predict a target phenomenon. We aim to help students build connections between their undergraduate chemistry and biology courses through engagement with carefully developed activities, which can be administered in a range of courses. In this study, we explored how students in 7 different chemistry, biology, or biochemistry courses engaged in CMR about preferential protein-ligand binding, a biological phenomenon that requires an understanding of core chemistry ideas like atomic properties and electrostatics. Explanations varied from noncausal mechanistic to fully causal mechanistic across all courses; however, students co-enrolled in molecular biology and second semester general chemistry did not differ in their engagement in CMR when situated in each course. Student responses provided evidence of activation of different conceptual resources, including charge, polarity, and space, to explain this phenomenon. Lastly, correct predictions about the preferred binding site were highly correlated with fully engaged CMR, showing compelling evidence for the power of this thinking strategy. This task effectively elicits CMR in both chemistry and biology courses, thus making it a potential tool for helping students build connections across disciplinary silos they experience in undergraduate science curricula.

Evolution is foundational to understanding biology, yet learners at all stages have incomplete and incorrect ideas that persist beyond graduation. Contextual features of prompts (e.g., taxon of organism, acquisition vs. loss of traits, etc.) have been shown to influence both the learning process and the ideas students express in explanations of evolutionary processes. In this study, we compare students' explanations of natural selection for humans versus a nonhuman animal (cheetah) at different times during biology instruction. We found "taxon" to be a significant predictor of the content of students' explanations. Responses to "cheetah" prompts contained a larger number and diversity of key concepts (e.g., variation, heritability, differential reproduction) and fewer naïve ideas (e.g., need, adapt) when compared with responses to an isomorphic prompt containing "human" as the organism. Overall, instruction increased the prevalence of key concepts, reduced naïve ideas, and caused a modest reduction in differences due to taxon. Our findings suggest that the students are reasoning differently about evolutionary processes in humans as compared with nonhuman animals, and that targeted instruction may both increase students' facility with key concepts while reducing their susceptibility to contextual influences.

As biological science rapidly generates new knowledge and novel approaches to address increasingly complex and integrative questions, biology educators face the challenge of teaching the next generation of biologists and citizens the skills and knowledge to enable them to keep pace with a dynamic field. Fundamentally, biology is the science of living systems. Not surprisingly, systems is a theme that pervades national reports on biology education reform. In this essay, we present systems as a unifying paradigm that provides a conceptual framework for all of biology and a way of thinking that connects and integrates concepts with practices. To translate the systems paradigm into concrete outcomes to support instruction and assessment in the classroom, we introduce the biology systems-thinking (BST) framework, which describes four levels of systems-thinking skills: (1) describing a system's structure and organization, (2) reasoning about relationships within the system, (3) reasoning about the system as a whole, and (4) analyzing how a system interacts with other systems. We conclude with a series of questions aimed at furthering conversations among biologists, biology education researchers, and biology instructors in the hopes of building support for the systems paradigm.

This article outlines a thinking framework that any teacher can use to adapt curriculum through a lens of gender diversity. The authors illustrate the adaptation of several sample lessons to achieve three key outcomes: (1) to support and reduce harm to LGBTQ students; (2) to engage all students with inquiry into science in society; and (3) to develop student empathy toward diverse identities and perspectives. Additional resources are included at the end of the article to continue teachers' explorations of creating inclusive classroom culture.

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.

Gwinnett Technical College (GTC), established in 1984, is the second-largest technical college in Georgia. As a two-year open-access college, GTC and other technical and community colleges are significant in educating STEM and nonSTEM majors in the scientific process and scientific literacy. To increase the success of students enrolled in non-majors Biology I, three GTC biology faculty collaborated to redesign the course, using a backward design method. Grade analysis performed inference about two population proportions and descriptive statistics to interpret data. After course redesign, there was a statistically significant decrease in the D, F, Withdrawal (DFW) rates and a significant increase in students passing with a C average. Further analysis showed first-semester "beginning" students, traditional-aged students, and minority students benefitted most from the curriculum redesign. The backward design model for curriculum redesign was effective in increasing learning and retention in biology at the technical college level. The redesign helped students in jeopardy of failing or withdrawing from the course, especially in groups of students considered "at-risk." This study contributes to the growing body of knowledge regarding the design of STEM curriculum at the technical college level.

We describe the conceptualization, design, development, validation, and testing of a summative instrument that measures high school students' ability to analyze and evaluate data, construct scientific explanations, and formulate scientific arguments in biology and chemistry disciplinary contexts. Data from 1,405 students were analyzed to evaluate the properties of the instrument. Student measurement separation reliability was 0.71 with items showing satisfactory fit to the Partial Credit Model. The use of the Evidence-Centered Design framework during the design and development process provided a strong foundation for the validity argument. Additional evidence for validation were also gathered. The strengths of the instrument lie in its relatively brief time for administration and a unique approach that integrates science practice and disciplinary knowledge, while simultaneously seeking to decouple their measurement. This research models how to design assessments that align to the National Research Council's framework and informs the design of Next Generation Science Standards-aligned assessments.

Information literacy is an essential skill for biologists; however, most biology curricula do not intentionally integrate information literacy into classroom and laboratory exercises. There is evidence that developing information literacy skills in undergraduates improves their research skills, writing, and GPAs. Our objective was to integrate information literacy skills into a first semester introductory biology laboratory with a multi-week, inquiry-based module that leverages primary literature. Here we describe the module, which challenges students to develop and test a hypothesis related to parental care behaviour in birds. Students form hypotheses based on literature searching done during librarian-led information literacy sessions, produce an annotated bibliography, collect and analyse video data of barn swallows feeding their offspring, and present their findings. Analysis of students' annotated bibliographies indicates that 83% of the referenced papers were appropriate for developing their specific hypotheses. The key elements of a successful information literacy training plan include faculty-librarian collaboration, multiple classroom or laboratory sessions that introduce or utilize information literacy, and relevance of the information literacy training to an assignment. By introducing information literacy early in biology curricula, departments can develop tiered information literacy plans that incorporate opportunities for students to use and refine these skills throughout their studies.

In this study, we propose an 'Approach to Modeling' (AtM) framework for examining how undergraduates approach tasks that require modelling scientific phenomena. Our framework is adapted from Approach to Learning (AtL) theories and consists of three observable behavioural constructs: metacognition, generative thinking, and causal reasoning. Twenty students participated in two think-aloud interviews, one year apart, in which they engaged in a total of five modelling tasks. We used AtM to analyse and score students' modelling behaviours. We concluded that: (1) students' AtM is associated with, but cannot be predicted by their previous academic achievement, and (2) students' AtM is not an inherent characteristic of the individual, but differs as modelling tasks change. We discuss the influence of prompt construction on AtM; specifically the presence of cueing words, the type and amount of background information provided, and familiarity with the contexts and concepts addressed in the prompts. In addition, we discuss connections between AtM and broader notions of science learning. We conclude with recommendations for constructing modelling prompts that may encourage diverse learners to engage more deeply in modelling tasks.

The Advanced Placement (AP) program has undergone two major reforms in recent decades: the first aimed at increasing access and the second at increasing relevance. Both initiatives are partially designed to increase the number of high school students from low-income backgrounds who have access to college-level coursework. Yet critics argue that schools in less-resourced communities are unable to implement AP at the level expected by its founders. We offer the first model of the components inherent in a well-implemented AP science course and the first evaluation of AP implementation with a focus on public schools newly offering the inquiry-based version of AP Biology and Chemistry courses. We find that these frontier schools were able to implement most, but not all, of the key components of an AP science course.

Since 2009, the U.S. National Science Foundation Directorate for Biological Sciences has funded Research Coordination Networks (RCN) aimed at collaborative efforts to improve participation, learning, and assessment in undergraduate biology education (UBE). RCN-UBE projects focus on coordination and communication among scientists and educators who are fostering improved and innovative approaches to biology education. When faculty members collaborate with the overarching goal of advancing undergraduate biology education, there is a need to optimize collaboration between participants in order to deeply integrate the knowledge across disciplinary boundaries. In this essay we propose a novel guiding framework for bringing colleagues together to advance knowledge and its integration across disciplines, the "Five 'C's' of Collaboration: Commitment, Collegiality, Communication, Consensus, and Continuity." This guiding framework for professional network practice is informed by both relevant literature and empirical evidence from community-building experience within the RCN-UBE Advancing Competencies in Experimentation-Biology (ACE-Bio) Network. The framework is presented with practical examples to illustrate how it might be used to enhance collaboration between new and existing participants in the ACE-Bio Network as well as within other interdisciplinary networks.

One of the goals of college-level introductory biology is to establish a foundation of knowledge and skills that can be built upon throughout a biology curriculum. In a reformed introductory biology course, we used iterative model construction as a pedagogical tool to promote students' understanding about conceptual connections, particularly those linking genetic variation to organismal fitness. In interviews conducted 2.5 years later, we examined students' retrieval of conceptual connections emphasized during the course. Students constructed a model similar to those practiced during the course, reviewed their models with the interviewer, and answered questions about how they retrieved this knowledge conceptual understanding. Student proficiency on this task was evaluated based on the quality of their modeling and responses to questions about their models. Three distinct groups emerged: students that had an inadequate cognitive structure for the biological concepts (absent), and students that had incomplete or complete cognitive structures. Students in the Complete group were better able to verbally link genetic variation to phenotypic variation and differential fitness and successfully used relationships stored in their cognitive structure to explain gaps present in their drawn model. Students in the Incomplete group had fragmented knowledge where some concepts were connected to each other, but not to the whole model. Students in the Absent group had extensive gaps in knowledge and were unable to connect their conceptual ideas. Students who were most proficient in the task differed in their ability to access and search within their cognitive structure and verify the quality of their conceptual relationships. This allowed the most proficient students to fill in knowledge gaps and transfer their conceptual understanding to new contexts.

Graduate teaching assistants (TAs) are increasingly responsible for instruction in undergraduate science, technology, engineering, and mathematics (STEM) courses. Various professional development (PD) programs have been developed and implemented to prepare TAs for this role, but data about effectiveness are lacking and are derived almost exclusively from self-reported surveys. In this study, we describe the design of a reformed PD (RPD) model and apply Kirkpatrick's Evaluation Framework to evaluate multiple outcomes of TA PD before, during, and after implementing RPD. This framework allows evaluation that includes both direct measures and self-reported data. In RPD, TAs created and aligned learning objectives and assessments and incorporated more learner centered instructional practices in their teaching. However, these data are inconsistent with TAs' self-reported perceptions about RPD and suggest that single measures are insufficient to evaluate TA PD programs.

In an ethnographic study set within a biology department of a public university in the United States, incongruity between the ideals and practice of science education are investigated. Against the background of religious conservative students' complaints about evolution in the curriculum, biology faculty describe their political intents for fostering science literacy. This article examines differences that emerge between the department's rhetorical commitment to improve science understanding amongst their students and the realities of course staffing and anxieties about promotion and tenure. Because tenure-track faculty are motivated to focus their careers on research productivity and teaching biology majors, other biology courses are staffed with adjunct instructors who are less equipped to negotiate complex pedagogies of science and religion. In practice, faculty avoid risky conversations about evolution versus creationism with religiously conservative students. I argue that such faculty are complicit, through their silence, in failing to equip their students with the science literacy which their own profession avows is crucial for a well-informed citizenry in a democracy.

Research in contemporary biology has become increasingly complex and organized around understanding biological processes in the context of systems. To better reflect the ways of thinking required for learning about systems, we developed and implemented a pedagogical approach using box-and-arrow models (similar to concept maps) as a foundational tool for instruction and assessment in an Introductory Biology course on genetics, evolution, and ecology. Over the course of one semester, students iteratively constructed, evaluated, and revised "Gene-to-Evolution" (GtE) models intended to promote understanding about the connections linking molecular-level processes with population-level outcomes. In practice, a successful GtE model contextualizes information provided in a case study and explains how genetic-level variation originates at the molecular level, is differentially expressed among individuals, and is acted upon by the environment to produce evolutionary change within a population. Our analyses revealed that students' ability to construct biologically accurate models increased throughout the semester. Model complexity peaked near mid-term then subsequently declined. This suggests that, with time, students were building more parsimonious models, shedding irrelevant information, and improving in their ability to apply accurate and appropriate biological language to explain relationships among concepts. Importantly, we observed the greatest relative gains in model correctness among students who entered the course with lower mean GPA. In an analysis comparing performance among achievement tritiles, lower-performing students effectively closed the achievement gap with the highest performing students by the end of the semester. Our findings support the effectiveness of model-based pedagogies for science teaching and learning, and offer a perspective on pedagogical application of modeling strategies to foster systems thinking and knowledge structuring in college-level biology. (Contains 4 tables and 6 figures.)

This paper analyzes recent research conclusions regarding biology teacher attitudes toward evolution, and the variable implementation of evolution in the high schools nationwide. Berkman and Plutzer (2010. "Evolution, creationism, and the battle to control America's classrooms." New York: Cambridge University Press) conclude that due to a large portion of high school biology teachers compromising or downplaying evolution in the curriculum, the placement of evolution specific courses in biology teacher preparation programs will steer evolution deniers away from the field. In this paper, such arguments are situated in a larger historical and philosophical context of science education. By discussing recent sociological insight into the religiosity of education majors and education faculty, new questions are raised about student and teacher ontology, what this means for understanding science, the politics of science teacher education programs, and the epistemological and ethical limits of science education standards to dissolve Creationism.

Introductory biology courses are widely criticized for overemphasizing details and rote memorization of facts. Data to support such claims, however, are surprisingly scarce. We sought to determine whether this claim was evidence-based. To do so we quantified the cognitive level of learning targeted by faculty in introductory-level biology courses. We used Bloom's Taxonomy of Educational Objectives to assign cognitive learning levels to course goals as articulated on syllabi and individual items on high-stakes assessments (i.e., exams and quizzes). Our investigation revealed the following: 1) assessment items overwhelmingly targeted lower cognitive levels, 2) the cognitive level of articulated course goals was not predictive of the cognitive level of assessment items, and 3) there was no influence of course size or institution type on the cognitive levels of assessments. These results support the claim that introductory biology courses emphasize facts more than higher-order thinking. (Contains 3 figures and 2 tables.)

Science writing from periods of great change in science can be used productively in the classroom to advance scientific literacy. Compares the scientific monograph with the short paper prevalent in the late 20th century and suggests that there are cases in which a small group of papers can serve the same function as a monograph. (Contains 30 references.) (Author/YDS)

Measured the effects of three variations in the use of diagnostic-prescriptive (DP) teaching on the cognitive and affective biology achievement of high school students (N=93). Variations included: (1) no DP assistance; (2) teacher-managed DP; and (3) student-managed DP. Results favor DP approaches. (Author/JN)

Bronchiectasis is a heterogeneous disease with multiple aetiologies and diverse clinical features. There is a general consensus that optimal treatment requires precision medicine approaches focused on specific treatable disease characteristics, known as treatable traits. Identifying subtypes of conditions with distinct underlying biology (endotypes) depends on the identification of biomarkers that are associated with disease features, prognosis or treatment response and which can be applied in clinical practice. Bronchiectasis is a disease characterised by inflammation, infection, structural lung damage and impaired mucociliary clearance. Increasingly there are available methods to measure each of these components of the disease, revealing heterogeneous inflammatory profiles, microbiota, radiology and mucus and epithelial biology in patients with bronchiectasis. Using emerging biomarkers and omics technologies to guide treatment in bronchiectasis is a promising field of research. Here we review the most recent data on biomarkers in bronchiectasis. [ABSTRACT FROM AUTHOR]

A transformer is the foundational architecture behind large language models designed to handle sequential data by using mechanisms of self‐attention to weigh the importance of different elements, enabling efficient processing and understanding of complex patterns. Recently, transformer‐based models have become some of the most popular and powerful deep learning (DL) algorithms in molecular science, owing to their distinctive architectural characteristics and proficiency in handling intricate data. These models leverage the capacity of transformer architectures to capture complex hierarchical dependencies within sequential data. As the applications of transformers in molecular science are very widespread, in this review, we only focus on the technical aspects of transformer technology in molecule domain. Specifically, we will provide an in‐depth investigation into the algorithms of transformer‐based machine learning techniques in molecular science. The models under consideration include generative pre‐trained transformer (GPT), bidirectional and auto‐regressive transformers (BART), bidirectional encoder representations from transformers (BERT), graph transformer, transformer‐XL, text‐to‐text transfer transformer, vision transformers (ViT), detection transformer (DETR), conformer, contrastive language‐image pre‐training (CLIP), sparse transformers, and mobile and efficient transformers. By examining the inner workings of these models, we aim to elucidate how their architectural innovations contribute to their effectiveness in processing complex molecular data. We will also discuss promising trends in transformer models within the context of molecular science, emphasizing their technical capabilities and potential for interdisciplinary research. This review seeks to provide a comprehensive understanding of the transformer‐based machine learning techniques that are driving advancements in molecular science. This article is categorized under:Data Science > ChemoinformaticsData Science > Artificial Intelligence/Machine Learning [ABSTRACT FROM AUTHOR]

Abstract The world is currently experiencing a global pandemic caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which causes severe respiratory disease similar to SARS. Previous studies have suggested that SARS‐CoV‐2 shares 79% and 96% sequence identity to SARS‐CoV and to bat coronavirus RaTG13, respectively, at the whole‐genome level. Furthermore, a series of studies have shown that SARS‐CoV‐2 induces clusters of severe respiratory illnesses (i.e., pneumonia, acute lung injury, acute respiratory distress syndrome) resembling SARS‐CoV. Moreover, the pathological syndrome may, in part, be caused by cytokine storms and dysregulated immune responses. Thus, in this work the recent literature surrounding the biology, clinical manifestations, and immunology of SARS‐CoV‐2 is summarized, with the aim of aiding prevention, diagnosis, and treatment for SARS‐CoV‐2 infection.

The sweet potato weevil Cylas formicarius is a notorious underground pest in sweet potato (Ipomoea batatas L.). However, little is known about the effects of cadmium (Cd) stress on weevil biology and resistance to pesticides and biotic agents. Therefore, we fed sweet potato weevils with Cd-contaminated sweet potato and assessed adult food intake and survival and larval developmental duration and mortality rates, as well as resistance to the insecticide spinetoram and susceptibility to the entomopathogenic fungus Beauveria bassiana. With increasing Cd concentration, the number of adult weevil feeding holes, adult survival and life span, and larval developmental duration decreased significantly, whereas larval mortality rates increased significantly. However, at the lowest Cd concentration (30 mg/L), adult feeding was stimulated. Resistance of adult sweet potato weevils to spinetoram increased at low Cd concentration, whereas Cd contamination did not affect sensitivity to B. bassiana. Thus, Cd contamination affected sweet potato weevil biology and resistance, and further studies will investigate weevil Cd accumulation and detoxification mechanisms. [ABSTRACT FROM AUTHOR]

Glioma shows diffuse infiltrative growth in the brain parenchyma. Even following the principle of "maximum safe resection", the residual tumor cells are resistant to adjuvant chemoradiotherapy and continue to invase and migrate in the brain tissue. This is the main reason for the recurrence of glioma and the dissemination in the central nervous system (CNS). As a result, understanding the mode of glioma invasion and migration can provide a new method for the treatment of glioma. This paper reviews our research findings of the invasion and migration of glioma during the period of Twelfth Five-Year Plan for National Economic and Social Development. DOI: 10.3969/j.issn.1672-6731.2018.01.006