Communicating science effectively is an essential part of the development of science literacy. Research has shown that introducing primary scientific literature through journal clubs can improve student learning outcomes, including increased scientific knowledge. However, without scaffolding, students can miss more complex aspects of science literacy, including how to analyze and present scientific data. In this study, we apply a modified CREATE(S) process (Concept map the introduction, Read methods and results, Elucidate hypotheses, Analyze data, Think of the next Experiment, and Synthesis map) to improve students science literacy skills, specifically their understanding of the process of science and their ability to use narrative synthesis to communicate science. We tested this hypothesis using a retrospective quasi-experimental study design in upper-division undergraduate courses. We compared learning outcomes for CREATES intervention students to those for students who took the same courses before CREATES was introduced. Rubric-guided, direct evidence assessments were used to measure student gains in learning outcomes. Analyses revealed that CREATES intervention students versus the comparison group demonstrated improved ability to interpret and communicate primary literature, especially in the methods, hypotheses, and narrative synthesis learning outcome categories. Through a mixed-methods analysis of a reflection assignment completed by the CREATES intervention group, students reported the synthesis map as the most frequently used step in the process and highly valuable to their learning. Taken together, the study demonstrates how this modified CREATES process can foster scientific literacy development and how it could be applied in science, technology, engineering, and math journal clubs.

Improvements in high-throughput sequencing makes targeted amplicon analysis an ideal method for the study of human and environmental microbiomes by undergraduates. Multiple bioinformatics programs are available to process and interpret raw microbial diversity datasets, and the choice of programs to use in curricula is largely determined by student learning goals. Many of the most commonly used microbiome bioinformatics platforms offer end-to-end data processing and data analysis using a command line interface (CLI), but the downside for novice microbiome researchers is the steep learning curve often required. Alternatively, some sequencing providers include processing of raw data and taxonomy assignments as part of their pipelines. This, when coupled with available web-based or graphical user interface (GUI) analysis and visualization tools, eliminates the need for students or instructors to have extensive CLI experience. However, lack of universal data formats can make integration of these tools challenging. For example, tools for upstream and downstream analyses frequently use multiple different data formats which then require writing custom scripts or hours of manual work to make the files compatible. Here, we describe a microbial ecology bioinformatics curriculum that focuses on data analysis, visualization, and statistical reasoning by taking advantage of existing web-based and GUI tools. We created the Program for Unifying Microbiome Analysis Applications (PUMAA), which solves the problem of inconsistent files by formatting the output files from several raw data processing programs to seamlessly transition to a suite of GUI programs for analysis and visualization of microbiome taxonomic and inferred functional profiles. Additionally, we created a series of tutorials to accompany each of the microbiome analysis curricular modules. From pre- and post-course surveys, students in this curriculum self-reported conceptual and confidence gains in bioinformatics and data analysis skills. Students also demonstrated gains in biologically relevant statistical reasoning based on rubric-guided evaluations of open-ended survey questions and the Statistical Reasoning in Biology Concept Inventory. The PUMAA program and associated analysis tutorials enable students and researchers with no computational experience to effectively analyze real microbiome datasets to investigate real-world research questions.

We sought to test a hypothesis that systemic blind spots in active learning are a barrier both for instructors-who cannot see what every student is actually thinking on each concept in each class-and for students-who often cannot tell precisely whether their thinking is right or wrong, let alone exactly how to fix it. We tested a strategy for eliminating these blind spots by having students answer open-ended, conceptual problems using a Web-based platform, and measured the effects on student attrition, engagement, and performance. In 4 years of testing both in class and using an online platform, this approach revealed (and provided specific resolution lessons for) more than 200 distinct conceptual errors, dramatically increased average student engagement, and reduced student attrition by approximately fourfold compared with the original lecture course format (down from 48.3% to 11.4%), especially for women undergraduates (down from 73.1% to 7.4%). Median exam scores increased from 53% to 72-80%, and the bottom half of students boosted their scores to the range in which the top half had scored before the pedagogical switch. By contrast, in our control year with the same active-learning content (but without this zero blind spots approach), these gains were not observed.

Course-based undergraduate research experiences (CUREs) and apprentice-based research experiences (AREs) represent inclusive, student-centered instructional strategies that can improve student learning and help to keep them on a scientific career pathway. Using backwards course design ensures that educators and faculty align research activities with the learning outcomes and that selected assessments provide adequate evidence of student achievements, visualized via curriculum mapping. Rubrics are suitable assessment tools for measuring how students perform in these research-based laboratory courses. Faculty benefit from teaching CUREs and mentoring students in AREs in ways that enhance both their teaching portfolios and research productivity.

Our study identified online lecture video styles that improved student engagement and satisfaction, while maintaining high learning outcomes in online education. We presented different lecture video styles with standardized material to students and then measured learning outcomes and satisfaction with a survey and summative assessment. We created an iterative qualitative coding scheme, coding online asynchronous lectures (COAL), to analyze open-ended student survey responses. Our results reveal that multimedia learning can be satisfying and effective. Students have strong preferences for certain video styles despite their equal learning outcomes, with the Learning Glass style receiving the highest satisfaction ratings. Video styles that were described as impersonal and unfamiliar were rated poorly, while those that were described as personal and engaging and evoked positive affective responses were rated highly. The students in our study rated lecture video styles that aligned with Mayers multimedia learning principles as highly satisfying, indicating that student feedback can be a valuable resource for course designers to consider as they design their own online courses. Finally, we provide guidelines for creating engaging, effective, and satisfying asynchronous lecture videos to support establishment of best practices in online instruction.

Calculus is typically one of the first college courses encountered by science, technology, engineering, and mathematics (STEM) majors. Calculus often presents major challenges affecting STEM student persistence, particularly for students from groups historically underrepresented in STEM. For life sciences majors, calculus courses may not offer content that is relevant to biological systems or connect with students' interests in biology. We developed a transformative approach to teaching college-level math, using a dynamical systems perspective that focuses first on demonstrating why students need math to understand living systems, followed by providing quantitative and computational skills, including concepts from calculus, that students need to build and analyze mathematical models representing these systems. We found that students who complete these new math courses perform better in subsequent science courses than their counterparts who take traditional calculus courses. We also provide evidence that the new math curriculum positively impacts students' academic performance, with data that show narrowing of the achievement gap, based on students' math grades, between student subgroups in the new math courses. Moreover, our results indicate that students' interest in the concepts and skills critical to the quantitative preparation of 21st-century life sciences majors increases after completing the new contextualized math curriculum.

A variety of genetic techniques have been devised to determine cell lineage relationships during tissue development. Some of these systems monitor cell lineages spatially and/or temporally without regard to gene expression by the cells, whereas others correlate gene expression with the lineage under study. The GAL4 Technique for Real-time and Clonal Expression (G-TRACE) system allows for rapid, fluorescent protein-based visualization of both current and past GAL4 expression patterns and is therefore amenable to genome-wide expression-based lineage screens. Here we describe the results from such a screen, performed by undergraduate students of the University of California, Los Angeles (UCLA) Undergraduate Research Consortium for Functional Genomics (URCFG) and high school summer scholars as part of a discovery-based education program. The results of the screen, which reveal novel expression-based lineage patterns within the brain, the imaginal disc epithelia, and the hematopoietic lymph gland, have been compiled into the G-TRACE Expression Database (GED), an online resource for use by the Drosophila research community. The impact of this discovery-based research experience on student learning gains was assessed independently and shown to be greater than that of similar programs conducted elsewhere. Furthermore, students participating in the URCFG showed considerably higher STEM retention rates than UCLA STEM students that did not participate in the URCFG, as well as STEM students nationwide.

Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.