In this module, students will investigate the mutualistic relationship between Agave its bat pollinators and the effects of coevolution on the morphological adaptations of the species involved.

This module is made up of four concepts. The goal of the first concept is to elicit an understanding of primate relatedness, phylogeny, and how specific characteristics are beneficial for life in an arboreal environment. The next concept explains the overarching trends in hominin evolution and the selective pressures that encouraged their development. Concept three examines specific fossils and the characteristics that are associated with them. This concept serves to provide a timeline of hominin evolution. The final concept encourages students to understand characteristics in the hominin lineage and how they relate to social behaviors. This concept ends by driving home the point that evolution is a dynamic and continual process.

This adaptation of the Vertebrate Clade Race provides a tactile approach to introduce basic tree reading skills for evolutionary phylogenies. Using a Universal Design for Learning informed approach, the variation makes the activity accessible for students who are blind or low-vision and streamlines the activity for all students, while retaining the original learning goals. After completing this group activity, students should be familiar with basic terminology and how to "read" a phylogenetic tree.

Using a multimodal approach, the non-linear aspect of the surface area to volume relationship is explored. Students use their their senses of taste and sight to determine how smaller cells and larger cells differ. Quantitative examples are explored. Concepts of structure and function Examples along the biological hierarchy are provided.

New stop-motion ‘candymation’ videos of mitosis and meiosis, plus Instructor Guides and problem sets.

In this lesson students 1) become familiar with various graphs that are used to study diversity patterns within and across sites, 2) learn about some of the questions that can be addressed by metabarcoding studies, and 3) reflect on an interview with evolutionary ecologist Maria Rebolleda Gomez, who collected the data used in the lesson.

This lesson targets entry-level undergraduate students to enhance their proficiency in comprehending and interpreting scientific graphs. The lesson incorporates group discussions centered around several graphs about lizards, together with individual reflective essays and a social media assignment. Students will also gain insights from an interview video featuring Dr. Daniel Warner, the lizard scientist who was responsible for data collection and graph creation explored in the lesson.

Biodiversity databases, based on species occurrences, are now readily available for students to use a free of charge. These databases allow exploration of how species ranges shift through time. One of these tools, Map of Life, has integrated Shared Socioeconomic Pathways (SSPs) to project species occurrences and ranges (based on suitable habitat) through 2070. The different SSPs use variable greenhouse gas emissions scenarios with different climate policies, ranging from sustainable futures to fossil-fueled development. This activity first allows students to explore current ranges and suitable habitat of individual species, globally. Then, students use different SSPs to investigate future projections of species ranges and relate changes in range size to suitable habitat and life history traits.

This module explores the introduction of the American bullfrog on their ecosystem. Using species diversity calculations and data collection techniques, students explore how the bullfrog affected the species in its community. Students are introduced to calculations like species richness, species evenness, and species diversity indices. Also, this activity provides students an understanding of how this information is gathered in the field and provides them an opportunity to learn how to collect data themselves.

Meiosis modeling

In order to introduce students to the concept of molecular diversity, we developed a short, engaging online lesson using basic bioinformatics techniques. Students were introduced to basic bioinformatics while learning about local on-campus species diversity by 1) identifying species based on a given sequence (performing Basic Local Alignment Search Tool [BLAST] analysis) and 2) researching and documenting the natural history of each species identified in a concise write-up. To assess the student’s perception of this lesson, we surveyed students using a Likert scale and asking them to elaborate in written reflection on this activity. When combined, student responses indicated that 94% of students agreed this lesson helped them understand DNA barcoding and how it is used to identify species. The majority of students, 89.5%, reported they enjoyed the lesson and mainly provided positive feedback, including “It really opened my eyes to different species on campus by looking at DNA sequences”, “I loved searching information and discovering all this new information from a DNA sequence”, and finally, “the database was fun to navigate and identifying species felt like a cool puzzle.” Our results indicate this lesson both engaged and informed students on the use of DNA barcoding as a tool to identify local species biodiversity.

Primary Image: DNA Barcoded Specimens. Crane fly, dragonfly, ant, and spider identified using DNA barcoding.

Antibiotic resistance is a global public health concern. Bacteria have evolved resistance to most antibiotics, which means that for any given bacterial infection, the bacteria may be resistant to one or several antibiotics. For effective treatment and to control the spread of resistant strains of bacteria, accurate and efficient detection of resistance is important. It has been suggested that genomic sequencing and machine learning (ML) could make resistance testing more accurate and cost-effective. Given that ML is likely to become an ever more important tool in medicine, we believe that it is important for pre-health students and others in the life sciences to learn to use machine learning tools. This paper provides a step-by-step tutorial to learn four different ML models to predict drug resistance for E. coli isolates based on genomic data. The tutorial is accessible to beginners, doesn’t require any software to be installed as it is based on Google Colab notebooks, and can be used in undergraduate and graduate classes.

Signaling and gene expression are fundamental to cell biology and developmental biology. Although these topics are highly interrelated, they typically appear in separate units in a course. We use a series of short problem-based learning exercises for two complementary purposes: 1) to promote a better understanding of the mechanisms of signal transduction; and 2) to reinforce students' understanding of cell- and tissue-specific gene expression. Moreover, the exercises promote synthesis of these two topics in the context of real biological problems. The first small-group exercise that we present poses questions about the implications of cell- or tissue-specific expression of signaling molecules, encouraging students to synthesize information when thinking about biological systems. The second exercise asks students to apply the principles of signal transduction to interpret data presented in a case study based on mutations in a MAP kinase pathway that cause Noonan syndrome. Both in-class exercises present opportunities for the students and the instructor to assess the students' understanding of signaling mechanisms. Finally, we include a set of guiding questions on the Wnt signaling pathway as an out-of-class assignment, to be followed by a quiz on Wnt signaling as a summative assessment.

I implemented Unit 5 of the "Climate of Change" module into two weeks of my nonmajors Environmental Science course to cover the concepts of atmospheric science, climate change, and data evaluation.

The BioSkills Guide comprises program- and course-level learning outcomes for the Vision and Change core competencies that elaborate what general biology majors should be able to do by the time they graduate.

Students typically find linear regression analysis of data sets in a biology classroom challenging. These activities could be used in a Biology, Chemistry, Mathematics, or Statistics course. The collection provides student activity files with Excel instructions and Instructor Activity files with Excel instructions and solutions to problems. Students will be able to perform linear regression analysis, find correlation coefficient, create a scatter plot and find the r-square using MS Excel 365. Students will be able to interpret data sets, describe the relationship between biological variables, and predict the value of an output variable based on the input of an predictor variable.

Using oVERT project models students examine examples of extant traditional lizards, snakes and limbless lizards and create phylogenies based on trait and genetic data.

place based cure

This Practical Guide in the Bringing Bioinformatics into the Classroom series introduces the idea of computers as tools to help understand aspects of biology.