In this lesson, students interpret a map of species occurrences. Then, students view and reflect on an interview with biologist Dr. Jennifer Dean, whose research includes the map that they interpreted.
graph interpretation, Invasive Species, Aquatic invasive species, spatial data, women in stem, invasive plants, Citizen and Community Science, BioGraphI, representation in STEM, map interpretation, iMapInvasives
493
356
0
0
07.2023
In this lesson, learners interpret a table summarizing the factors influencing the persistence of Black students at an HBCU. Then, learners view and reflect on an interview with science education researcher Dr. Catherine Quinlan, who collected the data that they interpreted.
biology, data interpretation, hbcu, Self-Efficacy, BioGraphI, representation in STEM, #BIPOCinSTEM, Black representation in STEM
2.0K
886
0
0
08.2022

Make Your Move: Interpreting graphs of pollinator behavior

Rachel Pigg, Suann Yang

Version: 1.0

In this lesson, students interpret graphs of pollinator movement behavior. Then, students view and reflect on an interview with community ecologist Dr. Suann Yang., who collected the data that they interpreted.
graph interpretation, Community Ecology, Biodiversity, competition, data literacy, pollination, invasive plants, interspecific interactions, BioGraphI, representation in STEM, #AAPIinSTEM, #BIPOCinSTEM
3.1K
1.4K
0
1
08.2022
In this lesson, students review plant-pollinator interactions and global change concepts. Next, students interpret graphs of pollinator visitation data to Scarlet Gilia. Then, students view and reflect on an interview with community ecologist Dr. Connor Morozumi, who collected the data that they interpreted.
mutualisms, graph interpretation, Community Ecology, plants, fmn, global change, pollinators, BioGraphI, representation in STEM
45
11
0
0
05.2024
In this lesson, students discuss the effects of disturbance in marine environments with a focus on pollution. They also evaluate the anthropogenic causes and consequences of pollution on a variety of marine ecosystems. Students then interpret a graph of oil pollution on tissue apoptosis in larval Red Drum. Finally, students view and reflect on an interview with Dr. Rachel Leads, the biologist who collected the data that they interpreted.
fish, graph interpretation, fmn, marine ecosystems, marine ecology, microplastic pollution, Ecological Disturbance, intermediate disturbance hypothesis, student STEM identity, pollution, BioGraphI, representation in STEM, oil spill
318
164
0
0
02.2024

Antibiotic Resistance of Bacterial Soil Isolates and Biofilm Production

Stephanie Mathews, Danielle Graham

Version: 1.0

In this lesson, learners will hear about research that focuses on bacterial antibiotic resistance and biofilm production. Students will see how antibiotic resistance is measured and interpret a graph measuring biofilm production of these bacterial soil isolates. Then, learners view and reflect on an interview with microbiology researcher Dr. Danielle Graham, who collected the data that they interpreted.
graph interpretation, microbiology, biofilm, fmn, antibiotic-resistance, BioGraphI, representation in STEM
279
211
0
0
12.2023
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.
evolutionary ecology, graph interpretation, fmn, BioGraphI, representation in STEM
736
250
0
0
07.2023

Defenses against predation: Interpreting graphs of predator behavior

Jennifer Schafer, Lynette Strickland

Version: 1.0

In this lesson, students discuss anti-predator defense mechanisms and the types of cues defenses provide to predators. Students then interpret graphs of behavior of arthropod predators when presented with different phenotypes of color polymorphic tortoise beetles. Finally, students view and reflect on an interview with Dr. Lynette Strickland, the biologist who collected the data that they interpreted.
graph interpretation, fmn, data literacy, interspecific interactions, consumption, BioGraphI, representation in STEM, arthropods, aposematism, phenotypic variation, tortoise beetle, carton-nest ants, praying mantis, orb-weaving spider
391
316
0
0
07.2023

How We Help: Human elements of restoration ecology

Sophia Anner, Anna Sher

Version: 1.0

In this lesson, students recall the basics of restoration ecology, interpret and predict several graphs that explain restoration manager characteristics, and reflect on an interview with restoration ecologist Dr. Anna Sher, who wrote the paper in focus in the lesson.
graph interpretation, Ecosystem Ecology, fmn, conservation biology, data literacy, invasive plants, LGBTQ, Restoration Ecology, riparian ecology, Natural Resource Management, BioGraphI, representation in STEM
492
297
0
0
06.2023

Biodiversity Counts! Making sense of diversity metrics and graphs

Ana Elisa Garcia Vedrenne, Maria Rebolleda Gomez

Version: 1.0

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.
graph interpretation, fmn, metabarcoding, biodiversity literacy, BioGraphI, representation in STEM, alpha diversity, beta diversity
988
658
0
3
06.2023

From Nano to Life: Interpreting graphs from Nanopore sequencing of bacterial genomes

Carlos C. Goller, Carly Sjogren, Jason Williams

Version: 1.0

In this lesson, learners meet several scientists working on sustainable ways of recycling discarded electronics. Through an interactive H5P activity, participants watch videos and complete a series of knowledge checks. In the process, they meet Jason Williams and learn how Nanopore sequencing works. Importantly, Williams teaches learners how to analyze output from Oxford Nanopore sequencers.
graph interpretation, fmn, Nanopore, Representation, BioGraphI, representation in STEM, Nanopore sequencing
472
439
0
0
05.2023