Placebased Data Analysis (formerly GEOG 0139) Who migrates from urban areas during a pandemic? How are livelihoods distributed around protected areas in Central Africa? How much does location influence the price of a house? In this course students will discover ways  to answer questions like these by introducing fundamentals for generating and analyzing data about people and the places they are connected to. Students will practice constructing datasets, visualizing relationships, formulating and testing hypotheses, modeling outcomes, and conveying results. We will cover descriptive and inferential statistics, focusing on geographic applications and the unique complexities of spatial data. Through cases and problem sets, students will explore complementarities between quantitative and qualitative analysis, emphasizing critical and reflexive approaches. Labs will build proficiency with software packages like R and GeoDa. The course aims to make students more savvy consumers of published work, to produce careful analysts, and to foster a deeper appreciation for the research process. No prior experience with Statistics or Geography is required; the course is designed to introduce students to approaches broadly relevant in Geography and allied social sciences.

Land and Livelihoods - From Local to Global How do flows of money, people, materials, and ideas connect local livelihoods to distant sites and global processes? How do geographers study patterns of poverty and inequality at different scales?  How do we define human development and wellbeing, how do we determine who participates, and why does it matter?  In this course we will draw from perspectives in fields ranging from development geography and political ecology to post-colonial studies to examine livelihood dynamics in the Global South. We will use texts, interviews, writing assignments, problem sets, and mapping exercises to explore relationships between economy, identity, and place in an increasingly connected world.

Environmental Change in Latin America This course examines Latin America from a geographical perspective with emphasis on the social, political and ecological underpinnings of change in the region. Building upon the theme of global environmental change in the context of human-environment geography, we will explore urgent challenges linked to the agricultural and extractive industries, urban expansion, land grabs, land reform, indigenous rights, and rural and urban poverty.

Fieldwork in Geography: Constructing Place-based Data (formerly GEOG 0339) From the presence of wildlife to the preferences of community members, we often want to understand more than we can see using satellite imagery, census tables, and existing data products alone. In this course, we will practice constructing primary data. Exploring a range of approaches from interviews to transects, we will pay attention to sources of bias, our own positionality, and the kinds of decisions one confronts when generating data. This course will provide foundational skills for students interested in conducting their own research and useful insight for interpreting data collected by others. Be prepared to spend several labs outdoors and off-campus in ‘the field’. Prerequisites: GEOG 281 or another GEOG class numbered 250-299.

Natural History of Addison County In this course, we will forge a sense of place through attention and connection— learning to see the relationships within the region's ecological communities and cultivating relationships within its human communities. To this end, students will engage in a series of field trips in Middlebury and surrounding parts of Addison County. We will use Natural History as a structuring principle, building an understanding of the ways that current landscapes are shaped by influences from bedrock geology to human history to plant and animal assemblages. Our goal over the course of the semester is to help each other find our own places within the wider community, and by so doing, to help make Middlebury feel more like home. Be ready to venture outside. [One 50-min lec. + one

Data Science Across Disciplines In this course, we will gain exposure to the entire data science pipeline—obtaining and cleaning, large and messy data sets, exploring these data and creating engaging visualizations, and communicating insights from the data in a meaningful manner. During morning sessions, we will learn the tools and techniques required to explore new and exciting data sets. During afternoon sessions, students will work in small groups with one of several faculty members on domain-specific research projects in Biology, Geography, History, Mathematics/Statistics and Sociology. This course will use the R programming language. No prior experience with R is necessary.  BIOL 1230: Students enrolled in Professor Casey’s (Biology) afternoon section will use the tools of data science to investigate the drivers of tick abundance and tick-borne disease risk. To do this students will draw from a nation-wide ecological database.  GEOG 1230: In this section, we will investigate human vulnerability to natural hazards in the United States using location-based text data about hurricane and flood disasters from social media. We will analyze data qualitatively, temporally, and spatially to gain insights into the human experience of previous disasters and disaster response. We will present findings using spatial data visualizations with the aim of informing future disaster preparedness and resilience.  HIST 1230: In U.S. history, racial differences and discrimination have powerfully shaped who benefited from land and farm ownership. How can historians use data to understand the history of race and farming? Students will wrangle county- and state-level data from the U.S. Census of Agriculture from 1840-1912 to create visualizations and apps that allow us to find patterns in the history of race and land, to discover new questions we might not know to ask, and to create tools to better reveal connections between race, land, and farming for a general audience.    STAT 1230: In this course students will dive into the world of data science by focusing on invasive species monitoring data. Early detection is crucial to controlling many invasive species; however, there is a knowledge gap regarding the sampling effort needed to detect the invader early. In this course, we will work with decades of invasive species monitoring data collected across the United States to better understand how environmental variables play a role in the sampling effort required to detect invasive species. Students will gain experience in the entire data science pipeline, but the primary focus will be on data scraping, data visualization, and communication of data-based results to scientists and policymakers.  SOCI 1230:  Do sports fans care about climate change? Can sports communication be used to engage audiences on environmental sustainability? In this section of the course, students will use the tools of data science to examine whether interest in sports is associated with climate change knowledge, attitudes and behaviors, as well as other political opinions. Participants will use survey data to produce visualizations and exploratory analyses about the relationship between sports fandom and attitudes about environmental sustainability.

Research Craft in Human Geography Whether you are planning to do your own research or want to be a more savvy consumer of research produced by others, it is useful to develop an understanding of the process of creating, discovering, and interpreting information about the world. In this course, students will explore quantitative and qualitative methodologies and the ways they can be used in human geography research. Through examples, exercises, and readings, students will learn the types of questions different techniques are designed to answer, how they work, and how to interpret the results. Students will gain hands on experience conducting surveys, generating and interpreting qualitative data, selecting and implementing statistical analyses, and writing research reports, to build competence and critical awareness in the practice and communication of research.

Practicing Human Geography Whether you are planning to do your own research or want to be a more savvy consumer of research produced by others, it is useful to develop an understanding of the process of creating, discovering, and interpreting information about the world. In this course, students will explore quantitative and qualitative methodologies and the ways they can be used in human geography research. Through examples, exercises, and readings, students will learn the types of questions different techniques are designed to answer, how they work, and how to interpret the results. Students will gain hands on experience conducting surveys, generating and interpreting qualitative data, selecting and implementing statistical analyses, and writing research reports, to build competence and critical awareness in the practice and communication of research.

Seminar in Human-Environment Geography: Landscapes in Transition  What will Vermont look like in 100 years? What about the Brazilian Amazon, the Albertine Rift, or your home town? In this seminar, we will explore the ways that processes of change discussed in our thematic Geography classes like urbanization, climate change, gentrification, commoditization, 'globalization', and more may interact and play out in the future. We will discuss studies of historic and ongoing landscape transitions and conduct our own studies of student-selected places, focusing both on the changes most likely to occur given existing trajectories, and attempting to imagine and articulate what changes would be desirable.

Jessica L'Roe

Reviews and ratings for Jessica L'Roe at Middlebury College.Jessica L'Roe teaches Placebased Data Analysis, Land and Livelihoods, Environ Change Latin America and more.  Explore top rated instructors and find the best for you.Is Jessica L'Roe good ? Find out on MiddCourses.

This class is interesting if you want to learn more about data science specifically in the context of spatial data. While it doesn’t require any prior experience with R or statistics, it would absolutely be helpful in getting off the ground. “Intro to Data Science” in the Math Department would be a great preparation for this course. 

Loved this course and was very minimal work. I pretty much never did the readings and still did really well in the class. The work for the semester comes from about 4 projects that you have to do, but Lroe grades pretty fairly. She's a very accommodating professor and it just overall a great person, would definitely recommend this class. Also as a bio major I liked the cross over to ecology that this class had. 

i loved this class! so much good info, and jess is so awesome. the material is so beneficial, the only thing that would be nice would be perhaps more open class discussions since the course was grounded in a lot of philosophy.