Georgia Titcomb
PhD Student in Ecology, Evolution, and Marine Biology; Master's Student in Statistics
Hands-on activities and opportunities for exploration and creativity have kept me on my learning journey through the trials and tribulations of understanding statistics.
Statistics: A story of questions and numbers
I'm an ecologist who loves statistics; and, having been both a learner and instructor in several statistics courses, I find that I prefer to ground my teaching in relatable examples or interesting stories. Statistics is fundamentally an exercise in curiosity: in answering questions and finding patterns to improve our understanding about something we didn't know before. As an instructor, I'm very excited to share this philosophy with students, and I come back to my own experiences as a learner, especially for concepts that I struggled (and still struggle!) to understand. I recognize that I learn best by feeling motivated and interested in solving a problem, approaching a problem equipped with the tools to tackle it, and having confidence in my abilities and creativity. In my teaching, I use a variety of Grasha's 5 teaching styles, depending on the course content and which of these goals I'm focusing on.
"I believe that having the freedom, curiosity, creativity, and confidence to understand the story in a dataset is important to learning and to being a good statistician.”
Part One: Inspiring Interest
Statistics is a (relatively) new field compared to other mathematical disciplines, but its applications are diverse and relevant across fields. Yet, despite the wealth of resources and interdisciplinary opportunities, I've been in many classes where instruction focuses purely on numerical patterns and properties. While these are certainly important, I don't find this immediately inspiring to a learner just beginning to grapple with the material. Therefore, when I first introduce a concept and related problems, I like to show why it's important and to convince students how it's relevant outside of the classroom. I like to use facilitative teaching tools to get students actively involved in thinking about how this concept might build on previous ideas (e.g. what if we have a dataset where observations are not independent? Or, what questions would you ask the researcher who collected this dataset?)
Part Two: Building Confidence
I recognize the importance of equipping students with content and resources to solve a problem, and that concrete assessments are needed to build confidence through evidence of success. I use more authoritative and demonstrative teaching methods to convey material and to provide feedback through formative assessments (e.g. short quizzes or homework problems). I like to ask students to solve problems and to compare their solutions with each other as another way to build confidence. As a learner, I found that these sorts of assessments and opportunities to teach and learn from peers were very important in building my self confidence.
Part Three: Facilitating Exploration
However, I feel that long-term learning occurs best when students are given the opportunity to be creative and to apply their new skills to problems that they really care about. In this phase of teaching, I shift back to a role of being a facilitator or delegator, and have students work on an individual or group project of their choice.
I think these approaches are definitely informed by my personality. I am neither introverted nor extroverted, so I like the idea of interacting with students in a larger lecture setting and in meeting with them to discuss group projects. I'm very open to new ideas, which makes me inclined to solicit feedback on the course and to spend more time on content that might be confusing. Finally, my personality is a tad wacky and imaginative -- I have a strong desire to turn mundane datasets into an interesting story. (For example, as a student, I once converted an assignment to analyze a simulated dataset into a Lion King-themed story about Timon and Pumbaa's quest to start a profitable realty company in the African savanna). I believe that having the freedom, curiosity, creativity, and confidence to understand the story in a dataset is important to learning and to being a good statistician.
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