Teaching Statement

We are living through a moment that demands ecological thinkers: people who can look at a changing world and ask meaningful questions. This shapes how I teach. As a biodiversity ecologist studying how big data can help us understand climate change’s impacts on forests, I am constantly reminded that the concepts I teach are not abstractions, rather they are tools students will carry beyond their coursework. For me, education is the most powerful form of connection, a way to transform complex ideas into moments of wonder that send students back into the world asking new questions.

I am a fourth-year PhD student at the Nicholas School of the Environment, where I have had the opportunity to develop this philosophy across a range of teaching contexts: undergraduate and graduate courses, large lectures and small seminars, classrooms, computer labs, and field settings. Among all these settings, my central commitment remains the same: to foster curiosity, build inclusive and supportive spaces, and help students see themselves as active participants in science rather than observers of it.

Designing and Planning for Learning

As I design learning experiences for my students, I value understanding who my students are before they walk in the door. In my weekly discussion sections for Introduction to Environmental Sciences and Policy, a large lecture course where discussion was often students' only opportunity to engage personally with the content and their peers, I asked students to fill out a pre-survey where they could share about their background, prior positive discussion experiences, and visions for inclusivity in our group [V1]. Their responses directly shaped my planning. When students expressed a preference for small group discussion before sharing with the larger group, I built a scaffolded discussion arc, working from individual reflection in a think-pair-share, progressing to small-group conversation, and culminating in peer-led whole-group discussion. Each stage was designed to build students’ confidence before asking them to share more widely [A1/V2].

Designing for this level of participation also required intentional structure from day one. For many students, this was their first time considering environmental science in the context of their own lives, and I recognized that meaningful engagement would require both safety and structure. I scaffolded our discussions with AORTA Collective’s Anti-Oppressive Facilitation for Democratic Process community guidelines to set norms for equitable participation and respectful dialogue [A1/V4]. Students later said that they “loved how we discussed expectations on day 1”, something they said was rare in their other courses.

As the semester progressed, I included ways for students to take ownership of their learning, giving students the chance to lead a group discussion with 3 other classmates [V2]. One student noted that this helped them “engage more with the content”. For their final projects, I designed a two-minute pitch session so students could receive peer feedback before finishing their projects, and I offered flexible format options: research paper, podcast, video, to honor different strengths and learning styles [V2]. The range of submissions I received confirmed that structure and flexibility can coexist, as students took more ownership over their projects, and the quality of work I received was stronger for it.

Teaching and Supporting Student Learning

Leading twice-weekly lab sections for Applied Statistical Modeling for Environmental Management has taught me that responsive teaching means constantly assessing understanding and adapting on the fly. In these lab sections, I guide master’s students through R programming tutorials that extend lecture concepts into practical analysis of real datasets. Because students enter the course with various coding backgrounds, I have learned to explain statistical concepts through multiple approaches: visual representations, worked examples, and analogies to familiar scenarios. The goal is to find the explanation that fits the student, not just the concept. When one student asked about the difference between a confidence interval and a p-value and my initial explanations weren't landing, I kept trying different angles until an analogy about fishing finally clicked for her [A2/K3]. Similarly, when students struggled to understand what QQ plots were displaying, I developed a short slide deck breaking down the concept visually, step by step, and paired it with a practice problem students worked through together at the board [K4]. Watching them point at the data and discuss what the deviations meant showed me what the move from confusion to understanding actually looks like [A2/K1].

To assess comprehension in real time, I pause activities with questions during labs like, “What do you expect to see here? Why might this assumption matter?” These questions help students and me identify where understanding breaks down and allow me to provide targeted support [A2/K3].

Assessing and Giving Feedback for Learning

As a TA for Data Visualization and Storytelling for Duke’s Master’s in Interdisciplinary Data Science, I provided written feedback on students’ problem sets that explained why certain approaches were more or less effective and offered specific strategies for future work. Rather than stopping at the rubric score, I tried to connect my feedback to the principles behind good visualizations from lecture, so students understood not just what to fix but why it mattered. Even technically correct work received feedback grounded in course principles that they could carry forward [A3]. With each assignment, I could see students applying comments from previous rounds, confirming that improvement-focused feedback encourages students to engage with the content more intentionally rather than just chase a grade.

Writing and grading exams for Plant Communities of North Carolina gave me a different perspective on assessment. I collaborated with the instructor to write exam questions, requiring careful thinking about how to asses students’ understanding, and how to make expectations clear to students before they take the exam [A3/V5]. Sitting side by side with the instructor to deliberate over student responses, I saw how much interpretive judgment goes into evaluation. These conversations about what a response correctly explained versus what it missed, and whether our standards were being applied consistently across all exams, showed me that fair assessment is itself a collaborative practice, requiring ongoing calibration rather than a fixed rubric [A3/K5].

Supporting and Guiding Learners

Some of the most meaningful support I have provided for students happened outside, guiding 12 undergraduates through diverse ecosystems from North Carolina’s Piedmont forests to coastal plains as a TA for Plant Communities of North Carolina [A4/K2]. When we were on field trips, I would circulate among the students, asking questions designed to push past identification toward interpretation: Why these species here? What does this composition suggest about disturbance history? Over time I watched students make the shift from memorizing plant names to noticing patterns in community composition and asking ecological questions of their own [K1]. Taking students out of the classroom and into the field helped me show them the natural world as a place of inquiry, not just a place to learn content.

Beyond field instruction, I hold weekly office hours for Applied Statistical Modeling for Environmental Management, creating space for students to work through coding challenges or lecture content one-on-one [A4]. But these office hours serve a purpose beyond troubleshooting: I intentionally ask students how the course is feeling for them and invite conversation about their personal and professional goals by sharing about my own [V1]. These are questions I rarely have time for during lab. Building these personal connections creates trust that transforms office hours from a simple help session into genuine mentoring relationships, where students feel comfortable admitting what they do not yet understand.

Engaging in Professional Development as a Teacher

My growth as a teacher has been shaped as much by deliberate study as by classroom experience. Through Duke’s Certificate in College Teaching, I have built a grounding in evidence-based teaching practices, moving from intuitive decisions to intentionally designed learning experiences informed by research on how students learn [A5/V3]. In a course titled Teaching in Biology, for example, we read research on effective assessment methods and applied these strategies directly to our own lesson plans.

Currently, I am participating in the Teaching on Purpose Fellowship through Duke’s Kenan Institute for Ethics, where we grapple with foundational questions like “Why teach?” and “Why learn?” These conversations push me to articulate not just how I teach content, but what purpose my teaching serves beyond delivering content and what I hope students carry with them long after the course ends [K1]. Together, these experiences have reinforced that becoming a better teacher is an ongoing practice of reflection, learning, and revision.

Looking across my teaching, a few commitments remain consistent: listening before designing, building structure that makes risk-taking feel safe, and staying curious alongside my students. Whether I am scaffolding a discussion arc in response to student needs, searching for the analogy that finally makes a concept click, or sitting with a student in office hours to listen to how the course is feeling, I am guided by the same foundation that learning happens when students feel seen and supported enough to be honest about what they don’t yet understand. My teaching philosophy is ever evolving in every class I teach, but at its center is an unwavering hope that students leave my class more confident and curious than when they arrived.

As I look toward my future as an educator, I am eager to design and teach courses in introductory ecology and environmental science, as well as data science methods for students from non-quantitative backgrounds. I want to continue developing as a teacher by deepening my practice in active learning and community-based field, finding ways to bring my students into contact with real questions. I am also committed to ongoing professional development through communities like the ones I have been fortunate to participate in at Duke. Ultimately, I hope to continue building a teaching practice that grows alongside my students, where curiosity is not just something I encourage, but something I continue to model.