COASTWISE: An Evaluation of a Wonderful Program

A week inside COASTWISE 2026 — where students built real instruments, collected real data, and asked real questions about the coastline they call home.

On a Monday morning in late July, sixteen students filed into Building 25a at State College of Florida in Bradenton and sat down in front of tables scattered with small cardboard boxes, circuit boards, and what looked like the insides of a DVD player. By the end of that first day, most of them had built a functioning spectrometer. By Friday, they had used it to collect reflectance data from mangrove leaves, compare their readings to NASA satellite records, and present research findings to a room full of scientists, educators, and their own peers.

That’s COASTWISE — Community Observation and Analysis using Spectroscopic Techniques and Wetlands Imaging to foster Stewardship of our Environment — a free, week-long STEM program run by the Science and Technology Society in Manatee County. This summer’s Part 1 session ran July 20–24 at SCF Bradenton, and I was there all five days in my dual role as marine science instructor and formal program evaluator.

What follows is a day-by-day account of what happened, woven together with what the data actually showed about how students learned.

Day 1: Mangroves Up Close, NASA Data from Above

These were honest answers, and that honesty mattered. The program used a formal pre- and post-course evaluation instrument across 18 items — fourteen of them carried over from the 2025 version to allow year-over-year comparison, four new ones targeting 2026-specific goals around spectroscopy literacy, NASA data use, and science identity. Before a single lesson was taught, students were baseline-assessed so we could measure what actually changed.

Students spent two-plus hours with me working through Florida’s three mangrove species — red, black, and white — using a combination of actual specimens (leaves, pneumatophores, propagules), a dichotomous identification key, and a jigsaw activity on ecosystem services. Each group of students became the classroom expert on one service category: coastal protection, blue carbon storage, nursery habitat, water quality, biodiversity, or economic valuation. They had to present it to the rest of the group and field questions.

The town hall debate that followed was the liveliest moment I observed all week. Students were assigned stakeholder roles — developer, commercial fisher, Suncoast Waterkeeper representative, county planner, marine science student — and given a scenario: a waterfront developer in Manatee County wants to clear two acres of mangrove fringe for a marina. The room got loud in the best way.

That engagement showed up in the pre-to-post data in a way that was hard to ignore. On the survey item “I am familiar with mangrove ecosystems,” new students moved from an average of 1.55 out of 3 at pre-course to 2.89 at post-course — a gain of +1.34, the single largest shift of any item in the entire 18-question instrument. On “I understand how mangroves affect other species in coastal ecosystems,” new students gained +0.96. Five of nine new students with complete data went from marking Disagree to Agree on the familiarity question. Five students. Complete reversals.

The pre-course survey responses themselves told the starting story clearly. “Mangroves are plants,” one student had written. After the lesson, that same student wrote: “Mangroves create carbon sinks, provide food and shelter for animals, and protect from hurricanes.” One week. That’s the gap instruction is supposed to close.

After introductions — including a visit from Mike Taylor, Chief Engineer of the NASA STELLA program, who explained how STELLA spectrometers are used for plant and agricultural monitoring around the world — students got to the build. Working in teams alongside a high school peer development team who had helped design the program, they assembled NASA’s DIY STELLA Q2: an 18-channel Visible and Near Infrared spectrometer that requires no soldering. The DVD fragment they’d puzzled over earlier became a diffraction grating, splitting incoming light into its component wavelengths.

By late afternoon, the mood in the room had shifted. As my observation notes from that day record: “once students got STELLA built, students were excited and asking about learning the software program.” Students who had been quietly listening through lectures were suddenly leaning over each other’s shoulders, troubleshooting assembly issues, conferring with the development team. The productive struggle was real — engagement scores for that activity hit 4 out of 5 — and it was the most animated the group had been all day.

The week had started.

Day 2: Taking Readings, Asking Questions

Tuesday brought new students — two who couldn’t make it on Monday — and a full shift toward doing rather than learning about. After getting the latecomers caught up and STELLA’s software installed on everyone’s laptops, the group headed outside.

With guidance from the instructional team and the student development crew, students took their first real spectral readings. They pointed STELLA at different plants, worked through sun-position calibration issues, and recorded batch data. When something went wrong with a reading — sensor angle, ambient light contamination, instrument calibration — they didn’t wait to be told how to fix it. They figured it out.

That engineering problem-solving registered in the observation data. Peer collaboration and productive struggle both scored 5 out of 5 that day. Students who the previous afternoon had been too nervous to ask questions were now flagging instructors across the room to show them something interesting in their data.

My NASA Data

After lunch, we shifted to satellites. The setup was a question: you’ve been reading one leaf at a time with STELLA. How do scientists read an entire coastline?

That gap — from centimeters to kilometers — is exactly what NASA’s My NASA Data portal is built for. Students navigated the Earth System Data Explorer together, learning to select a variable (we started with NDVI, the Normalized Difference Vegetation Index), draw a geographic region, set a time window, and interpret the time-series graph that generates automatically. We used the Manatee River estuary as our target area — a place several students had driven past, fished in, or kayaked on — which made the data immediately readable rather than abstract.

When students extended the time window to five years and looked for anomalies, something clicked. The class identified NDVI drops corresponding to Hurricane Ian in 2022 and Helene in 2024. Several students in the room had evacuated for Ian. They were now looking at a satellite record of an event they had lived through, encoded as a vegetation health signal. The conversation that followed — about why a hurricane causes an NDVI drop, what recovery looks like in the spectral record, and how that connects to the prop roots they’d examined that morning — was the kind of cross-domain thinking the program is designed to produce.

On the evaluation item “I know how to find and use NASA Earth data to answer a scientific question,” new students entered the program at a mean of 1.55 (near Disagree) and left at 2.56 (near Agree) — a gain of +1.01, the only item in the dataset where new students exceeded a full scale point. On “I understand how ground-level measurements connect to satellite observations of the same landscape,” the gain was +0.92.

Students also got an introduction to Claude AI as a data analysis assistant, walking through how to use it to process spectral output files. My observation note from that session flags something worth naming directly: the AI demonstration worked better as a concept than as instruction. Students needed to try it themselves. The lesson for next year is the same one that runs throughout the week — show and do beats show and tell, every time.

Guest speaker Matthew Pearce from NASA’s Educator Astronaut Program joined via Zoom to connect the week’s work to a bigger context — the Nancy Roman Mission, climate science, NASA internship pathways. He directly encouraged students to see COASTWISE as a gateway into NASA’s broader science ecosystem, pointing toward programs like FL Space Grant and the STEM Educator Ambassador network.

The conversation that resonated most, though, happened outside on the grass, STELLA in hand, when a student asked about a specific band in the electromagnetic spectrum and the instructor walked them through exactly what that wavelength reveals about plant physiology. One-on-one, in the field, with a real instrument.

Day 3 & 4: Data, Development Team, and the Drone Horizon

Wednesday and Thursday was a synthesis day. Students returned to their STELLA data, working through the spectra they’d collected from the mangroves and other plants with growing fluency. The development team — high schoolers who had participated in previous years and helped design and run the program — pitched a research idea to the group. Watching younger students respond to near-peers with genuine intellectual engagement was one of the quietly remarkable things about the program structure.

A Zoom session with Luca Stine, the AI and software developer who built the web application used for STELLA data processing, walked students through analysis workflows. The observation notes flag what my post-course student feedback confirmed: structured, hands-on analysis time would have served students better than a demonstration. That’s not a criticism of the content — it’s a design note for Part 2 in August.

One observation from Thursday that stood out: by this point in the week, students who had barely spoken on Monday were getting up voluntarily to take spectrometer readings from the mangrove specimens. The behavioral shift from passive observer to active participant was visible and gradual, exactly what experiential learning research would predict.

Day 5: Presentations, Reflection, and What Comes Next

Friday was a half day for the non-development students. Before anything else, post-course surveys were completed — administered as a structured, scheduled activity rather than an optional add-on, which contributed to the 88% post-course completion rate (a substantial improvement over COASTWISE 2025’s 50%).

The morning’s centerpiece was a student symposium. Six presentations in just over an hour, two minutes of questions each. Students presented on program design, spectral data analysis, the STELLA spectrum viewer interface, project management, My NASA Data applications, NASA Worldview, and housing design for the STELLA instrument. Gabi — one of the five returning students who had been through COASTWISE 2025 — presented on My NASA Data. The depth of that presentation reflected a year of compounding.

Students who had written “I am not sure what a spectrometer is or what it does for studying plant life” at the start of Monday were, by Friday morning, explaining electromagnetic wave reflectance to a room of adults.

What the Data Showed

A few numbers worth pulling out of the formal evaluation:

Across all 16 students, the biggest pre-to-post gains were concentrated in exactly the areas the program targeted most directly. Mangrove familiarity and ecological understanding showed the largest shifts. Spectroscopy comprehension and NASA data navigation — both new to the 2026 curriculum — showed strong gains among students who started near the floor. The economic value of ecosystems item (+0.71 for new students) suggests the jigsaw activity moved more than content knowledge — it shifted the way students thought about why a wetland is worth protecting.

The five returning students (identifiable by the -DT suffix in the evaluation data) entered 2026 with meaningfully higher baseline scores on almost every item. On mangrove familiarity, the gap between returning and new students at the start of the week was 1.46 points on a 3-point scale. That’s not just knowledge retention — it’s the program working as designed, building year over year. Returning students showed no net change post-course, which reflects ceiling effects on a 3-point scale rather than lack of engagement. Their story lives in the qualitative reflection data, where their comments showed the sharpest analysis of the program’s structural strengths and gaps.

One finding deserves honest attention. The science identity item — “I see myself as someone who does real scientific work, not just learns about it” — showed a small decline among new students (-0.16). It’s counterintuitive for a program that had students actively building instruments and collecting data. The most likely explanation is calibration: students who came in with an optimistic self-assessment encountered the genuine difficulty of real science — the calibration errors, the messy data, the things that didn’t work — and adjusted their self-perception accordingly. That’s not a failure. It may actually be one of the more honest outcomes of the week. The student who wrote “felt like they were actually doing science instead of learning science” in the final reflection said the same thing differently.

What Students Said

The feedback themes from the final day were consistent and direct. Students wanted:

More hands-on, interactive activities — less lecture-heavy delivery, more doing alongside learning
More data analysis time — students were excited to collect data and frustrated when they couldn’t fully interpret it
A trip to actual mangrove habitat — multiple students asked for field access to the fringe systems they’d been studying all week
More structured scheduling — both students and the development team flagged that clearer time blocks would help everyone stay oriented

The things they loved were equally clear: building STELLA, collecting spectral data, the teamwork-building games and challenges, the collaborative work with the development team, and the sense of doing something real.

One student’s post-course reflection on the sense of place question is worth quoting directly: “The beach is very meaningful to me now ever more knowing that the mangroves that protect coastal waters need close monitoring.”Another, describing a bay near their hometown in China: “I only knew that it is important but I didn’t know why — but now I learned a lot about this and I know.”

That’s what a week is supposed to do.

Looking Ahead

COASTWISE 2026 continues August 3–6 at the Faulhaber Fab Lab in Sarasota, where Part 2 will take the spectroscopy work into drone-based aerial imaging. Students will attempt to fly STELLA itself, with a telescope attachment that narrows the field of view at elevation, producing spectral maps of plant clusters on the grounds.

The evaluation instrument — expanded this year with a structured mid-course reflection, a post-course extended reflection grounded in Kolb’s experiential learning framework, and a full pre/post comparison — travels with the program. Part 2 will add the STELLA-to-satellite ground-truth comparison (Scenario D from the My NASA Data lesson) as a live field activity, with students designing their own spatial sampling protocol.

There is something clarifying about watching a student hold a spectrometer over a mangrove leaf, look at the spectral output on their laptop, and then pull up the MODIS satellite record for the same estuary and ask — unprompted — why the numbers are different. That question is not taught. It emerges when students have enough understanding to notice a gap.

COASTWISE exists to create the conditions for that question to arise. On the evidence of this week, it’s working.