Recruiting for our training wasn't extremely difficult.  At the start of the project my wife was an Ag teacher, so she was able to post a survey that was available to every ag teacher in the state to get some input as we designed our approach.  Then we put a call out through the same channels for teachers to apply.  Ag teachers are not known to be the most progressive group of teachers, and they tend to be about the busiest and most project-laden teachers I've seen, but we got a satisfactory number on board for this scary new venture.  We presented some of our content at a state science teacher conference and filled the rest of our quota.  We had one person who wasn't able to make our initial summer training, who went radio silent in our efforts to get him caught up.  Another teacher dropped out after our pre-pilot semester, in which we did a small test of curriculum and assessment tools before training the full cohort.  I knew this teacher personally, and she had a ton on her plate already, so it was understandable that she didn't feel like adding more.

Almost all of our teachers began implementing our content toward the end of the school year, so we actually haven't gotten a wealth of feedback from them yet, although I did observe each of their classrooms, and we will be analyzing classroom videos and teacher reflections to get a better idea of how things went in the long-run.  The biggest challenge that teachers and students seemed to face with the projects wasn't the programming, as much as it was dealing with electronics issues... There are sometimes a lot of wires going to a lot of places, so even with instructions, errors are made.  I don't know whether to feel bad about this as a frustrating barrier to learning about coding, or good that students are learning how to methodically troubleshoot complex systems.  

Two things have helped implement Arduino, and we saw it with both the teachers and students:

1) We used the Tinkercad platform to bridge the gap between Scratch and Arduino.  It's shown briefly in the video (@ 1:03).  Users can build breadboard simulations or use pre-built Arduino setups, then code them with Scratch-type blocks or with C+ Arduino code.  Or the cool thing is that they can use the Blocks & Text setting to build code with blocks and see it instantly translated into C+ text.  Some of our pilot teachers had to start by building their projects with blocks and copy/paste the Tinkercad text code into the Arduino IDE to send to their real Arduino and make it work.  It was a longer process, but it got them to a point where they could do it on their own once they saw how to type out what they had previously blocked out.

2) The tutorials explicitly model the fact that you don't have to "create new Arduino code" to make something new.  I am not very good at writing a program out of my head.  I always forget a ton of steps, like where to put "PINMODE" or how to structure a for() loop.  So the tutorials model how to find base code from Arduino's built-in examples or its online tutorial resources, and borrow the pieces that need to work together to make the project function... Want to make a servo work based on temp readings?  Open the "Knob" example and the "LoveOMeter" example, and put them together.

I have been teaching TinkerCad for my sophomore level college course, which uses our campus Makerspace. I had not thought about using it with the Arduinos, we were using it for 3D printing. I will check that out!

Also the chicken coop door idea is very popular - our local high school Makerclub that spun off my college program did that as one of their projects, and our Learning by Making students are also fond of the idea! As someone who lost my chickens to a very smart racoon, even with doors, I appreciate the design work!

We're still waiting on our post-implementation data for our first year, so any conclusion so far won't be very generalizable.  One thing that we saw with the pre-data for classes of 8th grade students was that about 18% had "correct" attitudes toward aspects that contribute to CS success.  This includes questions relating to a growth mindset, tenacity in problem-solving, and an interest in CS topics.  Their answers jumped to over 40% in the post-test, and this was just based on going through the introductory module, not the ag challenges.  Is 40% a good result? We'll have to see, but it's definitely a good amount of growth.  The teachers who supplied this data also did a great job of using Computational Thinking vocabulary with the kids, which showed up in the buy-in of students and their own use of reflective terminology when working.

I hope to be most surprised by interesting independent student projects.  This week I had to shoot some emails back and forth with a teacher who was helping his student troubleshoot his fishing reel alarm.  (Sense motion = LED on)  The cool thing is that using this sensor wasn't part of our curriculum, so he brought in outside resources and concepts to apply to something he found useful.  

For selecting our topics, we basically tried to think of projects that could apply to the standard courses that nearly all ag programs have: Animal Science, Horticulture, and Ag Mechanics.  We pitched several ideas to the pilot teachers, and we used their feedback to select what we would tackle with our modules, in a way that would balance the types inputs and outputs used, and possible programming complexity... When to introduce variables, "While" loops, functions, etc.  While adding the CS components to something like Animal Science requires a bit of a shoehorn, all of our hands-on modules would fall right into the Advanced Ag Mechanics course.  Most of our science teachers are implementing this in engineering-based "STEM" courses, although we do have a biology teacher using it in his horticulture class, which operates a greenhouse and outdoor growing area. 

As for GIS, there is SO MUCH in ag operations and support services, but SO LITTLE training for ag teachers to enable their students to use it. Your project looks like it really delivers high-level analysis of so much data (and your students have a very impressive ease with the vocabulary and concepts of data literacy, so props on that).  That's definitely the type of data analysis that ag producers are using on a daily basis to make decisions.  I like the potential of the MIT App Inventor tool to enable students to develop spatial skills with GPS, since students can develop apps that use a phone's location data.  In addition to the one shown in the video, we show how to make a "Tree Tracker" app that lets users enter specimen data into a database and mark their tree specimens on an interactive map.  It's probably on the low end of GIS outcomes, but there is potential there.

That info is still tied up in this year's final data that we will be sorting through in the next month or so.  We are really looking forward to next year to see what students come up with in a 2nd round of implementation, where some will get a 2nd dose.  And we are starting to plan for a project showcase next year, partly inspired by some of the ideas we saw here in the Video Showcase.

One of our "rural" schools has basically been swallowed up as a Kansas City suburb over the years.  When I observed the horticulture teacher's class I was very pleased to see the focus question written on the whiteboard: "How can we use urban gardening to connect our community with healthy foods?".  One of our advisory panel members has a big focus on urban agriculture and is excited about what we are doing.  So while our foundation was meant to even the playing field for rural students through a culturally-relevant introduction to CS,  the urban applications of our curriculum are on our radar as a possible investigative route when we go for a 2nd round of funding.