I'm Molly Schauffler and I teach  SMT504 Integrated approaches to Earth Science Education Part 2
I am faculty in the department of, the school of Earth and Climate Sciences, and I am part of the RiSE center - the center for research in STEM education.
The course SMT504 was started about 15 years ago and it arose out of a concern I had, after interviewing teachers, science teachers, all around, actually around the country in California, Oregon
and Massachusetts and Maine um to find out how they might engage their students in community based environmental research as a part of their science education.
So how could they get students working with real data and exploring it to learn the science content they had to
and teachers universally told me that one of the biggest barriers they experienced was students, and their own inability to know was to do with data.
The research side, so, how do you get data and what do you do with it?
So I developed this course in I think 1999 was the first time I taught it and mostly the people who took it were practicing teachers.
And at that time agencies were just coming out with large data sets, environmental data sets, and computers were just coming into the classrooms
and teachers needed a lot of help with how to work with data, how to use spreadsheets, how to graph data electronically.
So, over the years, the course had evolved from that to much more of the pedagogical aspects of working with data.
More participants in the class were MST students and they often came into the class with background in science research and working with data.
So we focused a lot more on the pedagogical aspects.
Coincidental with that, about five year ago, we started a project here in Maine, the Maine data literacy project, and came up with a strategy, a framework, for teaching data literacy skills in science learning.
So the course reform I implemented in last falls class, funded by the NOYCE grant that we had, was to shore up the pedagogical approaches to building data literacy using environmental data.
So, we had developed a framework that we had good success with practicing teachers, so we shared it, I shared it in the class this past fall.
The focus was around the question of "How can we get students feedback on the graphs and the interpretations that they do make using data?" "How can we give students feedback that scaffolds their skill and gives them a framework to really think about data in a coherent way?"
And really deepen their interpretation of data?
So, that involved giving a pre-survey at the beginning of the course to the participants in the class
Which were samples of, in part, samples of students graphing and data interpretations
and then asking the teachers in the class to evaluate those, assess those student responses.
and give feedback to students and then gave those same questions and samples of student work at the end of the class to see if there was any difference in how teachers gave feedback
So, I am still in the process of analyzing those but feedback from teachers is positive that, that aspect of the class did deepen their thinking about the pedagogy around data literacy
I also get feedback from, actually, just today I got feedback from a teacher who tried something with students, 8th grade students,
and was very encouraged and surprised by how useful this approach was with a group of 8th grade students looking at water quality data.
So, It looks like it was a good success
