Published: February 12, 2024
Mr. Newland writes:
The way I see astronomy education and how students might interact with astronomy education has been transformed by my exposure to IRSA and datasets I have wrangled using IRSA tools. NITARP is a good example of demonstrating that astronomy needs data science pedagogy and computational thinking so that students can understand the ways we do astronomy now. Being able to ask questions of NITARP and IRSA data is a skill that teachers can translate into curriculum materials and experiences. Without NITARP and IRSA data tools teachers might never learn about the wealth and breadth of data available and how to reduce, visualize, and interpret that data.
Because of my exposure to SDSS data via NITARP-adjacent projects, I have been able to work with SDSS scientists to make a few astronomy lessons. IRSA is still one of the best ways for an astronomy teacher to access SDSS data to create lessons and projects for astronomy students.
My astronomy course serves my entire school population and not just those taking advanced courses. Being able to use NITARP and IRSA related materials means that data-centric lessons can impact groups of students who can benefit from this new and innovative style of pedagogy. Teaching underserved groups to think computationally and to handle data science while also learning astronomy is truly a game changer. Students that do not typically use statistics at all are using this new kind of thinking in an astronomy context and that is amazing. Students are producing astronomical images and creating histograms and looking for correlations between variables all while using authentic data and real-world research techniques.
NITARP is a very unique and important way for the astronomy research community to give teachers authentic ways to use the data and research techniques to impact how astronomy students see science as a way of knowing and as a field of study. Certainly NITARP gives teachers the ability to make curriculum that positively influence student science attitudes and self-efficacy.
I have created four separate lab activities based on my NITARP exposure and that includes working with other NITARP teachers. Students make astronomical images from authentic data. Students measure the distances to star clusters using statistical thinking. Students create color-magnitude diagrams to figure out the relative
ages of old and not-so-old star clusters. Students can create a spectral energy distribution for a target to characterize the astrophysical nature of the target (this one is not yet done).