What is unique about your work on emerging technologies for teaching and learning?
STEM is all about trying different things, discovering something new, and building off of whatever you are passionate about. I had the opportunity to serve as Albert Einstein Fellow at the NASA Office of STEM Engagement, I had the opportunity to try something new and different and a wonderful new door opened for learning.
There are many unique aspects to incorporating emerging technologies for teaching and learning. The goal at Meharry School of Applied Computational Sciences (SACS) is to enable innovative and engaging teaching methods and learning experiences centered on data science. Emerging technologies such as adaptive learning, augmented reality and simulation, are just some of the technological areas reshaping education. Data Science highlights a trend in shaping the future that continues to make a significant impact in the industry ranging from AI, IoT, to Quantum Computing.
If your project succeeds, how will learning be transformed? If I walked into a learning environment that was using your innovation, what would be different?
Our project, “SACS Summer Data Science Academy: Promoting Data Science with Robotics and NASA Geospatial and Extraterrestrial Big Data for Grades 9-12 will bring exposure to NASA research and data science tools to underrepresented high school students. The key objective of the program is to stimulate curiosity in the cross-cutting field of data science through a discovery-based summer immersion program. Program activities will build statistical and critical thinking skills, while inspiring and diversifying the next generation of explorers, researchers, and data scientists.
Involvement in this project includes interaction with robotic guidance, remote sensing; environmental monitoring, machine learning, and data mining thus bringing a new layer of innovation in the learning environment.
How have you attended to equity-related issues within your project? Please discuss actions taken.
We are attending to equity-related issues by getting diverse participation that would not normally have access to a program of this nature.
Action steps include:
- introducing students to diverse role models in data science education
- differentiating learning pathways for students
- analyzing data science for good
- and catalyzing social change.