Over the past couple of weeks, I have been playing around with the Databot. I have a couple of takeaways from my experimentation that are relevant to this project.
I originally wanted to have some sort of real time sound data, but this proved to be more difficult than anticipated. This is challenging because In an effort to start simple, I am opting to
This past week, I was privileged to attend the Washington Oregon Higher Education Sustainability Conference (WOHESC). The conference took place at Western Washington University. The goal of the conference is to promote collaboration and facilitation of sustainability in higher education institutes around Washington and Oregon.
One speaker at the event is Todd Mitchell from the Swinomish Tribe. Todd does environmental education for the tribe. A lot of his work revolves around education of place, through interactive activities.
(Openly Published Environmental Sensing) OPEnS Lab, is a lab at OSU. This lab is overseen by Dr. Chet Udell. The lab works with environmental sensors, which is very relevant to the project that I am currently working on. One of their projects is called Weather Chimes.
This week I had the privilege to talk to Sean Rowe about this project, specifically about data visualization. Sean is the head of the Hatfield Marine Visitor Center, in Newport. Some big takeaways that I took away is that data should be easily read, which should be done by relating the data to something that a person already knows. We also talked about curriculum, what it would look like to implement it in different programs, as well as people who may have further knowledge on aspects of this project.
The first part that we talked about was data visualization. Sean has a background in this field as he is one of the first people to do active research on how people interact with learning in everyday activities. He does this by monitoring hands-on exhibits that he procures for the visitor center. He says that generally people are poor at understanding data that is presented to them. There are certain things that people presenting data can do to help make the data more readable. An example is that when he creates a map of the ocean with data on it, he will add major cities in the area onto the map, so that people will have a starting point to engage. A map of the Oregon coast would include Eugene, because many people will be able to orient themselves spatially when they see this. Another example is that he will use a blue to red color scale to represent temperature, and a green scale to represent plant growth. People relate those colors to the objects that the data is representing, which makes the data much more readable.
One final exhibit that I want to specifically point out is the topographic sandbox map. This exhibit is a sandbox with a camera above it. The camera looks at the sandbox, uses some free government software to determine the contour of the sand mounds, and then projects the topographic map onto the sand. As a person moves the sand, the topographic map changes. The map is also displayed from the bird’s eye view on a tv screen. This screen shows a 2-D map. This is a cool way of data visualization because it allows for interaction, and the 3-D map will help to connect people to what the 2-D map actually represents.
Sean’s work is primarily with data visualization, which is less challenging than data sonification. People do not know the rules for what data means when you are listening to it. He did give a good example of data sonification. This example is at the Science Museum of Minnesota, called the Seismofon. This exhibit has tubes that will play a noise whenever an earthquake occurs on earth. The noise will be a larger or smaller intensity depending on the magnitude of the earthquake.
We talked about how my project first should start out small, with one piece of data connecting to an output. We also agreed that visuals could also be a good addition to this project.
This week, I will be working through preliminary research into related subjects and request interviews with people who have experience with certain facets that I will be tapping into during my project.
Data Sonification will be extremely important for this project. Turning data into sound in a way that young students can understand will be necessary for this projects success. There are many aspects of data sonification that I did not think about before I did some research over this week.
Data Sonification refers to displaying data through sound. A lot of the ideas that I learned about this subject came from a LinkedIn Learning podcast interview between Bill Shander, Miriam Quick, and Duncan Geere. This field of data display has been historically underutilized.
It is most notably used in the field of astronomy. Outside of astronomy, it is am underutilized field. Data Sonification has some drawbacks, especially in comparison to Data Visualization. Sonification is challenging to represent to the public. Everyone knows about bars, lines, and dots, but a lot of people do not have the knowledge of tempo, pitch, and dynamics. At this moment in time, Data Sonification is mostly used as an art form. It may not be as versatile as the visual representation.
This does not mean that auditory representation of data does not have its positives. It can be harder hitting than visual data. It also can be used as a tool for equity, because it allows visually impaired people to interpret data that they normally may not be able to.
I watched a short LinkedIn Learning course on the most important skills for a robotics engineer to have. The course is from Free the Data Academy and Ben Sullins. Three aspects of robots that stood out to me is the sensor and actuator combination, the programming, and the human-computer interaction. Actuators are how a robot moves, it turns electrical signals into movement. Sensors are how a robot takes in information. Programming takes in the data from the sensors, and then tell the robot to move in a specific way dependent on the data. It will use algorithms to move more effectively, efficiently, or interact with complex environments safely. Human-computer interaction may be the most important idea for robotics in the upcoming years. Robotics have gotten to a point where they can do tasks better than humans in many scenarios, but they still are not well trained in interacting with humans.
I requested informational interviews from two people this week. The people I contacted are Sean Rowe and Robert Grover. Sean Rowe runs the Hatfield Marine Science Visitor Center through Oregon State University. Robert Grover is the CEO of aRobotics, the company responsible for DataBots. They both responded to me, and I am in the process of setting up informational interviews with them. I will write longer posts after I speak with them.
I am also in the process of setting up a tour at Chet Udell’s OPEnS Lab at Oregon State University. OPEnS stands for Openly Published Environmental Sensing. They make environmental sensors, build open sourced code for environmental sensing, and deploy the sensors into the real world. The lab’s work with environmental and biological sensing could provide helpful insight for my work in collecting sensor data from plants.
Hello to everyone who stumbles across this blog. My name is Josiah Liebert. I am a second-year Computer Science student at Oregon State University, participating in the URSA Engage program. I am from Portland, Oregon. I am interested in sustainability, learning, leadership, science, and sports. URSA stands for Undergraduate Research, Scholarships & the Arts. The goal of the URSA Engage program is to match first-year, second-year, and first-year transfer students with an OSU faculty for research in their field of interest. The program runs for 15 weeks and culminates in a Spring Showcase, where students show off the research that they have been working on. The time commitment is five hours weekly.
My mentor is Victor Villegas. Through his job at OSU Extension Services, and through investing his own free time, he creates different curricula that encourage youth in underserved and underrepresented communities to pursue STEM and STEAM careers. I applied to the URSA Engage program because I felt that my values and skillset aligned well with the work that Victor is actively pursuing. I come from a background in youth advocacy through different experiences at organizations such as Chess for Success, Bike First, and TOPSoccer. These experiences made me realize that I enjoy the creative freedom that teachers can have in making lessons in addition to the joy that children bring to learning. Finding ways to make topics interesting and fun while also explaining ideas in a way that young students can understand is something that has been appealing to me for years. I saw that Victor had experience in the field of youth advocacy, and was looking to take on an undergrad for STEAM-based lesson building. At that point, I became interested in applying.
Throughout this experience, I want to create something that will impact Oregon communities beneficially. It would be awesome to see a lesson that I create, actually be implemented successfully in some school or camp. STEAM has so many cool aspects that are not explored engagingly. They relate these subjects to negative connotations. Math is challenging or science is boring. Instead of going from a foundation of learning the ideas, and then doing some hands-on activity if we have the time, I want to create lessons that will integrate hands-on activities into learning foundational ideas. I would also love to learn from people already in these fields to learn whatever I can about teaching underserved communities STEAM, or any other topic that applies to my project.
Generally, in this experience, I will be creating STEAM-based lessons for elementary and middle school students in underserved populations. The idea of these lessons is that they are self-contained so that any teacher with the correct tools could teach the lesson to their class and that the lessons are fun, through hands-on learning. The first lesson that I will be working on will be utilizing a DataBot sensor. Be sure to keep an eye out for updates involving the specifics of the DataBot project, as well as any future projects!
If you have any questions or want to contact me, my school email is liebertj@oregonstate.edu, and this is my LinkedIn. I look forward to sharing my progress with you!
My progress for this week was a bit all over the place. One thing that I spent a sizeable amount of time on is updating my LinkedIn profile. LinkedIn is a great resource for contacting people doing similar work that I am doing. My experience was very undescriptive and my about section was outdated. I spent some time explaining what I did in each of my work experiences and updating my about section to hopefully connect with more people who are interested in STEAM education. I also added a link to this blog.
Another thing that I did this week is research DataBot and Drone Blocks, to see what other educators have previously done with these pieces of equipment. There were many interesting projects, and they can range greatly in terms of how challenging they are to learn. Some interesting projects that I found were tracking a garden’s health, measuring height using a drone, measuring air quality, etc. The DataBot has a lot of different sensors which can all be used to track different important qualities of the Earth. The following picture found on their website will show all of the different sensors.
Overall, this looks to be a powerful science tool, that has a lot of different features for the price. I have not been able to actually use one yet, so I do not know what its strengths and limitations are in practice. There are a couple of thing that will need to be discussed between me and Victor surrounding audience and purpose. The specific questions are the following:
Who specifically is our audience? What grade, or age, are they? How much STEM experience do they have? Is there a specific demographic of student that I should be tailoring the lesson for?
What is the purpose of the lesson? Are there specific learning outcomes that the students should take away? Will this lesson have more of the goal to just give students a positive experience with STEM, or will there be a bigger outcome?
Two questions that I may focus on after our meeting is, What will the specific lesson look like? How will students’ demographics be reflected in this lesson?