2024 ASEE Annual Conference & Exposition

[Project Name] is an NSF-funded after-school STEM program through which an interdisciplinary team of faculty, staff, and students at [University Name] is collaborating with teachers from four high schools in a large school district in the U.S. and four non-profit Community-Based Organizations (CBOs) in the surrounding communities to develop innovative hands-on activities for underrepresented students. These informal educational activities are centered on robotics, automation, and renewable energy topics. In the program's inaugural year, one of the four units will focus on assessing air quality, employing the micro:bit microcontroller for programming and the Kitronik Air Quality Board for sensing and data collection. All the air quality unit activities were developed by undergraduate students under the guidance of faculty advisors. High school teachers mentoring the student learners in the after-school STEM program iteratively reviewed all activities when these activities were developed. These air quality assessment activities are outlined as follows. Activity 1: Students are introduced to the significance of indoor and outdoor air quality. They subsequently learn about air quality components, including temperature, pressure, humidity, air quality index, and CO2 equivalent. Activities 2 & 3: Students collect air quality data from different locations and visualize the collected data to comprehend variations among these locations. An extension activity is available for students interested in collecting air quality data over an extended period, allowing them to evaluate the correlation between indoor conditions and air quality changes. Activity 4: Students learn to program the micro:bit to display air quality status using LED lights on the air quality board. Activity 5: The learning unit concludes by presenting air quality conditions in their neighborhood in collaboration with their CBOs. Students can assess the air quality using the hand-held device they programmed and compare their findings to data collected by existing air quality monitoring sensors in their communities. Preliminary data collected during the testing phase indicate that the developed programs effectively display air quality. These activities were designed to help student learners comprehend coding, microcontroller technology, and data collection and visualization. In the summer of 2023, the [Project Name] team organized two one-day professional development workshops. Teachers who participated in these summer workshops completed a selection of air quality assessment activities. They provided feedback, confirming that the programs on the air quality board work seamlessly. Minor suggestions were received, and the instructions were modified accordingly. This Work in Progress paper aims to document one of the first year’s learning activities of the highly collaborative after-school STEM program, demonstrate the activity development processes, and foster an exchange of ideas and feedback among educators in related fields.