Impact of Active Learning Implementation on Student Performance in Introductory Atmospheric Science Laboratory Classrooms

Tuesday 1:30pm-4:00pm
Poster Session Part of Tuesday Poster Session

Authors

Kassidy Kjos, University of North Dakota-Main Campus
Montana Etten-Bohm, University of North Dakota-Main Campus
Dr. Jacob Carstens, University of North Dakota-Main Campus
Dr. Elizabeth Suazo-Flores, University of North Dakota-Main Campus
While numerous studies across science, engineering, technology, and mathematics (STEM) disciplines examined and demonstrate active learning education is beneficial to student performance, fewer than 50 of these studies explored atmospheric sciences specifically. This study aims to build upon these limited publications by investigating student performance when exposed to a diverse set of interactive education practices. In this study, three active learning strategies are randomly chosen to be implemented in an introductory meteorology laboratory. The randomly chosen methods include think-pair-share, game-based education, role-playing, diagramming, and gallery walks, which have demonstrated effectiveness in other STEM disciplines. Student performance is analyzed using overall course grades. Pre- and post-test are also examined for direct assessment of learned material. Student performance after exposure to active learning strategies is compared to all other students taught using traditional laboratory practices. Preliminary results indicate that students exposed to active learning performed better than students not exposed on most assessments. More specifically, mean grades were higher on all but one assessment in sections implementing active learning. Early analysis of pre- and post-test data also indicates greater learning gains, suggesting students understand the material more after more interactive teaching styles compared to students in the traditional laboratory courses. Further investigation of grades with the addition of statistical analysis is anticipated to quantify student performance increases for fall and spring semester data.