Weather Forecasting as a Learning Tool in a Large Service Course: Does Practice Make Perfect?

Abstract

Each spring roughly 200 students, mostly nonmajors, enroll in the Introduction to Meteorology course at Iowa State University and are required to make at least 25 forecasts throughout the semester. The Dynamic Weather Forecaster (DWF) forecasting platform requires students to forecast more than just simple ''numeric'' forecasts and includes questions on advection, cloudiness, and precipitation factors that are not included in forecast contests often used in meteorology courses. The present study examines the evolution of forecasting skill for students enrolled in the class in spring 2010 and 2011 and compares student performance with that of an ''expert forecaster. '' The expert forecasters were chosen from meteorology students in an advanced forecasting course who showed exemplary forecasting skill throughout the previous semester. It is shown that these introductory students improve in forecast skill over only the first 10-15 days that they forecast, a number smaller than the 25 days found in an earlier study examining meteorology majors in an upper-level course. The skill of both groups plateaus after that time. An analysis of two types of questions in the DWF reveals that students do have skill slightly better than that of a persistence forecast when predicting parameters traditionally used in forecasting contests, but fail to outperform persistence when predicting more complex atmospheric processes like temperature advection and factors influencing precipitation such as moisture content and instability. The introduction of a contest ''with prizes'' halfway through the semester in 2011 was found to have at best mixed impacts on forecast skill. ABSTRACT Each spring roughly 200 students, mostly nonmajors, enroll in the Introduction to Meteorology course at Iowa State University and are required to make at least 25 forecasts throughout the semester. The Dynamic Weather Forecaster (DWF) forecasting platform requires students to forecast more than just simple ''numeric'' forecasts and includes questions on advection, cloudiness, and precipitation factors that are not included in forecast contests often used in meteorology courses. The present study examines the evolution of forecasting skill for students enrolled in the class in spring 2010 and 2011 and compares student performance with that of an ''expert forecaster.'' The expert forecasters were chosen from meteorology students in an advanced forecasting course who showed exemplary forecasting skill throughout the previous semester. It is shown that these introductory students improve in forecast skill over only the first 10-15 days that they forecast, a number smaller than the 25 days found in an earlier study examining meteorology majors in an upper-level course. The skill of both groups plateaus after that time. An analysis of two types of questions in the DWF reveals that students do have skill slightly better than that of a persistence forecast when predicting parameters traditionally used in forecasting contests, but fail to outperform persistence...

Engaging Earth- and Environmental-Science Undergraduates Through Weather Discussions and an eLearning Weather Forecasting Contest

“…3. Instead, our results are more similar to those of Seuss et al (2011) showing relatively little improvement after the first few forecasts.…”

“…Yet, whether these students would benefit from similar forecasting exercises as meteorology majors is less well known. Specifically, Hilliker (2008) showed that students in a general education course and geology majors who participated in a forecast contest could improve as they developed more experience, although Seuss (2011) did not find such improvement among students in a survey course for nonmajors. In addition, students' performance in the contest may (e.g., Hilliker 2008) or may not (e.g., Bond and Mass 2009) be correlated with their academic performance.…”

ManUniCast: a real-time weather and air-quality forecasting portal and app for teaching

“…Besides its popularity with students, active learning through repeated practice is the best way for students to gain experience and improve (Roebber and Bosart, ). Specifically, Hilliker () and Suess et al () showed that students in a general education course and geology majors who participated in a forecast contest could improve as they developed more experience. Thus, repeated exposure to weather forecasting tools appears to benefit student learning.…”

“…application, analysis, synthesis, evaluation). In addition, forecasting contests and discussions of the current weather in the classroom can motivate student learning (Harrington et al , ; Skeeter, ; Barrett and Woods, ), inspire better grades (Hilliker, ) and result in better forecasts (Market, ; Bond and Mass, ; Suess et al , ). Finally, weather discussions help close the gap between the knowledge‐seeking professors and the goal‐seeking students (Roebber, ), because an otherwise sterile set of equations illustrating complicated physical concepts comes alive when being used to illustrate the current weather in the news or outside the window.…”

Perception and confidence on weather forecasts among Spanish undergraduate students enrolled in different subjects related to physics

“…Weather predictions have been used in the classroom as part of the learning process in order to facilitate students to better understand complex theoretical concepts as well as different atmospheric processes addressed in the corresponding lectures (Morss and Zhang, 2008;Bond and Mass, 2009;Schultz et al, 2015;Suess et al, 2013;Gómez Doménech et al, 2016). In addition, the usage of weather forecasts in an educational environment provides students with first-hand experiences to visualize and contextualize different theoretical concepts and handle available information.…”