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An eLearning Weather Forecasting Contest

The EART 30551 Meteorology course at the University of Manchester incorporates an innovative eLearning forecasting contest to enhance student engagement. Third-year Environmental Science students, with no prior meteorology experience, are tasked with predicting daily weather conditions at Woodford, including high temperatures and precipitation probabilities. The contest, which accounts for 10% of the final grade, fosters critical thinking and practical applications of lecture materials. Students report improved understanding and engagement through this unique hands-on approach, with opportunities for bonus marks for top performers.

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An eLearning Weather Forecasting Contest

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  1. An eLearning Weather Forecasting Contest David M. Schultz Centre for Atmospheric Science, School of Earth, Atmosphere and Environmental Science, University of Manchester Stuart Anderson and Ryo Seo-Zindy eLearning Team, Faculty of Engineering and Physical Sciences, University of Manchester

  2. The class EART 30551: Meteorology 40 Third-Year Environmental Science/Studies students No previous experience with meteorology

  3. The goal is to get the students to… see the practical application of the lecture material look at the weather outside of the lecture material engage their critical thinking skills (i.e., the answer is not in the back of the book)

  4. Each week students must forecast: next day (Sat midnight to Sun midnight) official observing station at Woodford (outside of Manchester) 1. high temperature (T, whole °C) 2. probability of precipitation: 0, 10, 20, …, 100% (P: 0, 1, 2, …, 10)

  5. Scoring system Score = |Tobs – Tforecast| x 8 + (Pobs – Pforecast)^2 Pobs = 0, if no precipitation Pobs = 5, if a trace Pobs = 10, if measurable precipitation (>=0.2 mm) Missed forecasts receive 150 points

  6. Rules of the contest Forecasts are due by 2300 Friday night Participation is mandatory (10% of final mark) Quality of forecasts is not assessed Best scores receive bonus marks at the end of the semester Best student forecaster receives 8 bonus marks, followed by 6, 4, and 2 marks

  7. Little relationship between MetCast score and average score of five quizzes Indicates that the contest assesses different skills than the quizzes Best Worst

  8. Little relationship between MetCast score and average score of five quizzes Indicates that the contest assesses different skills than the quizzes Allows students to excel in different ways Best Worst

  9. What the students thought: Online Survey Did forecasting contest help you understand the course material better? YES: 18 NO: 11 Did your forecasts improve over the ten weeks? YES: 16 NO: 13

  10. What the students thought: Written Survey

  11. What the students thought: Written Survey

  12. What the students thought: Written Survey

  13. Improvements for next year Better integration of forecast contest into weather discussions Postmordem discussion of last week’s weather forecast to help improvement Less harsh penalty for missed forecast

  14. Dissemination of results Presentation submissions to upcoming GEES, Royal Meteorological Society, and National Centre for Atmospheric Science conferences Submission to Journal of Geoscience Education after next years’ results

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