Conference 2019 Session: Using Questionmark to Build Microlearning for Photo Estimators
Using Questionmark to Build Microlearning for Photo Estimators
Progressive photo estimators use videos and photographs to identify damage and write estimates for necessary repairs. Writing accurate estimates without physically inspecting vehicles is challenging. Leaders in the group identified ideas for techniques estimators can use to create more accurate estimates. Estimators are extremely busy, and need short, focused activities they can apply on the job. We are building a set of microlearning modules to contribute toward improving the accuracy of photo estimates.
Benefits associated with using Questionmark to build microlearning modules include the ability to:
- Export results to provide the business with detailed data about how each estimator’s performance at the “quiz,” question, and answer choice level
- Align the scored items in the microlearning modules with tasks the photo estimators perform on the job
- Extend the functionality of QMOD question types using the Advanced Question Editor
- Include explanation items to provide information to the estimators about the estimating techniques.
In this session, I’ll share details about the microlearning modules and the process we used to develop them. I’ll also try to share Level 1 feedback, Level 2 results, and any Level 3 findings we’re able to gather through January 2019.
Recognize the potential to use Questionmark to build microlearning
Leverage the Explanation question type to present information needed to set the stage in microlearning
Extend the functionality of text match and other question types by using the Advanced Question Editor
Use Questionmark reporting to provide relevant results to the business