JumpRope is all about saving time and making things more efficient for busy educators. We've spent the last three years building the most powerful mastery-based gradebook in the world, and have over six million individual data points on student mastery. It is with great pride that I introduce to you a feature that represents the culmination of our hard work: AutoGrader.
I've long understood that grades are essentially subjective pieces of data. While I trust fellow educators to do their best to collect meaningful data on student mastery, I know that other pressures (time, emotions, etc.) can often get in the way of accurate and meaningful scores. But you're in luck! JumpRope has expended significant resources on research and development over the years to develop a technology that statistically controls for subjectivity in grades. With our data set, we can use a combination of previous performance, teacher grading characteristics, demographics, grading philosophies, and predictive algorithms to determine student mastery for you. Yes, you heard us right: we now have enough data to predict student mastery with more accuracy than you can!
AutoGrader represents the pinnacle of educational technology. Imagine a world in which you are no longer responsible for the doldrums of "assessment" and "grading" - instead, you can focus on the more interesting parts of education such as the 3pm dismissals and the long, numerous vacations. We believe that this feature is the silver bullet that can bring educators - and education - to the next level: improve student achievement while making your job significantly easier.
To boot, we are so confident in our recommendations that we even provide a specific rationale for each suggested grade, detailing the thinking behind the suggestion. Better still, you don't need to do anything to activate this feature - it's turned on automatically in your account! Sit back and let computers to the work so that you don't have to - satisfaction guaranteed. Just go to the Grade or Track tab to get started.
Thanks for all of your work and the invaluable data that you have contributed to this effort (with or without your knowledge)! We look forward to hearing you feedback, though we now have an algorithm automatically responding to your support requests... so we'll probably never read it.