Peerceptiv Grades: A Brief Overview for Instructors

There are three components that make up the Overall Grade awarded on a Peerceptiv assignment. 

1. Submission Grade: This is the grade received on a student submission, generated by the reviews it was given. Accuracy-adjusted ratings from both the instructor and peers, or either one alone, are used to generate this grade. The grade is then placed on a relative curve according to a set mean and standard deviation (chosen by the instructor during assignment set-up), or instructor benchmarking (the instructor grades the top five and bottom five submissions and the rest are sorted in between these two sets). The submission grade is based on the average rating scores received, but is then adjusted according to reviewer accuracy and overall class performance to produce a finely calibrated grade that is both fair and valid.  
2. Reviewing Grade: The Reviewing Grade is made of two components: the Accuracy Grade and the Helpfulness Grade. Accuracy Grades measure how closely a student’s ratings track with peer and instructor ratings on the same document. Helpfulness Grades are calculated based on the feedback ratings the student receives from their peers. After the Accuracy and Helpfulness grades are combined, the Reviewing Grade is placed along the same curve as the Submission Grade, to make it relative to the rest of the class.
3. Task Grade: The Task Grade is a simple measure of whether the student did all the required tasks in the assignment. If they completed all the tasks, they will receive 100% of the task grade. 

Once there is a grade for each of these three components, they are combined to make the Overall Grade according to the weight that an instructor has placed on each component. The default weights are that the Submission Grade counts as 40 percent of the Overall Grade, the Reviewing Grade counts as 40 percent of the Overall Grade, and the Task Grade counts as 20 percent of the Overall Grade.  See below for a student grades breakdown: 

The algorithm that Peerceptiv uses to generate grades is complex, robust, and it has been rigorously tested and validated over the course of a decade of research by learning scientists and professors at the University of Pittsburgh. 

For more detailed information about grading, please read: Peerceptiv Grades: A Detailed Explanation for Instructors.

For information about how to explain grades to students, please read: How to Explain Peerceptiv Results to Students.

For more information about adjusting the grading settings in your assignment, please read: Adjust Grading Settings or How to Create an Assignment.