Mastery Calculation Guide

Each new evaluation receives a greater weight, with previous averages counting for less. Essentially, newer assignments count for more, while older assignments progressively count for less.

What’s the advantage?

• Provides a strong indication of student growth.

• Student progress isn’t impacted as much by earlier failed attempts.

Things to consider:

• Using this method makes it harder to get the highest score on a standard if the student has previously received a lower score on an assignment. The reduced impact of older work in favor of newer ones does help a bit in rounding up.

• It’s not as easy to explain or understand as some of the other calculation methods available.

Formula:

If only two assignments have been evaluated:

• [assignment 1 score * (1 - decay rate in decimal form)] + (assignment 2 score * decay rate in decimal form) = total score

If more than two assignments have been evaluated:

• [previously calculated average * (1 - decay rate in decimal form)] + (newest assignment score * decay rate in decimal form) = total score

Calculation example

A school's set decay rate is 65%. A student has two evaluated assignments. Assignment one has a score of 4 and assignment two has a score of 3.

To calculate the student's average, we'd first need to multiply the assignment one score by .35.

• 4 * .35 = 1.4

We would then multiply the assignment two score by .65.

• 3 * .65 = 1.95

Finally, we would add the two numbers together and we get the student's average.

• 1.4 + 1.95 = 3.35

A new assignment has been evaluated for the student. This assignment has a score of 4.

To calculate the student's new average, we'd multiply the previously calculated average by .35.

• 3.35 * .35 = 1.1725

We would then multiply the new assignment score by .65.

• 4 * .65 = 2.6

Finally, we would add these two new numbers together to get the new average for the student.

• 1.1725 + 2.6 = 3.7725

When using Most Recent Evidence, a mastery level is assigned that’s equal to the latest evaluation of a skill. It ignores any evaluations before the latest.

Keep in mind that this calculation method is based on the due date, which can be viewed from the Most recent evidence column under Learning progression. If there are multiple assignments with the same due date and skill associated, the one with the highest rating is used.

What’s the advantage?

• Easier to control than some of the other calculations. For example, for students that may need more opportunities to show mastery, teachers can simply add in another score to immediately update the mastery level.

• Simple to understand mathematically as well as conceptually as to how it works.

• As more evidence is added, this calculation method is better for seeing student scores grow substantially and show more movement than other methods.

Things to consider:

• It can be easier to game the system if students figure out that this calculation method is being used. The fear is that students could intentionally not try as hard in the beginning knowing that only the most recent assignments count.

• If a student has what would be considered a bad day, previous evidence won’t be able to counteract it. However, you could always allow them to retake the test or do something else to provide alternative methods to show mastery.

With Weighted Average as your calculation method, all evaluations of a skill are averaged while also taking into account any weight added to the skill when an assignment is created.

What’s the advantage?

• Well, this calculation is easy to understand as it most resembles more traditional grading systems. Basically, averaging scores together with certain types of work (exams, quizzes, etc) counting more than others.

• Teachers have more control over the calculation through adding more weight to more important work items rather than letting the algorithm handle things behind the scenes.

Things to consider:

• The real drawback to this calculation method is that it’s not great for showing the learning path/pattern that the student has gone through. It’s also harder to determine mastery, encouraging teachers to score students more on if they did what they were supposed to rather than measuring them against the criteria.

Formula:

• sum of ( scores * weight )/ sum of weights = total score

Calculation example

A student has submitted four assignments with the following scores and weights:

• Assignment one: Score = 3; Weight = 1

• Assignment two: Score = 2; Weight = 1

• Assignment three: Score = 3; Weight = 2

• Assignment four: Score = 4; Weight = 3

In order to calculate the average, we must first multiple each assignment's score by its weight and add them together.

• Assignment one: 3 * 1 = 3

• Assignment two: 2 * 1 = 2

• Assignment three: 3 * 2 = 6

• Assignment four: 4 * 3 = 12

• 3 + 2 + 6 + 12 = 23

We then must add up all the weights for the assignment.

• 1 + 1 + 2 + 3 = 7

Finally, we'll divide the total sum of the scores * weight by the sum of the weights.

• 23 / 7 = 3.2857

When this calculation method is selected, the main requirement is that the student shows a mastery of the skill a certain amount of times before the rating is earned.

You can also enable N times before mastery to work in conjunction with other calculation methods as well. For example, you could use decaying average to determine the current score, but in addition require that two of the individual scores were mastery rank or higher.

What's the advantage?

This method is arguably the easiest to use, setup, and understand.

Things to consider:

Compared to the other methods, it's more simplistic. Essentially, by using ‘N’ times only, students could show mastery in their first 2 attempts (as long as 2 is set as being proficient). Even if the student then rates low on all other evaluations, they met the criteria and are still considered proficient. If students figure this out, they could conceivably stop trying as hard once they hit mastery level.