Model for Student Evaluation

School Grade Book

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School Grade Book

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Description of the School Grade Book Template

The model uses information about assignments, pupils, and pupils' grades on the assignments to compute the grade point

average for each pupil and some measures of the assignments themselves. Not all features are available in the Standard

Version.

The model computes a final grade and a measure of the consistency of each pupil's performance.

– For each pupil, the final grade is the ratio of "quality points" earned / the total quality points for all

assignments. That is, the final grade is a weighted average of grades, weighted by the type of assignment.

o For each pupil, the total number of "quality points" earned and the number of quality points

earned on each assignment. Quality points = grade x assignment weight x attendance.

o For each pupil, the total number of "quality weight" points for all assigments, and the number

of quality weight points for each assignment. Quality weight points = assignment weight x attendance.

– For each pupil, the weighted standard deviation of the grades. A lower (higher) standard deviation

indicates more steady (more uneven) performance by that pupil.

– For each class section, a summary page of results (optional)

You enter the following information about the assignments (in the shaded cells.)

– A list of the individual assignments that are graded.

– A list of the types of assignments, such as 'homework', 'report', 'quiz', 'half test', 'test'.

– For each assigment, the type of assignment.


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School Grade Book

– For each type of assigment, a numerical weight. For example, a test has a much higher weight

than a typical homework assignment.

The teacher enters the following information about the pupils.

– A list of the names of pupils (or other identifiers of pupils), preferably grouped into class sections.

– A table of numerical grades achieved by each pupil on each assignment.

– To indicate that a pupil did not participate in an assignment, enter any negative number as the grade .

The Advanced version supports fitting grades for each assignment to a curve specified for that assignment.

The Advanced version optionally tracks pupil fees assesses and paid.

Technical notes

The model computes four measures of the pupil reactions to each assignment.

1. The average grade earned by participating pupils for each assigment. This is an indication of the difficulty

of the assignment.

– For each assignment, the total number of "quality points" earned by all pupils, and the number

of quality points earned by each pupil.

– For each assignment, the total number of "quality weight" points for all pupils, and the number

of quality weight points for each pupil.

2. The standard deviation of the distribution of grades for each assignment. Always positive or zero.

Roughly speaking, about 2/3 of the grades are within +/- standard deviation points of the mean grade.

3. The skewness of the distribution of grades for each assignment. (A normal distribution has skewness = 0.)

– If skewness <0, the distribution has some very low grades and the mean grade < 50th percentile grade.

A few pupils may be unable to keep up with the middle of the class.

– If skewness >0, the distribution has some very high grades and the mean grade > 50th percentile grade.

A few very good pupils may be far ahead of the midde of the class.

4. The kurtosis of the distribution of grades for each assignment. (A normal distribution has kurtosis = 0.)

– If kurtosis <0, the distribution has a sharper, narrower peak, and many very high and very low grades.

The class may have a wider a range of performance than is optimal.

– If kurtosis >0, the distribution has a flatter, wider peak, and fewer very high and very low grades.

The class probably is targeting nearly all pupils well, leaving few pupils far behind and few far ahead.

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A lower (higher) standard deviation indicates more steady (more uneven) performance by that pupil.

50 60 70 80 90 100

Section 1, pupil101

Section 1, pupil102

Section 1, pupil103

Section 1, pupil104

Section 1, pupil105

Section 2, pupil201

Section 2, pupil202

Section 2, pupil203

Section 2, pupil204

Section 2, pupil205

Student Grade Averages

0 0 0 0 0 1 1 1 1 1 1

Section 1, pupil101

Section 1, pupil102

Section 1, pupil103

Section 1, pupil104

Section 1, pupil105

Section 2, pupil201

Section 2, pupil202

Section 2, pupil203

Section 2, pupil204

Section 2, pupil205

Grade Spread by Student

0 0 0 0 0 1 1 1 1 1 1

Homework 1

Class report

Quiz 1

Homework 2

Quiz 2

Test

Average Grade by Assigment

0 0 0 0 0 1 1 1 1 1 1

Homework 1

Class report

Quiz 1

Homework 2

Quiz 2

Test

Grade Spread by Assignment

If skewness <0, the distribution has some very low grades and the mean grade < 50th percentile grade.


If skewness >0, the distribution has some very high grades and the mean grade > 50th percentile grade.


Inclusiveness:

If kurtosis <0, the distribution has a sharper, narrower peak, and many very high and very low grades.

If kurtosis >0, the distribution has a flatter, wider peak, and fewer very high and very low grades.


0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Homework 1

Class report

Quiz 1

Homework 2

Quiz 2

Test

Grade Skewness by Assignment

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Homework 1

Class report

Quiz 1

Homework 2

Quiz 2

Test

Inclusiveness by Assignment

A lower (higher) standard deviation indicates more steady (more uneven) performance by that pupil.

If skewness <0, the distribution has some very low grades and the mean grade < 50th percentile grade.


If skewness >0, the distribution has some very high grades and the mean grade > 50th percentile grade.


Inclusiveness:

If kurtosis <0, the distribution has a sharper, narrower peak, and many very high and very low grades.


If kurtosis >0, the distribution has a flatter, wider peak, and fewer very high and very low grades.


School Name Washington College

Teacher Name Dr. Faust

Academic Subject Sociology

Academic Term Spring 2010

Assignment Type

Homework 1 Homework

Class report Homework

Quiz 1 Homework

Homework 2 Homework

Quiz 2 Homework

Test Homework

Assign Type Weights

Homework 1

Quiz 1

Test 1

Mean Grade (Curve) Std Dev of Grades (Curve) Min Grade (Curve) Max Grade (Curve)

Homework 1 0.0 0.0 0.0 100.00

Class report 0.0 0.0 0.0 100.00

Quiz 1 0.0 0.0 0.0 100.00

Homework 2 0.0 0.0 0.0 100.00

Quiz 2 0.0 0.0 0.0 100.00

Test 0.0 0.0 0.0 100.00

Washington College

Dr. Faust

Sociology, Spring 2010

Administration

To increase number of assignments or Types, generate a new template.

Grading 'on a Curve'

These parameters define the grading curve for each assignment.

Shaded cells are input cells. You can enter data in them.

Formulas in shaded cells are starting values. You can overwrite them.

Description of Assignments

For each assignment on the left, enter an Assignment Type from the list below.

You can edit names of assignments and Assignment Types on sheet 'Labels'.

Fees Assessed Fees Paid

Section 1

pupil101 $0.00 $0.00

pupil102 $0.00 $0.00

pupil103 $0.00 $0.00

pupil104 $0.00 $0.00

pupil105 $0.00 $0.00

Subtotal $0.00 $0.00

Section 2

pupil201 $0.00 $0.00

pupil202 $0.00 $0.00

pupil203 $0.00 $0.00

pupil204 $0.00 $0.00

pupil205 $0.00 $0.00

Subtotal $0.00 $0.00

Total $0.00 $0.00

Washington College

Dr. Faust


pupil Fees

Homework 1 Class report Quiz 1 Homework 2 Quiz 2 Test

Assignment Type Homework Homework Homework Homework Homework Homework

Assignment Weights 1.0 1.0 1.0 1.0 1.0 1.0

Grades

Section 1

pupil101 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil102 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil103 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil104 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil105 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Subtotal 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Section 2

pupil201 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil202 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil203 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil204 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil205 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Subtotal 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Participation by Assignment

Section 1

pupil101 1 1 1 1 1 1 1

pupil102 1 1 1 1 1 1 1

pupil103 1 1 1 1 1 1 1

pupil104 1 1 1 1 1 1 1

pupil105 1 1 1 1 1 1 1

Subtotal 1 1 1 1 1 1 1

Section 2

pupil201 1 1 1 1 1 1 1

pupil202 1 1 1 1 1 1 1

pupil203 1 1 1 1 1 1 1

A negative entry means a pupil did not participate in an assignment; no grade is included in averages.

Shaded cells are input cells. You can enter data in them.

Formulas in shaded cells are starting values. You can overwrite them.

You can edit the names of pupils and assignments on worksheet 'Labels'.

Washington College

Dr. Faust


All Grades

To increase the number of pupils, class sections or assignments, you must generate a new Template.

pupil204 1 1 1 1 1 1 1

pupil205 1 1 1 1 1 1 1

Subtotal 1 1 1 1 1 1 1

Total 1 1 1 1 1 1 1

Quality Points

Section 1

pupil101 0 0 0 0 0 0 0

pupil102 0 0 0 0 0 0 0

pupil103 0 0 0 0 0 0 0

pupil104 0 0 0 0 0 0 0

pupil105 0 0 0 0 0 0 0

Subtotal 0 0 0 0 0 0 0

Section 2

pupil201 0 0 0 0 0 0 0

pupil202 0 0 0 0 0 0 0

pupil203 0 0 0 0 0 0 0

pupil204 0 0 0 0 0 0 0

pupil205 0 0 0 0 0 0 0

Subtotal 0 0 0 0 0 0 0

Total 0 0 0 0 0 0 0

Quality Weights

Section 1

pupil101 1 1 1 1 1 1 6

pupil102 1 1 1 1 1 1 6

pupil103 1 1 1 1 1 1 6

pupil104 1 1 1 1 1 1 6

pupil105 1 1 1 1 1 1 6

Subtotal 5 5 5 5 5 5 30

Section 2

pupil201 1 1 1 1 1 1 6

pupil202 1 1 1 1 1 1 6

pupil203 1 1 1 1 1 1 6

pupil204 1 1 1 1 1 1 6

pupil205 1 1 1 1 1 1 6

Subtotal 5 5 5 5 5 5 30

Total 10 10 10 10 10 10 60




Grades (Curve)

Section 1

pupil101 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!





Subtotal #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Section 2







Total #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Participation by Assignment

Section 1

pupil101 1 1 1 1 1 1 1

pupil102 1 1 1 1 1 1 1

pupil103 1 1 1 1 1 1 1

pupil104 1 1 1 1 1 1 1

pupil105 1 1 1 1 1 1 1

Subtotal 1 1 1 1 1 1 1

Section 2

pupil201 1 1 1 1 1 1 1

pupil202 1 1 1 1 1 1 1

pupil203 1 1 1 1 1 1 1

pupil204 1 1 1 1 1 1 1

pupil205 1 1 1 1 1 1 1

To increase the number of pupils, class sections or assignments, you must generate a new Template.


Washington College

Dr. Faust


Grades - Curved

You can edit the names of pupils and assignments on worksheet 'Labels'.

Subtotal 1 1 1 1 1 1 1

Total 1 1 1 1 1 1 1

Quality Points (Curve)

Section 1







Section 2







Total #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Quality Weights

Section 1

pupil101 1 1 1 1 1 1 6

pupil102 1 1 1 1 1 1 6

pupil103 1 1 1 1 1 1 6

pupil104 1 1 1 1 1 1 6

pupil105 1 1 1 1 1 1 6

Subtotal 5 5 5 5 5 5 30

Section 2

pupil201 1 1 1 1 1 1 6

pupil202 1 1 1 1 1 1 6

pupil203 1 1 1 1 1 1 6

pupil204 1 1 1 1 1 1 6

pupil205 1 1 1 1 1 1 6

Subtotal 5 5 5 5 5 5 30

Total 10 10 10 10 10 10 60

Mean Grade Std Deviation Skewness Kurtosis

Homework 1 0.0 0.00 #DIV/0! #DIV/0!

Class report 0.0 0.00 #DIV/0! #DIV/0!

Quiz 1 0.0 0.00 #DIV/0! #DIV/0!


Quiz 2 0.0 0.00 #DIV/0! #DIV/0!

Test 0.0 0.00 #DIV/0! #DIV/0!

Total 0.0 0.00 #DIV/0! #DIV/0!

Interpretation

If skewness <0, the distribution has some very low grades.

Washington College

Dr. Faust


Assignments

Metrics for each assignment

A lower standard deviation indicates more steady performance on that assignment across pupils.

A higher standard deviation indicates more uneven performance on that assignment across pupils.

If kurtosis >0, the grade distribution has fewer very high and very low grades.



If skewness >0, the distribution has some very high grades.


If kurtosis <0, the grade distribution has relatively many very high and very low grades.


Mean Grade (Curve) Std Dev of Grades (Curve) Skewness (Curve) Kurtosis (Curved)


Class report 0.0 0.0 #DIV/0! #DIV/0!

Quiz 1 0.0 0.0 #DIV/0! #DIV/0!


Quiz 2 0.0 0.0 #DIV/0! #DIV/0!

Test 0.0 0.0 #DIV/0! #DIV/0!

Interpretation

If skewness <0, the distribution has some very low grades.

Washington College

Dr. Faust


Assignments - Curved

Metrics for each assignment

A lower standard deviation indicates more steady performance on that assignment across pupils.

A higher standard deviation indicates more uneven performance on that assignment across pupils.

If kurtosis >0, the grade distribution has fewer very high and very low grades.



If skewness >0, the distribution has some very high grades.


If kurtosis <0, the grade distribution has relatively many very high and very low grades.


Mean Grade Std Deviation

Section 1

pupil101 0.0 0.00

pupil102 0.0 0.00

pupil103 0.0 0.00

pupil104 0.0 0.00

pupil105 0.0 0.00

Subtotal 0.0 0.00

Section 2

pupil201 0.0 0.00

pupil202 0.0 0.00

pupil203 0.0 0.00

pupil204 0.0 0.00

pupil205 0.0 0.00

Subtotal 0.0 0.00

Total 0.0 0.00

Washington College

Dr. Faust


Final Grades

Mean Grade Std Deviation

Section 1

pupil101 0.0 0.00

pupil102 0.0 0.00

pupil103 0.0 0.00

pupil104 0.0 0.00

pupil105 0.0 0.00

Subtotal 0.0 0.00

Section 2

pupil201 0.0 0.00

pupil202 0.0 0.00

pupil203 0.0 0.00

pupil204 0.0 0.00

pupil205 0.0 0.00

Subtotal 0.0 0.00

Total 0.0 0.00

Washington College

Dr. Faust


Final Grades - Curved




Homework 1 Class report Quiz 1 Homework 2 Quiz 2 Test Total

Grades

pupil101 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil102 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil103 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil104 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil105 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Subtotal 0.0 0.0 0.0 0.0 0.0 0.0 0.0


Washington College

Dr. Faust


Class Section 1

pupil Participation

pupil Consistency

Quality Points

Quality Weights





Grades

pupil201 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil202 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil203 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil204 0.0 0.0 0.0 0.0 0.0 0.0 0.0

pupil205 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Subtotal 0.0 0.0 0.0 0.0 0.0 0.0 0.0


Washington College

Dr. Faust


Class Section 2

pupil Participation

pupil Consistency

Quality Points

Quality Weights





Grades (Curve)








Washington College

Dr. Faust


Class Section - Curved 1

pupil Participation

pupil Consistency

Quality Points

Quality Weights





Grades (Curve)








Washington College

Dr. Faust


Class Section - Curved 2

pupil Participation

pupil Consistency

Quality Points

Quality Weights

Variable Display As Dimension Index Formula / Data

Academic_Subject Academic Subject

Academic_Term Academic Term

Assign_Type_Weights Assign Type Weights

Assign_Types_Dim Assign_Types Assign_Types Data: diminfo("Assign_Types", 0)

Assignment_Type Assignment Type Assignments Data: index(ranged("Assign_Types", Assign_Types_Dim), 1)

Assignment_Weights Assignment Weights Assignments Data: index(ranged("Assign_Types", Assign_Type_Weights, true), match(Assignment_Type, ranged("Assign_Types", Assign_Types_Dim, true), 0))

Assignments Assignments Assignments Data: diminfo("Assignments", 0)

Assignments_dim Assignments_dim Assignments Data: diminfo("Assignments", 7, ", ")

Fees_Assessed Fees Assessed

Fees_Paid Fees Paid

Grades Grades Assignments, pupils Roll-up: Quality_Points/Quality_Weights

Grades_Curve Grades (Curve) pupils, Assignments Data: if(Grades<0, Grades, max(Min_Grade_Curve, min(Max_Grade_Curve, (Grades-Mean_Grade_by_Assignment)*Std_Dev_Grades_by_Assign_Curve/Std_Dev_Grades_by_Assignment)+Mean_Grade_by_Assign_Curve))

Roll-up: Quality_Points_Curve/Quality_Weights

Grades_Curve_Norm_Wtd Curved Grades Norm Wtd pupils, Assignments Data: max(0, Grades_Curve)*Quality_Norm_Wgts

Grades_Norm_Wtd Grades Norm Wtd pupils, Assignments Data: max(0, Grades)*Quality_Norm_Wgts

Grades2_Wtd Grades2 Wtd pupils, Assignments Data: max(0, Grades)^2*Quality_Weights

Grades2_Wtd_Curve Grades2 Wtd (Curve) pupils, Assignments Data: max(0, Grades_Curve)^2*Quality_Weights

Kurt_Grades_by_Assign_Curve Kurtosis (Curved) Assignments Data: kurt(ranged("pupils", Grades_Curve, true))

Kurt_Grades_by_Assignment Kurtosis Assignments Data: kurt(ranged("pupils", Grades, true))

Max_Grade_Curve Max Grade (Curve)

Mean_Grade Mean Grade Global Data: averager(ranged("pupils", Mean_Grade_by_pupil, true))

Mean_Grade_by_Assign_Curve Mean Grade (Curve) Assignments Data: Mean_Grade_by_Assignment

Mean_Grade_by_Assignment Mean Grade Assignments Data: sumr(ranged("pupils", Quality_Points, true))/sumr(ranged("pupils", Quality_Weights, true))

Mean_Grade_by_Stud_Curve Mean Grade (Curve) pupils Roll-up: sumr(ranged("Assignments", Quality_Points_Curve, true))/sumr(ranged("Assignments", Quality_Weights, true))

Mean_Grade_by_pupil Mean Grade pupils Roll-up: sumr(ranged("Assignments", Quality_Points, true))/sumr(ranged("Assignments", Quality_Weights, true))

Mean_Grade_Curve Mean Grade (Curve) Global Data: averager(ranged("pupils", Mean_Grade_by_Stud_Curve, true))

Min_Grade_Curve Min Grade (Curve)

Participation Participation by Assignment Assignments, pupils Data: if(Grades<0, 0, 1)

Roll-up: 1

Quality_Norm_Wgts Normalized Quality Wgts Assignments, pupils Data: Quality_Weights/sumr(ranged("Assignments", Quality_Weights, true))

Quality_Points Quality Points pupils, Assignments Data: Grades*Quality_Weights

Quality_Points_Curve Quality Points (Curve) pupils, Assignments Data: Grades_Curve*Quality_Weights

Quality_Weights Quality Weights pupils, Assignments Data: Assignment_Weights*Participation

School_Name School Name

Skew_Grades_by_Assign_Curve Skewness (Curve) Assignments Roll-up: skew(ranged("pupils", Grades_Curve, true))

Skew_Grades_by_Assignment Skewness Assignments Roll-up: skew(ranged("pupils", Grades, true))

Std_Dev_Grades_by_Assign_Curve Std Dev of Grades (Curve) Assignments Data: stdev(ranged("pupils", Grades, true))

Washington College

Dr. Faust


Formulas

Std_Dev_Grades_by_Assignment Std Deviation Assignments Roll-up: stdev(ranged("pupils", Grades, true))

Std_Dev_Grades_by_Stud_Curve Std Deviation (Curve) pupils Roll-up: sqrt(Var_Grades_by_Stud_Curve)

Std_Dev_Grades_by_pupil Std Deviation pupils Roll-up: sqrt(Var_Grades_by_pupil)

pupils_dim pupils_dim pupils Data: diminfo("pupils", 7, ", ")

Teacher_Name Teacher Name

Var_Grades_by_Stud_Curve Var Grades by pupil pupils Data: Var_Grades_by_Stud_Curve_Num/Var_Grades_by_pupil_Den

Var_Grades_by_Stud_Curve_Num Var Grades by pupil Num pupils Data: sumr(ranged("Assignments", Grades2_Wtd_Curve, true))-sumr(ranged("Assignments", Quality_Weights, true))*sumr(ranged("Assignments", Grades_Curve_Norm_Wtd, true))^2

Var_Grades_by_pupil Var Grades by pupil pupils Data: Var_Grades_by_pupil_Num/Var_Grades_by_pupil_Den

Var_Grades_by_pupil_Den Var Grades by pupil Den pupils Data: sumr(ranged("Assignments", Quality_Weights, true))-1

Var_Grades_by_pupil_Num Var Grades by pupil Num pupils Data: sumr(ranged("Assignments", Grades2_Wtd, true))-sumr(ranged("Assignments", Quality_Weights, true))*sumr(ranged("Assignments", Grades_Norm_Wtd, true))^2

Variable Display Label Comment

Academic_Subject Academic Subject The academic subject for the pupils and class sections in this gradebook

Academic_Term Academic Term The academic term for this gradebook

Assign_Type_Weights Assign Type Weights Weight for each type of assignment, used in weighted average of grades.

You can enter a descriptive name for each assignment type (such as: homework, quiz, half

test, test) on worksheet 'Labels', in the dimension 'Assign Types'; enter names in the blue

cells in column B.

Assign_Types_Dim Assign_Types Converts the dimension Assign_Types into an analysis variable for use in lookups.



cells in column B.

Assignment_Type Assignment Type The type of each assignment, which determines what weight the assignment has in averages

of pupil grades. Enter one of the names in variable table 'Assign Types'.

You can enter a descriptive name for each assignment on worksheet 'Labels', in the

dimension 'Assignments'; enter names in the blue cells in column B.



cells in column B.

Assignment_Weights Assignment Weights The weight of each assignment in the weighted grade point average for each pupil.

You can enter pupil names on worksheet 'Labels', in the dimension 'pupils'; enter names in

the blue cells in column B.



Assignments Assignments Names of the assignments.



Assignments_dim Assignments_dim Variable containing display names of items in dimension 'Assignments'

Fees_Assessed Fees Assessed

Fees_Paid Fees Paid

Grades Grades Grades for each pupil on each assignment. A negative number indicates that the pupil did not

do the assignment and gets no grade. Participation is indicated in the same table as grades

so the teacher doesn't have to enter this data in two places.



Washington College

Dr. Faust


Labels

Grades_Curve Grades (Curve) Grades for each pupil on each assignment using the grading 'curve'. A negative number

indicates that the pupil did not do the assignment and gets no grade. Participation is indicated

in the same table as grades so the teacher doesn't have to enter this data in two places.



Grades_Curve_Norm_Wtd Curved Grades Norm Wtd Curved grade * quality norm weight, for each pupil and each assignment

Grades_Norm_Wtd Grades Norm Wtd Grade * quality norm weight, for each pupil and each assignment

Grades2_Wtd Grades2 Wtd Grade^2 * assignment weight

Grades2_Wtd_Curve Grades2 Wtd (Curve) (Curved grade)^2 * assignment weight

Kurt_Grades_by_Assign_Curve Kurtosis (Curved) Fn each assignment, the 'kurtosis' of all 'curved' grades.

If kurtosis <0, the grade distribution has a sharper, narrower peak, and many very high and

very low grades. The class may have a wider a range of performance than is optimal.

If kurtosis >0, the distribution has a flatter, wider peak, and fewer very high and very low

grades. The class probably is targeting nearly all pupils well, leaving few pupils far behind and

few far ahead.

Kurt_Grades_by_Assignment Kurtosis Fn each assignment, the 'kurtosis' of all grades.

If kurtosis <0, the grade distribution has a sharper, narrower peak, and many very high and

very low grades. The class may have a wider a range of performance than is optimal.

If kurtosis >0, the distribution has a flatter, wider peak, and fewer very high and very low

grades. The class probably is targeting nearly all pupils well, leaving few pupils far behind and

few far ahead.

Max_Grade_Curve Max Grade (Curve) The maximum grade on each assignment when grading on a 'curve'. Any grade that would be

higher than this maximum on the curve is set to the maximum allowed value.

Mean_Grade Mean Grade Weighted average grade on all assignments by all pupils

Mean_Grade_by_Assign_Curve Mean Grade (Curve) The user-specified mean grade for each assignment when grading on a 'curve'

Mean_Grade_by_Assignment Mean Grade For each assignment, the average grade for all pupils

Mean_Grade_by_Stud_Curve Mean Grade (Curve) For each pupil, the weighted average 'curved' grade on all assignments.

You can enter pupil names on worksheet 'Labels', in the dimension 'pupils'; enter in the blue

cells in column B.

Mean_Grade_by_pupil Mean Grade For each pupil, the weighted average grade on all assignments.

You can enter pupil names on worksheet 'Labels', in the dimension 'pupils'; enter in the blue

cells in column B.

Mean_Grade_Curve Mean Grade (Curve) Weighted average 'curved' grade on all assignments by all pupils

Min_Grade_Curve Min Grade (Curve) The minimum grade on each assignment when grading on a 'curve'. Any grade that would be

lower than this manimum on the curve is set to the minimum allowed value.

Participation Participation by Assignment If a pupil participated in an assignment, 1 else 0

Quality_Norm_Wgts Normalized Quality Wgts Quality weights, but normalized so the sum over all pupils is 1 for each assignment.

Quality_Points Quality Points For each pupil, the weighted sum of grades on all assignments

Quality_Points_Curve Quality Points (Curve) For each pupil, the weighted sum of curved grades on all assignments

Quality_Weights Quality Weights For each assignment and pupil, this is Assignment weight * Participation index (1 or 0)

School_Name School Name The name of the school where this gradebook is used

Skew_Grades_by_Assign_Curve Skewness (Curve) For each assignment, the 'skewness' of the distribution of 'curved' pupil grades.

If skewness <0, the distribution has some very low grades and the mean grade < median

(50th percentile) grade. A few pupils may be unable to keep up with the middle of the class.

If skewness >0, the distribution has some very high grades and the mean grade > 50th

percentile grade. A few pupils may be far ahead of the midde of the class.

Skew_Grades_by_Assignment Skewness For each assignment, the 'skewness' of the distribution of pupil grades.

If skewness <0, the distribution has some very low grades and the mean grade < median

(50th percentile) grade. A few pupils may be unable to keep up with the middle of the class.

If skewness >0, the distribution has some very high grades and the mean grade > 50th

percentile grade. A few pupils may be far ahead of the midde of the class.

Std_Dev_Grades_by_Assign_Curve Std Dev of Grades (Curve) The user-specified standard deviation (spread) of grades for each assignment when grading

on a 'curve'

Std_Dev_Grades_by_Assignment Std Deviation Standard deviation of distribution of pupil grades on each assignment.

A lower (higher) standard deviation indicates more uniform (more uneven) performance by

pupils on that assignment. The minimum value is zero, which occurs only if all grades on the

given assignment are equal.

Std_Dev_Grades_by_Stud_Curve Std Deviation (Curve) Weighted standard deviation of distribution of grades on all assignments for each pupil.

Assignment weights are used in the computation.

A lower (higher) standard deviation indicates more steady (more uneven) performance by

that pupil. The minimum value is zero, which occurs only if all grades of the given pupil are

equal.

Std_Dev_Grades_by_pupil Std Deviation Weighted standard deviation of distribution of grades on all assignments for each pupil.

Assignment weights are used in the computation.

A lower (higher) standard deviation indicates more steady (more uneven) performance by

that pupil. The minimum value is zero, which occurs only if all grades of the given pupil are

equal.

pupils_dim pupils_dim Variable containing display names of items in dimension 'pupils'

Teacher_Name Teacher Name

Var_Grades_by_Stud_Curve Var Grades by pupil For each pupil, the variance of the distribution of 'curved' grades on all assignments

Var_Grades_by_Stud_Curve_Num Var Grades by pupil Num Numerator in computation of weighted variance of 'curved' grades on all assignments for

each pupil

Var_Grades_by_pupil Var Grades by pupil For each pupil, the variance of distribution of grades on all assignments

Var_Grades_by_pupil_Den Var Grades by pupil Den Denominator in computation of weighted variance of grades on all assignments for each pupil

Var_Grades_by_pupil_Num Var Grades by pupil Num Numerator in computation of weighted variance of grades on all assignments for each pupil

Dimension (item) Display Item As Total As Level As Comment

Assign_Types Assign Types Total AssignTypes A list of the types of assignments given to the pupils. The types are needed to assign

numerical weights to each assignment.

Do not use identical names for different leaves of this dimension.

Homework Homework AssignTypes

Quiz Quiz

Test Test

Assignments Assignments Total Assignments A list of the assignments given to the pupils. Do not use identical names for different leaves

of this dimension.

Homework_1 Homework 1 Assignments

Class_report Class report

Quiz_1 Quiz 1

Homework_2 Homework 2

Quiz_2 Quiz 2

Test Test

pupils pupils Total pupils A hierarchical list of the pupils by class section

Section_1 Section 1 Subtotal pupils

pupil101 pupil101 pupils 2

pupil102 pupil102

pupil103 pupil103

pupil104 pupil104

pupil105 pupil105

Section_2 Section 2 Subtotal

pupil201 pupil201

pupil202 pupil202

pupil203 pupil203

pupil204 pupil204

pupil205 pupil205

Model for Student Evaluation

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