pygtracker is a Python package that allows UBC MDS lecturers to record, analyze and adjust grades for students in a particular program. Users can record grades from each course, generate a summary report to determine which class is more challenging than the rest, or identify students who may need help. Finally, the package can suggest ways to adjust the grades for students to ensure the average grades match predefined benchmarks.
There are existing packages to manage students' grades in the Python ecosystem. For example, grades-report is a package purely generating statistics from all grades. In addition, edx-bulk-grades aids lecturers in grading and modifying students' grades in bulk. However, these packages are lacking useful features that are unique to the MDS program, such as identifying students / courses that are much different from their peers or adjusting grades to make sure they conform to MDS standard. As a result, we come up with this useful tool which helps UBC MDS lecturers have a better control of student performance.
This package contains seven functions: register_courses, record_grades, calculate_final_grade, generate_course_statistics, rank_courses, rank_students and suggest_grade_adjustment.
The main components of this package are:
- Register courses
- Read/store the courses information as a dataframe
- Record grades for students
- Read/store the students' grades for each assessment as a dataframe
- Calculate the final grade
- Provide the final grade for each student in each course using the courses information and students' grade
- Generate course statistics
- Provide grade statistics on the courses, including mean, 1st quantile, median and 3rd quantile
- Rank courses
- Provide the rankings of courses based on courses' average grades
- Rank students
- Provide the rankings of students based on their average grades for the selected course (or the whole program).
- Suggest grade adjustment
- Suggest grade adjustments for any course based on predefined benchmarks
$ pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple pygtracker
- You can find all dependencies in pyproject.toml file
A toy dataset is used to showcase the usage of the functions. Any csv file containing the grades and courses for the UBC MDS program may be used.
- you will need to import the
pygtrackerpackage, create an instance of the class, and storecourses,gradesas data frames by functionregister_courses()andrecord_grades().
# import packages
from pygtracker import pygtracker
import os
# call an instance of the class
tracker = pygtracker.GradeTracker()
# read in the toy dataset
courses = pd.read_csv(os.path.join(".", "tests", "test_data", "course_info.csv"))
grades = pd.read_csv(os.path.join(".", "tests", "test_data", "student_info.csv"))
# read and stores data as a dataframe
tracker.register_courses(courses)
tracker.record_grades(grades)- By specifying a list of courses, function
generate_course_statistics()would allow you to create a data frame with summary statistics, includingmean,1st-quantile,medianand3rd-quantileof grades so far.
# generates a dataframe with summary statistics for a specified course
tracker.generate_course_statistics(["511"])| course_id | mean | 1st-quantile | median | 3rd-quantile | |
|---|---|---|---|---|---|
| 0 | 511 | 87.87 | 86.91 | 88 | 88.96 |
- Function
rank_courses()generates a data frame of course ranking based on specifiedmethod(default ismean) in descending order by default. This would allow the user to find which course students perform better and which they may struggle with so far.
# generates a dataframe for course ranking by grade
tracker.rank_courses()| course_id | grade | |
|---|---|---|
| 0 | 522 | 91.29 |
| 1 | 511 | 87.87 |
- To look into more details on performance of individual students, function
rank_students()would generate a data frame with student ranking by grades based on specified courses (default is all courses completed so far) in descending order. Thus, the students who may need more help or guidance could be found.
# generates a dataframe with student ranking by grade
tracker.rank_students()| student_id | grade | rank | |
|---|---|---|---|
| 0 | joel | 91.81 | 1.0 |
| 1 | tom | 90.09 | 2.0 |
| 2 | mike | 88.29 | 3.0 |
- Lastly, based on function
suggest_grade_adjustment(), the user is able to find adjusting suggestions by settingbenchmarkof the whole course, labs, or quizzes of that course, such that the final grades meet or exceed these benchmarks.
# calculates the adjustment for a course for a specified benchmark
tracker.suggest_grade_adjustment("511", benchmark_course=100)| course_id | student_id | feedback | lab1 | lab2 | lab3 | lab4 | milestone1 | milestone2 | milestone3 | milestone4 | quiz1 | quiz2 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 511 | joel | 0 | 100 | 100 | 100 | 100 | 0 | 0 | 0 | 0 | 100 | 100 |
| 1 | 511 | mike | 0 | 100 | 100 | 100 | 100 | 0 | 0 | 0 | 0 | 100 | 100 |
| 2 | 511 | tiff | 0 | 100 | 100 | 100 | 100 | 0 | 0 | 0 | 0 | 100 | 100 |
| 3 | 511 | tom | 0 | 100 | 100 | 100 | 100 | 0 | 0 | 0 | 0 | 100 | 100 |
The official documentation is hosted on Read the Docs: https://pygtracker.readthedocs.io/en/latest/
We welcome and recognize all contributions. You can see a list of current contributors in the contributors tab.
- Javairia Raza
- Jianru Deng
- Tran Doan Khanh Vu
- Yanhua Chen
This package was created with Cookiecutter and the UBC-MDS/cookiecutter-ubc-mds project template, modified from the pyOpenSci/cookiecutter-pyopensci project template and the audreyr/cookiecutter-pypackage.