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Assessment Strategy

Table of Contents

Assignment Types

Assessment Overview

You will complete all of your course work through an industry standard system called GitHub. All students will create a free GitHub account at the start of the Fall 2020 semester. You will use this account and the GitHub repositories associated with it to receive starter materials and submit the final version of each technical challenge, laboratory assignment, and practical assignment.

You will receive rapid feedback on your work through a tool called GatorGrader. The course instructor will define GatorGrader checks for each type of course assignment and your job will be to use a programming language like Python to implement a complete solution that passes all of the GatorGrader checks. In addition to running the GatorGrader tool on your laptop, you will see the results from running GatorGrader checks in the GitHub Actions continuous integration environment.

Assessment Strategy Details

Laboratory Assignments

Taking inspiration from the principles of specification-based grading, the grade that a student receives on a laboratory assignment will be based on whether or not it meets the standards for technical work in the fields of software engineering and discrete structures. Instead of receiving a single numerical or letter grade for this assignment, your grade will have the following components:

  • Percentage of Correct GatorGrader Checks Ranging Between 0 and 100: Your submitted Python program must pass all of GatorGrader's checks by, for instance, ensuring that it produces the correct output and has all of the required characteristics. Your technical writing must pass all of GatorGrader's checks about, for instance, the length of its output and its use of the required Markdown language features for technical writing. For this component of a laboratory assignment's grade, your work will receive a percentage, ranging from 0 to 100, that corresponds to the percentage of GatorGrader checks that automatically pass inside of a GitHub Actions build.

  • GitHub Actions Build Status of Either ✔ or ❌: Since additional checks on the Python source code and/or technical writing are encoded in GitHub Action workflows and, moreover, all of the GatorGrader checks are also run in GitHub Actions, your work will receive a checkmark grade if the last before-the-deadline build in GitHub Actions passes and a ✔ appears in the GitHub commit log instead of an ❌. The build status reported by GitHub Actions will only be a ✔ if the source code and technical writing in the GitHub repository pass all of both the GatorGrader checks and the additional checks.

  • Technical Writing Mastery of Either ✔ or ❌: Students will also receive a ✔ grade when the responses to the technical writing questions presented in the writing/reflection.md reveal a mastery of technical writing skills. To receive a checkmark grade, the submitted writing should have correct spelling, grammar, punctuation, and formatting in addition to following the rules of the Markdown language. Your work will receive a ✔ grade for this component if the build report from GitHub Actions reveals that there are no detected mistakes in the technical writing.

  • Technical Knowledge and Skill Mastery of Either ✔ or ❌: Students will also receive a checkmark grade when the GitHub repository reveals that they have mastered all of the technical knowledge and skills developed during the completion of the laboratory assignment. As a part of this grade, the instructor will assess aspects of the project including, but not limited to, the use of effective Python source code comments, correct Git commit messages, and accurate responses to the technical writing questions.

Practical Assignments and Technical Challenges

Again taking inspiration from the principles of specification-based grading, the grade that a student receives on either a practical assignment or a technical challenge will be based on whether or not it meets the standards for technical work in the fields of software engineering and discrete structures as evidenced by:

  • GitHub Actions Build Status of Either ✔ or ❌: Your work will receive a ✔ if the last before-the-deadline build in GitHub Actions passes and a ✔ appears in the GitHub commit log instead of an ❌. The build status reported by GitHub Actions will only be a ✔ if the Python source code and technical writing in the GitHub repository pass all of both the GatorGrader checks and any additional checks.

Advance Feedback on an Assignment

Students who wish to receive feedback on their work for any course assignment should first open an issue on the issue tracker for their assignment's GitHub repository, giving an appropriate title and description for the type of feedback that you would like the course instructor to provide. After creating this issue, you will see that GitHub has created a unique web site that references it. To alert the course instructor to the fact that the issue was created and that you want feedback on your work, please send it to him by a Slack direct message at least 24 hours in advance of the project's due date. After the instructor responds to the issue, please resolve all of the stated concerns and participate in the discussion until the issue is resolved and ultimately marked as closed.

Assessment Delivery

The course instructor invites students to incrementally complete all of the learning objectives for a technical challenge, laboratory assignment, and practical assignment. As long as your work passes all of the GatorGrader checks before an assignment's deadline, you will receive full credit for that part of your assignment grade. After the deadline for project submission, all grades for the course projects will be reported through a student's GitHub repository using either messages in the GitHub repository's commit log, issues raised in the issue tracker, or comments on a pull request in the GitHub repository. Students should ask questions about their grade for any project on GitHub so as to facilitate an effective conversation about the submitted deliverables and to ensure that a student can ultimately master all of the technical knowledge and skills developed as part of that assignment's exploration of a specific topic in the field of discrete structures.

Discussion of a Graded Assignment

Students who wish to receive feedback on their work for any graded course assignment should leave question in the same region of Github where the course instructor submitted the assignment's grade. For example, if the instructor submits your grade to a pull request in your repository for a laboratory assignment, then you should ask questions about your grade in that pull request, bearing in mind the need to @-mention the course instructor in the body of your comment. Students can continue to discuss the graded assignment with the course instructor until they understand all the technical topics that were the focus of the particular assignment.

Calculating Your Grade

The instructor will convert the specification-based grades that you received to a numerical grade for each type of assignment. The following example succinctly illustrates the calculation of your grade under the simplifying assumption that there are three of each type of assignment with the following grades:

Laboratory Assignments

  • Assignment One: 100%, ✔, ✔, ❌
  • Assignment Two: 81%, ❌, ✔, ❌
  • Assignment Three: 95%, ❌, ✔, ✔

Laboratory Assignment Grade:

  • Assignment One:

    (100 + ((1+1+0)/3)*100)/200
        0.833

  • Assignment Two:

    (81 + ((0+1+0)/3)*100)/200
       0.572

  • Assignment Three:

    (95 + ((0+1+1)/3)*100)/200
       0.808

  • Overall:

    (0.833 + 0.572 + 0.808) / 3 * 100
        73.767

Practical Assignments

  • Assignment One: ✔

  • Assignment Two: ❌

  • Assignment Three: ❌

  • Overall:

    (1+0+0)/3 * 100
      33.33

Technical Challenges

  • Assignment One: ✔

  • Assignment Two: ✔

  • Assignment Three: ✔

  • Overall:

    (1+1+1)/3 * 100
      100.00

Grading Percentages

  • Technical Assessments: 10%
  • Midterm Examination: 10%
  • Final Examination: 10%
  • Technical Challenges: 10%
  • Practical Assignments: 30%
  • Laboratory Assignments: 30%

Please note that these grading percentages supersede those originally specified in the course syllabus.

Questions About Your Grade

Before asking the course instructor a question about the calculation of your either assignment grades or your overall grade, please make sure that you have already consulted the GitHub repository for each assignment to see your grades and then calculated your grade using this approach outlined in this document. The course instructor will use your calculations to support the discussion of any questions that you have about how to calculate either your grade for the technical challenges, laboratory assignments, and practical assignments or your overall grade for the course.