Curriculum Competency Tree Software; Alternatives to Conventional Grading: How Professors are Changing the Paradigm

Author:
Prohaska, Daniel, School of Engineering and Applied Science, University of Virginia
Advisor:
Floryan, Mark, EN-Comp Science Dept, University of Virginia
Abstract:

Preface
How can educators teach students more effectively?
How can students and educators track understanding of material in a course? Students rely on grades for a variety of reasons, including to qualify for scholarships, to fulfill course prerequisites, and for opportunities in graduate school and in career employment. In conventional teaching methods, teachers assign values to assignments and calculate a weighted average for a final grade. Averaging performance produces an amalgamation that can be hard to understand and unbeneficial. Development of a tool to track student progress through a course and use of standards based grading will improve student performance. The tool provides feedback based on student performance and assists with meeting personal goals.
How have professors advanced alternatives to the conventional grading model? Assessment methods influence the time and effort that students commit to study. Some students conserve effort, seeking to do no more than necessary to graduate. Others are ambitious, seeking high grades and the opportunities they promote. To such students, the grade may be more important than learning. Professors’ views also vary. To some, active participation is essential to education; others equate education with skill development. Educators have developed alternatives to conventional grading by assessing knowledge in other ways, by increasing student participation, and by making grades more meaningful.

Degree:
BS (Bachelor of Science)
Keywords:
standards based grading, grading models, conventional grading, competency grading, knowledge assessment, student driven learning, proficiency tree, computer science grading, grading tool
Notes:

School of Engineering and Applied Science Bachelor of Science in Computer Science
Technical Advisor: Mark Floryan
STS Advisor: Peter Norton
Technical Team Members:

Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2021/05/13