Work-in-Progress: Automation in Undergraduate Classes:  Using Technology to Improve Grading Efficiency, Reliability, and  Transparency in Large Classes

Lee Kemp Rynearson; David W Reazin

Download Paper | Permalink

Conference: 2015 ASEE Annual Conference & Exposition
Location: Seattle, Washington
Publication Date: June 14, 2015
Start Date: June 14, 2015
End Date: June 17, 2015
ISBN: 978-0-692-50180-1
ISSN: 2153-5965
Conference Session: Computers in Education Engineering Division Poster Session
Tagged Division: Computers in Education
Page Count: 13
Page Numbers: 26.1761.1 - 26.1761.13
DOI: 10.18260/p.25097
Permanent URL: https://peer.asee.org/25097
Download Count: 452

Request a correction

Paper Authors

biography

Lee Kemp Rynearson Purdue University, West Lafayette

visit author page

Lee Rynearson is currently pursuing a Ph.D. in the School of Engineering Education at Purdue University. He received a B.S. and M.Eng. in Mechanical Engineering from the Rochester Institute of Technology and has previous experience as an instructor of engineering at the Kanazawa Institute of Technology, in Kanazawa, Japan. His current research interests focus on learning task design and first-year engineering topics.

visit author page

biography

David W Reazin Purdue University

visit author page

Dave Reazin is currently a third-year student at Purdue University working towards a B.S. in Electrical Engineering with a focus on Automatic Controls and Integrated Software Methods. Scheduled to graduate in 2016, Reazin plans to enter industry before returning to school to complete his Master's. Throughout his time at Purdue, Dave has also worked as a Resident Assistant and Staff Resident for University Residences, a Teaching Assistant and Grading Systems Team Lead for the Purdue University First Year Honors Engineering Program, and an Electrical Engineering Intern for United Launch Alliance in Cape Canaveral, Fla.

visit author page

Download Paper | Permalink

Abstract

Automation in Undergraduate Classes: Using Technology to Improve Grading Efficiency, Reliability, and Transparency in Large ClassesLarge undergraduate classes offer many challenges relating to scale. This paper describes a suiteof automated computer tools developed to assist with these challenges, specifically those relatingto grading and performance analysis for either individual students or classes as a whole. Whilethe computer tools developed are independent of any Learning Management System (LMS), theycould easily be adapted to operate more closely with an LMS in other academic environments.The suite of tools in question allow for automated digital rubric generation, collection fromstudents, return to students, and most notably, analysis. Features include the ability to condenseseveral files submitted by one student into a single PDF for review, the ability to executesubmitted code in three programming languages (Python 3, MATLAB, and ANSI C) whilecapturing the output into a PDF, and the ability to track error conditions such as late submissionand incorrect file names and automatically assign penalties.Statistical reports are generated for each assignment automatically, providing a window intostudents’ performance and possible areas of concern. Automated warnings alert the teachingteam to potential errors in grading, equity issues (such as one section of the class performingsubstantially better or worse than another) or opportunities for improvement in the academicprocess (such as rethinking the pedagogy relating to specific ideas or areas that prove broadlytroublesome). These reports streamline instructor workflow and allow for much deeper insightsinto student performance than time would normally allow.The suite of tools was implemented using Visual Basic for Applications (VBA), Python 3, andMySQL databases. The implementation of these automated tools was inexpensive and providedmany benefits to the instructors and graders in terms of convenience, time saved, graderaccountability, process reliability, and enabling new diagnostic capabilities. Furthermore, costsavings were realized from reduced grader time and from almost eliminating the use of paper tooffset the cost of developing the tools. This paper presents details on each of the tools developedas a part of this effort, results of the adoption of the tools in a large first-year class, the potentialuses of similar tools in other venues, and avenues for future work and development.

Citation
Format

Rynearson, L. K., & Reazin, D. W. (2015, June), Work-in-Progress: Automation in Undergraduate Classes: Using Technology to Improve Grading Efficiency, Reliability, and Transparency in Large Classes Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.25097

TY  - CPAPER
AB  -                     Automation in Undergraduate Classes:        Using Technology to Improve Grading Efficiency, Reliability, and                        Transparency in Large ClassesLarge undergraduate classes offer many challenges relating to scale. This paper describes a suiteof automated computer tools developed to assist with these challenges, specifically those relatingto grading and performance analysis for either individual students or classes as a whole. Whilethe computer tools developed are independent of any Learning Management System (LMS), theycould easily be adapted to operate more closely with an LMS in other academic environments.The suite of tools in question allow for automated digital rubric generation, collection fromstudents, return to students, and most notably, analysis. Features include the ability to condenseseveral files submitted by one student into a single PDF for review, the ability to executesubmitted code in three programming languages (Python 3, MATLAB, and ANSI C) whilecapturing the output into a PDF, and the ability to track error conditions such as late submissionand incorrect file names and automatically assign penalties.Statistical reports are generated for each assignment automatically, providing a window intostudents’ performance and possible areas of concern. Automated warnings alert the teachingteam to potential errors in grading, equity issues (such as one section of the class performingsubstantially better or worse than another) or opportunities for improvement in the academicprocess (such as rethinking the pedagogy relating to specific ideas or areas that prove broadlytroublesome). These reports streamline instructor workflow and allow for much deeper insightsinto student performance than time would normally allow.The suite of tools was implemented using Visual Basic for Applications (VBA), Python 3, andMySQL databases. The implementation of these automated tools was inexpensive and providedmany benefits to the instructors and graders in terms of convenience, time saved, graderaccountability, process reliability, and enabling new diagnostic capabilities. Furthermore, costsavings were realized from reduced grader time and from almost eliminating the use of paper tooffset the cost of developing the tools. This paper presents details on each of the tools developedas a part of this effort, results of the adoption of the tools in a large first-year class, the potentialuses of similar tools in other venues, and avenues for future work and development.
AU  - Lee Kemp Rynearson
AU  - David W Reazin
CY  - Seattle, Washington
DA  - 2015/06/14
PB  - ASEE Conferences
TI  - Work-in-Progress: Automation in Undergraduate Classes:  Using Technology to Improve Grading Efficiency, Reliability, and  Transparency in Large Classes
UR  - https://peer.asee.org/25097
DO  - 10.18260/p.25097
ER  -