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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.

Details

Business indexing term
Title
Work-in-Progress: Automation in Undergraduate Classes: Using Technology to Improve Grading Efficiency, Reliability, and Transparency in Large Classes
Source details
Conference: 2015 ASEE Annual Conference & Exposition; Location: Seattle, Washington; Start Date: June 14, 2015; End Date: June 17, 2015
Pages
26.1761.1-26.1761.13
Publication year
2015
Publication date
Jun 14, 2015
Publisher
American Society for Engineering Education-ASEE
Place of publication
Atlanta
Country of publication
United States
Source type
Conference Paper
Language of publication
English
Document type
Conference Proceedings
Publication history
 
 
Online publication date
2015-07-06
Publication history
 
 
   First posting date
06 Jul 2015
ProQuest document ID
2317758478
Document URL
https://www.proquest.com/conference-papers-proceedings/work-progress-automation-undergraduate-classes/docview/2317758478/se-2?accountid=208611
Copyright
© 2015. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://peer.asee.org/about .
Last updated
2025-11-15
Database
ProQuest One Academic