Wright State University
Professors at WSU use Codio's virtual machine architecture and auto-grading to deliver engaging introductory programming courses to CS and non-CS majors.
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Requirements
With over 37,000 students and 70 computer science programs, we spend a six-figure sum each year on grading assignments. We needed a more efficient grading system, both cost and time wise. Additionally, students were not getting meaningful feedback until their assignments were turned in, so we needed a program to enhance student and faculty interaction, prioritizing instruction. Finally, we use the Desire2Learn LMS platform for managing students and classes and wanted something that would integrate smoothly and configures easily.
- Cloud IDE: The ability to configure environments of any complexity that can be accessed as easily at home on students’ own PCs as on a lab PC.
- Grading Flexibility: Auto-graded questions and auto-graded code assessments & manual grading of project assignments
- Instructor Access to Student Work: Ability to instantly access student code whenever required
- Customizable VM: Each assignment is a full-powered VM that can be configured with any programming language, database, component, etc., even providing sudo level privileges
- Level Ground for Students: Knowing that all students would start each assignment with the exact same configuration, no matter how complex
- Prioritize Teaching, Not Tech Support: Being web-based, we didn’t have to act as support staff for students’ own laptops and this allows us to spend more time teaching
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Why I Chose Codio
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Teaching with Codio
Courses Taught with Codio:
- Introductory Programming for CS Majors
- Introductory Programming for Non-CS Majors
- Operating System Concepts
Having become more experienced using Codio, we have developed methodologies that changed the way we teach. In many classes, the lecturer now uses the classroom projector to show different student projects as well as the lecturer’s own solution. This has led to new and highly collaborative approaches in classes with varied solutions. With Codio's VM, lecturers and TAs can design projects that allow them to monitor the progress in greater detail, track the command history and coding history to gain a far deeper understanding of the challenges faced by individuals and the class as a whole.
The strategic use of simple MCQ assessments, and their results clearly displayed in the Teacher Dashboard allows faculty to clearly see whether students are taking due care when reading the teaching materials properly and how fast they are moving through them. This has led to unprecedented insights into class behavior.
In the past, students did not get meaningful feedback until their assignments were turned in. Now, faculty can instantly review, compile and run student code when students ask for assistance or they want to review progress manually. Additionally, the customization possible for class examples, no matter how complex the stack configuration makes for a more engaging experience.
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Blending Manual and Auto-Grading with Codio
By converting many manually graded assignments into auto-graded coding assessments using Codio's auto-grading functionality, we fully expect to be able save tens of thousands of dollars. At least 80% of our auto-grade assessments take advantage of Codio’s “Standard Autograding” feature, a feature that was originally suggested by WSU, which enables code tests grading without needing to write a single line of testing code.
Within the Guides tutorial content we embed a series of simple questions that allows faculty to monitor student progress and how thoroughly students are reading the subject matter, based on multiple choice and fill in the blank questions. This ability to monitor student engagement is especially useful in the context of the flipped classroom where students are expected to prepare for a class.
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Going Forward
Codio is used in a variety of praktikums and labs. Thus far, it is used primarily at the undergraduate level, but there are plans to expand across the department.
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Chair of the Department of Computer Science and Engineering, Wright State University

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