Codio and Kent State
Kent State University Teaches Big Data Using the Codio Platform. Codio helps make advanced computer science courses more and engaging accessible for undergraduate students.
Authored by:
Dr. Greg Delozier is an Adjunct Professor of Computer Science at Kent State University.
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What we needed
Computer Science students are interested in Big Data with a view to the jobs market. They want to broaden their range of skills in order to increase employability. They are interested in the process of Big Data analysis itself and how it can be applied to a broad range of problems. However, there are also geologists, epidemiologists, statisticians, and other students who do not specialize in Computer Science but want to learn how to use Big Data tools in order to extract meaning from vast amounts of data.
In both cases, having an understanding of big data technology requires considerably more technical skills than the SQL query of old. With the correct big data solution architecture, a processing task may run an order or magnitude faster or more. This can be the difference between success and failure or making an informed decision or a guess.
It is for this reason that we are seeing Computer Science departments starting to embrace Big Data. Currently, it is often taught at the post-graduate level, but Codio allows lecturers to start incorporating it at the undergraduate level as well.
Why we chose Codio
One approach is for a distributed system to be set up in a computer science laboratory. This presents the lecturer and students with a real problem. Such an environment is a single entity serving many students. The administrator will not want students to play around with the configuration in case they destabilize the entire system for everyone else. This restriction means that students are not getting their hands dirty in order to build the necessary overall experience.
Teaching with Codio
Courses Taught With Codio
- Big Data Management
Dr. DeLozier was quickly impressed with Codio’s Box technology and how it allowed his students to quickly spin up a distributed system or even variations of these systems without having to purchase dedicated cloud servers or administer systems in-house. Codio’s boxes automatically deactivate when not in use. So Codio effectively charges for a single user even if they have 200 different configurations or projects.
He found that using Codio boxes, he could install the base Hadoop software (and other supporting systems, like Java or web servers) and essentially create small, single node Hadoop machines. These machines were capable enough to support HDFS, Hive, Pig, and other major components of the base Hadoop ecosystem. Having students install and configure what amounted to a small microcluster for each student was essential to creating deeper understanding of the basics of Hadoop and its theory of operation. Compared to the usual Hadoop-as-a-black-box method of giving access to a shared cluster, this experience was very well received by students learning the mechanisms of big data.
Many students chose to stay with Codio even when a campus cluster was provided. While processing was not as fast, the convenience and reliability of the Codio box was such that many of the students actually chose that as the tool with which to deliver their class projects. Via Codio’s classroom management dashboard, he can also instantly access a student’s projects and assess configurations, run jobs, diagnose issues and even grade each student’s project. There is no need for him to know urls and passwords for remote systems.
Achieve better learning outcomes
Schedule your personalized demo today to see how you can achieve the same level of success as Kent State.Codio provides all a student and instructor need
Codio Supports Big Data with Changes
Bigger Boxes - Codio’s boxes have a default CPU and RAM allocation that is adequate for almost all coding projects. However, some applications require higher levels of RAM and so Codio offers lecturers with the ability to configure larger allocations.
Time To Live Boxes - standard Codio boxes shut down automatically a few minutes after the student closes the project. It is this capability that ensures Codio can afford to offer users advanced server resources at a very low cost. However, for some projects such as big data and server-side API development, this automatic termination is troublesome. Our TTL boxes allow boxes to remain online for a specific time period before they are killed. If the student wants to restart the box at any point they can, whether in the CS lab or at home and so interruptions are rare and perfectly acceptable in a teaching environment.
Always On Boxes - we already offer this feature but due to fact that these servers are permanently live and consuming resources, Codio needs to charge extra. In a teaching environment, the Time To Live boxes provide the availability that teachers need at a cost that they can afford.
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Experience the Codio difference for yourself with a free proof-of-concept demo using your existing assignments or labs.