Taking the Guesswork out of Computer Lab Management

Computer lab management and providing effective and efficient computer services to students requires constant decision making. Lab managers must determine which applications to purchase and include on station images, and where hardware resources should be placed to maximize utilization. The availability of resources must then be effectively communicated to students for resources to be fully utilized. When computer lab management decisions are based on data, lab managers can be confident that false assumptions are not being made.

COMPUTER LAB MANAGEMENT

Computer lab space is expensive and those in charge of computer lab management cannot afford to waste it on underutilized stations. Station images can become unmanageable and lab managers must decide which applications to exclude. Locating available hardware can be difficult for students and faculty, so lab managers need a way to help them quickly and easily identify open computers. Gathering real-time usage data is the most effective way to solve these problems and eliminate the guesswork associated with managing computer labs.
Truly useful statistics provide data that is specific and digestible. Specific, in the sense that it needs to be viewable on an individual computer station, application, and user level. And digestible, so that the data can be used by managers and students to remove the guesswork.

DATA COLLECTION

There are different approaches to collecting usage data, but at New York University (NYU), software is used to collect and report on usage data. Accuracy increases and availability is improved when sophisticated software is used instead of tracking usage manually. Taking manual headcounts as students use computers is inefficient and inaccurate. Valuable staff time is consumed during collection and the resulting data is prone to errors and limitations that prevent it from being a true representation of usage. More importantly, it is not feasible to gather certain data manually, like which applications are being used and the duration of their use. Data collection and reporting software also offers easy analysis of the data; it automatically aggregates and segments the data, so it is digestible and meaningful.
Monitoring software needs to answer the questions that lab managers have. Any application used to gather data should be FERPA compliant and only track appropriate user login and application data. The software should work with a variety of operating systems and clients—macOS and Windows; virtual and physical clients.

APPLICATION TRACKING

Knowing which applications are being used and how often can be a guessing game, which leads to unnecessary strain on an already limited budget. Tracking the use of every local application or website visited often results in excessive information. Only tracking applications and websites that result in meaningful data helps cultivate digestible insights. For example, tracking many of an operating system’s default applications would only clutter the data that is being collected.

Tracking which expensive applications students are using might only show a portion of the full picture. For example, what if a student opens Adobe Photoshop, minimizes the window, and then proceeds to open and use Microsoft Paint? Even though the application was opened, it does not mean that it is being used. It is important to clarify applications that are actively used. Although at first, it might not seem worthwhile to track certain applications, identifying and tracking similar applications can reveal interesting comparisons.

Application Licenses

Usage data allows identification of software licenses that are being paid for each year but are not being used. This is crucial when imaging stations. Application licenses can be reallocated to different machines or labs where they are more likely to be fully utilized. The data shows which software is used and to what degree and has allowed NYU to negotiate better licensing agreements—more in line with the actual application use. Most schools invest heavily in expensive application packages; application usage data can help when it comes to negotiating renewal prices, and possibly investing money elsewhere. Whether buying licenses on a per-station basis or a campus-wide agreement, this information is key to decision-making. Tracking if each license is being used might give an inaccurate picture of application usage. For example, if at any given time only about 10% of AutoCAD licenses are being used, the number of individual licenses could be drastically lowered or a lower campus-wide price based on the actual usage trends could be negotiated. This problem can be further eliminated by effectively communicating where students can access the application and when the station is available for use.

Reduce Station Images

Application data can also be beneficial when identifying which users and labs use these applications the most. This data has allowed NYU to reduce its base image and to provide the applications that the students really need. Recently, they also started reviewing monthly metrics on application launches to determine whether software should be removed from the images. NYU images twice a year, so based on the previous usage they can determine if an application should remain available or be removed. It is part of their yearly workflow to improve the software offerings for students in their labs.

Application and login information arranged by station has also helped NYU identify which applications get used versus what they think they need to include on an image. This has allowed them to reduce the base image.
After they image a station or perform a hardware installation they ensure that the stations are handling any changes that were made. This imaging cycle happens twice a year; the rest of the year, they run weekly reports to manage inventory.

Students may be using an online version of a specific software that has been installed. If students are using Microsoft Word Online, for example, then it might make sense to think about removing the Microsoft Word application from the station image.

Tracking Web applications can also add more insight. For example, it might be useful to see how many students prefer to use Google’s free G Suite over Microsoft Office. More students might prefer Google’s G Suite, in which case it might be best to consider removing Microsoft Office from the station image or limiting the number of licenses purchased.

HARDWARE ALLOCATION

Computer lab monitoring shows answers to important questions—which machines are being used and how often, which physical layout is best, and if more or fewer seats are needed in specific labs. This data from monitoring ultimately makes the job of computer lab management much more straightforward.

Station Utilization

NYU often needs to find out the actual usage of stations in a computer lab; this information is useful for driving traffic to underutilized labs or ensuring that stations are operating as expected. They collect individual station usage data to determine when the station is powered on, when there are students actively logged in, and which applications are being used on that station.

There are many reasons why a station might not be used; it might be based on where the machine is physically located, which operating system is installed on it, whether it is a desktop or a laptop, or what the perception of the machine’s availability is. When this information is known, the reason for underutilization is understood. NYU collects data on stations and individual computer labs and further subdivides this information into smaller groups based on criteria they are interested in tracking. For example, tracking macOS vs Windows, hardware additions (scanner, more RAM, etc.), and the station’s physical location might provide value for different organizations. They segment tracking data to answer many specific questions. This allows them to know with certainty whether stations with Adobe Creative Cloud are used more than stations with Microsoft Office. Stockpiling data helps to curb the uncertainty of the future of computer labs and their impact. Having the flexibility to gather data on anything deemed important guides computer lab management decisions and allows managers to prepare to make the correct decisions.

For example, real-time data, when added to the physical layout of a computer lab can help to identify problems in computer util