Taking the Guesswork out of Computer Lab Management
July 1, 2018 | Data
Providing effective and efficient tech services to students requires constant decision making, and monitoring software can help.
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.
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.
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.
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.
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.
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 utilization due to lab space/setup limitations. This information has helped NYU better understand underutilized machines and gives them ways to help guide more traffic to those machines. Some available options are to provide better software on those machines or put them closer to the windows. Real data tells a story and gives vital information that can help in making important computer lab management decisions.
Tracking specific websites that are visited can also add beneficial data. Students may only access computer labs just to surf the web. Nothing is more frustrating than having a lab that is stocked with expensive hardware and software and seeing that students are using it to watch YouTube or browse Facebook. Website visit data can be valuable when learning how to direct students who are looking to just use the internet or closing certain labs during certain hours. Labs that are only used to browse the internet might have applications that can be removed. They may also be put on a slower track for hardware upgrades. All the traditional computers in a lab might be switched out for less expensive Chromebooks or lab usage rules might need to be amended to ensure hardware resources are available to students that can fully utilize them.
Physical Layout and Applications
Data showcasing station and application usage identifies how frequently stations and applications are being used. This data has helped NYU determine the use of software and machines in labs and has enabled them to reshape the computer labs and software packages for those areas. Application launch and application usage history data has also helped in this regard. This can provide an understanding of what software is used and to what extent the data can be leveraged to negotiate for lower prices during a renewal process. Even just moving a few machines to different locations can impact the usage of specific computers. Some students prefer more privacy while other students need an environment to work on a computer as a group.
It is a hassle, and frustrating, for students and faculty to walk from one lab to another just to find out that there are no computers available. Lab spaces are valuable and are always at risk. Thus, providing this information clearly and easily helps students find and use available resources, and further, faculty and IT can see and make decisions on how these labs are being used.
Real-Time Availability Maps
NYU sees the most value from real-time computer lab maps. The student tech center web page includes embedded maps so students can see real-time station availability. Additionally, the maps cycle on digital signage in public spaces for all patrons to see.
Real-time computer lab map displays allow students to check which stations are available at their location and can automate portions of computer lab management. The maps can be embedded on a website, can be used in conjunction with a kiosk display, added to a mobile app, or any other way that is beneficial. This information can show students, faculty, and staff where machines and software are available for use at any given moment in a day.
With data from individual labs, determining whether a computer lab’s hours meet the needs of students is simple. If data shows that a computer lab is full as soon as it is opened, it may show that opening an hour earlier will be better to allow students to utilize labs. Conversely, a lab might be rarely used and need to have shorter hours or be closed completely. Small adjustments to hours and lab staff can save large amounts of budget. Instead of hiring more employees, there might be lab managers that could be shifted around based on individual lab usage. Trimming or adding open hours can help to more accurately show lab utilization and potentially cut staff costs. Something as simple as adding or removing lab hours can go a long in helping problems with computer lab management.
Learn more about real-time availability maps
The monitoring software also includes a public API which showcases the data in more ways than is natively supported. The API includes status information on a number of stations that are either available, in-use, or offline. It can also be used to display several different labs in a carousel format. This information can be added to an existing school app, website, or anything else that can be imagined.
Computer Lab Management – Peak Usage
Some computer labs appear to be full to students or faculty as they pass by, but is that an accurate picture of the lab’s use? Is the lab truly full or could it be that only the computers closest to the door are being used? Gathered data can show when the most computers are in use at the same time. This data may help identify patterns that point to consistent times when many or few computers are in use and might allow for adjusting computer lab hours or making alterations to the number of computer lab staff throughout the day. This can also show whether more computer labs are needed or if students just need to be aware of less-used labs. These problems can be solved with the right information.
Are the right students able to find computers? School administrators might want to know if different groups of students have equal access or use computers equally. Tracking individual users and segmenting them into meaningful groupings can clarify. Grouping students by their major, class level, or other characteristics can provide all the answers that administrators need to show that computer labs are being used. This information can bring to light unknown usage situations. For example, English majors using the graphic design lab—that might have different and more expensive applications installed. Other use cases for this type of data can include tracking different student demographic groups to ensure equal access to computer resources. This same information could also be used to prove the demographic diversity needed to receive government grants and other funding.
The usage statistics for each individual user can be used in unique ways, too. For example, login time data could be used to track student lab manager’s attendance or classroom attendance in general, to ensure that they were logged in when they were supposed to be; these users can easily be segmented to make them viewable. This data will allow reporting on total campus activity or on a per-lab basis, knowing statistics such as the number of logins per lab or campus-wide logins at all locations.
User data displaying the number of logins for a specific user, the number of stations for that user, the total usage, and average usage for a user are also available. This is used to pinpoint a specific user or figure out a use-case for the average computer lab user.
Individual user tracking can also help to protect hardware and software assets. User data can be used to know which students were last on a school laptop before it was stolen or if students are accessing inappropriate websites or software.
Universities and colleges have always struggled to have enough money available in their budget to cover all their technology needs; technology is a large cost in education. With the cost of always updating and upgrading, do lab managers and administrators really know or understand if they are getting a return on their investment? With useful data, Universities and colleges can make decisions that can save thousands of dollars. Those helping with computer lab management and administrators can know that they are making the right decisions.
While labs are at risk of being extinct, data on lab statistics can save labs, and in some cases, expand them by taking the guesswork out of computer lab management.