Analyze Data to Make Recommendations
David Hollingshead, Gideon School District
Your technology committee is in place. You have established a vision and mission for technology use within your district. You have conducted surveys and gathered data. The next task is to analyze that data to make recommendations.
The major purpose of analyzing the data is to determine the gap between where you are and where you want to be. Your technology mission statement and the vision you have developed for technology use within your district should drive this analysis. With technology planning, you must always keep your ultimate goal in mind. Everything you do should be directed toward that target.
Basically, your data analysis should revolve around three distinct areas. Those three areas are hardware and software issues, instructional issues, and inservice issues. In each of these three areas you are looking for the gap between "what is" and "what should be." When you have identified that gap you will have a handle on the need. Then you are in a position to develop recommendations that will address those needs and help accomplish your technology mission.
Hardware and Software Issues
An accurate and complete inventory of all technology and software should be the basis of this aspect of your data analysis. You need to make sure you go beyond computers and consider all forms of technology within the district. Your analysis should address data, video, and voice. The integration of these three aspects is becoming more common in today's world and definitely needs to be considered in any technology plan.
This portion of the analysis is relatively straightforward. You simply need to determine the quantity and quality of technology and software that is available. You need to have established some minimum standards for each type of technology. The minimum standards should be driven by your technology mission.
This aspect entails looking at hard numbers. Much of this data was gathered for your Technology Census and this can be a starting point. Just knowing that you have a four to one student to computer ratio doesn't tell you much. But knowing how many computers meet your minimum standards can provide a basis for building your recommendations and designing upgrade plans. Ideally, you should have your inventory in a database of some sort so you can manipulate it and determine exactly what kind and what quantity of technology is available.
Furthermore, the hardware analysis should consider network infrastructure. It needs to look at servers, server capacity, trends in hard disk usage, trends in bandwidth usage, network structure, hubs, and switches. As you expand your desktop technology resources you must insure that your infrastructure is capable of handling it. Your data analysis should identify where you currently are and what you need to get where you are going. The gap between those two points then becomes the basis for your recommendations.
An analysis of available software is also important. You may have an extensive library of software, but if it is simply drill and practice software it may not move you toward the accomplishment of your technology mission. Data analysis should provide a clear picture of what categories of software are currently available in your district, and to what extent that software is appropriate for where you want to go. Once again, you are looking for any gap between where you are and where you want to be.
Instructional issues deal with how technology is currently being utilized in the classroom. This data often comes from surveys of teachers and students. The analysis should center around determining two things. First, you need to know how technology is currently being used to impact instruction. Data analysis should try to determine the type of uses of technology. This should include looking at the whole spectrum from more advanced uses focusing on inquiry based learning all the way down to the more simple forms of drill and practice uses. We already know that some uses of technology are more effective than others. Our technology plans need to move us toward the more effective uses of technology for instruction. In addition, we need to know how often technology is used for instruction. The type of instructional technology needed will ultimately be determined by the intended usage.
Second, you need to know what kinds of additional technology teachers want. This will most likely involve an analysis of narrative data and interviews where teachers have indicated how they would like to use technology. It could also come from a "pick-list" on a survey but this would have already limited their choices and may not provide complete data. If a teacher has a vision for the use of a particular type of technology, then it is important to try to develop recommendations that will provide the requested technology. Conversely, there is no need to place advanced technology in a teacher's classroom unless there is some indication that it will be utilized. This portion of the analysis will also help identify the types of software that should be considered.
This may be one of the most difficult areas of data analysis, because sometimes we may not know what it is that we need to know. Undoubtedly, the data you have collected will give some indication of what type of technology inservice the teachers desire. Your data may even include a listing of requested inservice topics, or your professional development chair may have that data. But as you look for the gap between "what is" and "what should be" you have to look beyond the surface. You have to determine what the current level of technology expertise might be, and then you have to go beyond the requested inservice and determine what types of training are necessary to ensure that teachers can appropriately integrate technology into their curriculum.
This is probably the most critical and yet most misunderstood aspect of the data analysis process. It is easy to look at numbers and determine we need so many more computers, or that we want to add LCD projectors and smart boards, or that we need to enhance our network. It is not as easy to determine what the data says about inservice needs.
Some Words of Caution
Throughout the data analysis process there are a few pitfalls we need to be careful to avoid. First, don’t use data analysis to support preconceived notions. Don't start with a technology plan in mind and then insure that your data analysis supports it. Too often we can "think" we know where we need to go and make the data analysis support that concept. Let the data analysis speak for itself and then develop the plan to address the gap that was identified.
Second, don't let your technology plan become a "single issue" plan. Too often we write a plan for a specific purpose. Our instructional technology plans need to address the broad scope of technology and technology use. Don't just analyze data for one purpose.
Third, an instructional technology plan must be a living document. It cannot be static. Technology is changing too rapidly for a document to be inflexible. Remember that data analysis must be ongoing. You cannot simply analyze the data once and then wait three years till you develop your next technology plan.
An effective instructional technology plan is dependent upon the quality of the data we collect, how we analyze that data, and the resulting recommendations that come from that analysis. The three distinct areas mentioned above are not the only way of looking at data analysis, and it is not the most technical method of looking at data analysis. But it will work. It will provide a good basis for developing your recommendations and moving forward with the development of your instructional technology plan.