You can always come back and revise things later. Remember to avoid letting the perfect become the enemy of the good, or, as they say, know when the results you are getting are good enough. This may be the most difficult step in terms of the need to create or reiterate tests of what you have designed as an implementation. As you build the baseline, you may be able to craft your learning objective, or modify it. This gives you a starting place against which you can assess your progress. Use the application(s) you select to build a baseline. Tool selection comes next, but I am going to jump ahead for a moment. If you are a team manager, this matching of skill sets and tools (or managing the mix) will be essential to success. Some potential members may be expert at using some tools, and others may have different skill sets. You may need to select team members on an interdisciplinary basis. If you have two questions, you will need to do two separate analyses. Data analytics can only deal with one question at a time. You should only be looking to get data to answer one specific question at a time. Data analytics can help answer all of these questions, but there's a catch. Or maybe you used a new approach to the design or delivery of a learning experience and you want to know if it worked. Or you may want to know whether a learning experience had an impact, made a difference, or the information was used some time later, and from that study you learned something else and you then need to go back and learn some more. Usually this means you have a question about performance or accomplishment that you want to answer. Rather than just begin to copy data from your LMS or through xAPI, at the very beginning, the instructional development team must know what it is looking for. The first step is to decide what you want to know. In this article, I will describe a process for selecting software or applications for data analytics during front-end analysis (also called needs assessment). There are many application and software types that can be used to perform data analytics as part of your instructional development project.
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