Analytics, Data Reporting, vs. Raw Data Dump: The Direction for the Higher Education Institutions to Perform Academic Analytics

Are you in the process of looking for a new solution as a learning management system, rotation management system, exam management system, video streaming platform? In short, are you particularly interested in a tool that may provide you valuable data to make decisions as a program or an instructor? Perhaps, you have heard the buzz words from the vendors such as analytics or data reporting. Be warned. The devil is in the details.

This article is not to put any particular company under the spotlight; however, it is to warn the stakeholders for the potential short delivery of the promises that you may hear during a sales speech. Analytics continues to be a popular selling gimmick for modern instructional technology. However, some may provide you nothing more than an electronic page with some filtering function in which you click “run,” “export,” or some similar button to display a spreadsheet looking page. This scenario happens if you are lucky. Sometimes, you get a giant spreadsheet in which you need to BYOES (Bring your own Excel skills).

This kind of raw data dump or “reporting” is far from the concept of analytics or business intelligence because the data still needs to be processed to answer specific questions. The data is not streamed live and not interactive for the end user. The challenge is that most technology companies need to select one direction either to become good at something specific such as exam management or to become a comprehensive tool such as a learning management system. Higher education institutions require data to make decisions at multiple layers. This sometimes means the scope could be as limited as analyzing students’ admission data coming from a Student Information System to identify critical factors affecting admission decisions or to evaluate how a degree program is doing in multiple areas such as financial, educational, and administrative. Every higher education institution operates in a different context and responds to various regulations and expectations. When this happens, a specialized solution may only provide data on a very narrow aspect of the situation while a larger company with comprehensive solution may end up stretching too thin to become flexible and responsive to any custom needs of the higher education institution.

To this end, I am not very hopeful about any technology company providing custom analytics solution to everchanging needs of the higher education institutions. I expect that it would not be profitable for companies unless they start to charge extra for consultations or custom solutions. The risk for this approach is the possible communication issues between non-technical (academic faculty and staff whose have the needs to be addressed) and technical staff from the company who may not have the understanding for the unique circumstances the institution is in. I think the real solution will arise within the institution through those who can bridge the gap. For the lack of a better word, the “translators” who would translate between technical and non-technical audiences and who are also makers not only understanding the needs but also developing solutions to respond to these needs.

Along with the access to the backend data of the technologies in the market through API, transferring the data into data visualization (business intelligence or analytics) tools, and creating custom data dashboards, or even conducting advanced statistical analysis to answer specific questions, it could only be done by those who have comprehensive understanding about the big picture. At this point, I am not sure if there is such a degree program training anyone in education for this area. My best-biased bet will be instructional designers with proper training. What I am confident is that technology companies will not be able to provide this solution. The solution will be created in-house.

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