Data analysis

Data Analytics and Higher Education: Colleges Fail to Teach the Right Skills

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Everyone knows that American colleges and universities teach most disciplines poorly. History, sociology, anthropology, English and other subjects have been infiltrated by professors who impart opinions rather than impart knowledge.

What about a difficult and technical subject like data analysis? If it seems (for the moment) to have escaped politicization, it is not taught in an optimal way. That’s what Steven Zhou, a Ph.D. candidate, argues in today’s Martin Center article.

Zhou explains that data analysis has advanced rapidly in recent years, and the programs it contains cover the advances. The problem, he argues, is that students find themselves lacking in some basic skills.

Zhou writes, “By placing too much emphasis on these advanced analytical methods, many programs lose sight of the importance of the ‘simpler’ methods and skills that are actually more important and relevant in future careers. My colleague and I collected an informal survey of about 100 former students working in non-academic jobs, asking them what statistical methods they used most often at work. The most frequently used methods were simple correlation (62% used “a lot”), data visualization (55%) and regression (49%); the advanced methods taught in most programs were used ‘little’ or ‘not at all’. In fact, the most frequently used software was Tableau, which is a data visualization platform. This reflects the growing trend of data visualization as a key skill in analytics jobs. »

The big flaw, Zhou argues, is that students aren’t trained in data visualization techniques: “The repercussions of poorly conducted data visualization and failure to explain statistical results are potentially far more damaging. . . for the vast majority of the population, advanced methods are far less valuable than the ability to communicate and visualize data. It is no use for students to be able to perform “latent class analysis” if they are unable to explain the method, demonstrate why the results are important, and visualize the results to people who have no idea what latent class analysis is. ”

I’ve heard of other technical college programs, like computer science, that they tend to focus on things faculty members like to teach more than things students need to know. Apparently, this also applies to data analysis. Deans should be careful.

George Leef is the Director of Editorial Content at the James G. Martin Center for Academic Renewal.