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Gaps between teaching, practice of advanced analytics


Students of advanced analytics who aspire to leave academia and succeed quickly in business and government arenas should assess their approaches and tools in the classroom and their research, according to an informal Princeton Consultants survey conducted at the 2015 INFORMS Annual Meeting in Philadelphia. The survey revealed notable gaps between what students learn, what professors teach and what practitioners need.

Irv Lustig of Princeton Consultants, a longtime INFORMS member and a former employee of CPLEX, ILOG and IBM, reported the following findings:

• Students must learn more about building applications with modern technologies so they have the skills needed by the practice community.

• Professors are, for the most part, not teaching the programming languages used by students or in practice. Students and practitioners are using both Python and R, both of which are used heavily in the data science community, but faculty members are not adapting their courses to teach these new languages.

• With few exceptions,  there seems to be misalignment between the use of modeling languages in academia and the use of modeling languages in practice.

The survey of 72 self-selected participants, all of whom were onsite at the INFORMS Annual Meeting, was comprised of college professors (44 percent), students (32 percent) and practitioners (24 percent). The non-scientific “snapshot” survey was designed to compare the responses of these three groups about solvers, programming languages, modeling languages and software development based on the participants’ last two years of experience.

Gaps between teaching, practice of advanced analytics


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