Revisiting an educator's dilemma: using natural language processing to analyze the needs of employers and inform curriculum development

Employers in technology are constantly changing their job advertisements and it is a challenge for academic programs to produce graduates who can meet these job requirements and employer expectations. The Information Systems (IS)/Information Technology (IT) educators have been facing the conundrum of whether an emerging technology is a game-changing development or something more transient so as to avoid bloating the curriculum. This study examines the body of knowledge as represented in our IT/IS program course syllabi and the recent job postings in five of our specialization areas including data science, computer science, healthcare IT, information systems and cybersecurity using natural language processing techniques. One of our goals is to identify the major overlaps and gaps between the two entities systematically by employing quantitative methods. The major contributions of this study lie in that it demonstrates how such data-driven analysis and mining approach informs clarifications to the wording of existing course syllabi, modifications to existing course contents, or the introduction of new courses into the curriculum. Lastly, the future research directions are delineated which this knowledge base can be applied to enhance university graduates' employability by analyzing students' resumes and presenting which jobs most closely match their knowledge, skills, and abilities.