This guest post was written by Owen P. Hall, Jr., Professor of Decision Sciences at Pepperdine University’s Graziadio School of Business and Management. He has more than 35 years of academic and industry experience in mobile learning technologies and business analytics. He also holds the Julian Virtue Professorship and is a Rothschild Applied Research Fellow.

Dr. Hall will also be presenting on The Growing Role of M-Learning in the Analytics Revolution: Application to Management Education at the Analytics 2014 conference in Las Vegas, Oct. 20-21.

Management education has come a long way since Sir Isaac Pitman initiated the first correspondence course in the early 1840s. Today, business schools are under growing pressure to engage in significant reforms due to the impacts of globalization, new learning technologies, and unprecedented economic uncertainty.

The increasing use of Analytics in business and government to improve efficiency and performance suggests similar opportunities for schools of business. A recent study, sponsored by the Association to Advance Collegiate Schools of Business (AACSB), revealed a wide gap between the changing needs of the business community and the programs being offered by the business management community.

The Analytics paradigm can be used to enhance management education and close the gap with the business community in the following ways:

1) Provide a conceptual setting for expanding student managerial decision-making expertise,

2) Assess student performance and identify appropriate additional learning resources via intelligent tutors, and

3) Offer business school administrators the capability to optimize operational effectiveness.

Identifying the “best” approach for teaching students and training professionals in modern decision-making and problem-solving is at the heart of the Analytics movement in academe. The learning goal should be to develop general analytic and quantitative problem-solving skills, which allow the graduate to transition seamlessly into the business universe.

The curriculum should be designed in such a way as to create an environment where the student becomes comfortable in using a wide variety of decision support tools. This is where mobile learning can play an important role. Typically, mobile learning (m-learning) is defined as the acquisition of knowledge through conversations across multiple contexts via interactive technologies. Mobile learning is designed to significantly alter the three pillars of traditional management instruction—fixed time, fixed location, and fixed learning pace—with a more flexible and customized learning environment.

The pairing of social media based mobile learning with the Analytics paradigm provides a vehicle for effectively integrating analytical based decision-making and problem solving into the curriculum at a time and place convenient to the student. This is a particularly important feature for working adults and those with disabilities.

The Analytics paradigm also provides business school administrators with the capability to better manage the institution’s strategic and tactical resources by reforming the traditional decision-making process.

Today, most business schools are facing intense competition and demanding students.  These forces tend to drive up the cost of student acquisition and retention. The emergence of the Internet generation as the new student body, who are web savvy and heavily engaged in social media, requires institutions to develop a more robust, nimble, and real-time response capability. Properly aligned with the school’s mission, the Analytics paradigm offers the promise of strengthening student learning and employment opportunities as well as improving institutional operational efficiencies.