If you were to grade higher education today, what letter would you give it? C-, D+ an even B, something else?

Whatever your opinion, higher education is in need of serious modernization, if not a complete overhaul. Customer satisfaction with cost, graduation rates and return on investment is exceedingly low. So too are post-graduation employment levels and graduation completion times.

How, then, can higher education turn things around? Innovations, such as massive open online courses, orMOOCs, are one approach. But the complete answer requires three broader ingredients, according to our resident education experts: new data, new learning management systems and adaptive learning gleaned through Code Halo™ thinking.

• New data. If higher education is going to get smarter, it needs new data – a lot more new data – to understand student needs and learning styles, as well as its own institutional value. This new data, big or small, structured or unstructured, can be mined from one of three meaningful sources:

1. Public information taken from social media platforms, such as students' personal interests and hobbies (including musical tastes and trips taken) to drive educator insights, sympathies and personalized curriculum

2. Online coursework interactions, including last log-in, time spent on content, course progress, intra-student communications, instructor feedback and, of course, test scores.

3. Third-party information and government statistics, including educational spending, institutional policies, rankings, majors, infrastructure, campus life and more to better understand student preferences.

By capturing, aggregating, analyzing and acting upon the insights that can be gained by the above data at every stage of the student lifecycle, educators can create powerful "student personas" to tailor their teaching approach, the student's job search and, ultimately, alumni involvement.

Interactive

Figure 1

• New learning management systems. In their current state, learning management systems (LMSs) are used more as a tool for administrative efficiency, including tasks such as course content distribution, broadcast announcements and e-mail discussions. 

When coupled with new data, however, next-generation LMSs can do so much more throughout the student lifecycle, including helping them select the right college, choose a major, identify a mentor and land a job after graduation.

For example, Khan Academy offers personalized landing dashboards similar to those found on Netflix and Amazon to guide learners and provide relevant content based on their experience.

To get an idea of what's possible, for a student who is 70% likely to pursue a career in applied mathematics, a smarter LMS might recommend a college with a strong math program, leading math professors and personalized connections to course resources, including academic groups of interest and outside experts.

Or, assume that a student earns a degree in anthropology from a prestigious university. Based on her personal Code Halo, she presents strong traits indicating a fit with a particular company's organizational theory and culture. This type of "code-meets-code" matching is potentially more powerful than traditional hiring and recruiting models, and is only made possible through an LMS that optimizes technologies built on a social, mobile, analytics and cloud foundation (the SMAC Stack).

• Adaptive learning with Code Halos. Now the real fun begins. When armed with a big data-ingesting LMS, institutions can simplify the delivery of adaptive learning, which enables students to spend significantly less time completing courses while maintaining learning quality. 

To accomplish this, however, institutions must create and apply meaning from student Code Halos to illuminate insights about their strongest subject area, motivations for learning and potential career paths. Educator Code Halos can be added to the mix to better understand the ideal pace of teaching and when to intervene with struggling students. Product Code Halos can enable smart course design and continuous innovations in course curricula and user interfaces. And institutional Code Halos can be tapped for feedback on alumni networks, reputation information, location, graduation rates, vocational alignment and the quality, depth and breadth of the curriculum.

These are not just pie-in-the-sky ideas. Institutions are already applying Code Halo thinking to improve the learning experience. For example:

• Purdue University acts upon new data collected from its LMSs to track student performance and identify at-risk students in real time.

• Samford University uses an "enrollment intelligence" algorithm to predict which students will most likely enroll by analyzing their social media behavior; Denver University is doing the same.

What the Future Looks Like

The bricks are still being laid for the future of higher education, but a glimmer of what is possible can be seen in Web sites like Match.com, which exemplifies what can happen when you converge student, institution, educator and employer Code Halos, according to our experts.

When student Code Halos intersect with institutional Code Halos, for example, the best matches of students and schools can be revealed. Educator Code Halos intersecting with employer Code Halos can pinpoint opportunities for collaboration between institutions and businesses. And student Code Halos connecting with employer Code Halos can show fruitful career matches.

To get started, or to further your institution's Code Halo thinking, we recommend the following:

• Reexamine the student lifecycle to identify where Code Halo thinking can be applied to improve the student experience.

• Identify programs and courses that can be redesigned for adaptive learning.

• Identify hypotheses that can be tested with analytics to drive student recruitment, retention and persistence.

To learn more, read our full white paper, It's Time for Learning to Go Back to School: Next-Generation Approaches Enrich the Student Experience or visit our Education Technology Practice.