Reimagining Higher Education

Anyone plucked from a century ago and set down in a typical lecture hall today would immediately know they were on a college campus. With better technology and a much deeper understanding of how students learn, educators are beginning to make strides in personalising learning by combining the best of traditional teaching with digital technology, using analytics to track student success, and focusing on competencies rather than credit hours. 

The way we learn should be our most personalised experience because no two people process information the same way.
– George Siemens  

Stanford University, for instance, in partnership with the online learning platform Khan Academy, piloted a blended learning “flipped classroom” biochemistry course. Students watch video lectures online at home and then spend class time solving problems, maximizing the time students spend with professors.  

Predictive analytics, commonly used in the private sector to inform decisions about consumer behaviour, offers higher education institutions a more effective way to calculate and track student progress. Software platforms such as Course Signals, for example, can serve as an early warning system for both students and faculty. Students receive notifications about how they are performing in a course as they progress through it. By providing this performance data to faculty, they are able to identify students who need additional assistance to succeed and can target interventions to ensure at-risk students stay on track. At Purdue University, students enrolled in Course Signals classes have a 21 percent higher graduation rate than those enrolled in courses that don’t use the software.

Competency-based models are emerging as an attractive alternative to the traditional credit hour model. Rather than using “butts in seats” as the yardstick for measuring success (How many credit hours did you complete?), competency-based degree programs focus on whether students are actually mastering the material.