What Is Personalized Learning?
In most settings, all students are expected
to learn material at the same time and in the same way. Many find themselves either
ahead or behind others, and learning outcomes suffer, particularly for students who need
extra time to master the material. Flipped courses, competency-based education,
and online and hybrid classes are changing the way we think about learning. Flexibility
in delivery creates opportunities with learning that adapts to the needs of each student.
Combining new learning models with digital courseware, integrated planning and advising
for student success, and analytics can create a learning ecosystem that tailors support
to individual students. For example, an e-textbook could share data
with a learning management system about the number of pages read, time spent on each page,
notes made, or number of times a video is watched. An analytics tool could evaluate
those data for patterns associated with engagement, achievement, and course success. The tool
could trigger alerts to students and faculty when problems arise.
An adaptive learning system could adjust learning content on the fly, based on data from an
online quizzing tool that showseach student’s mastery of the material.
Prior-learning assessment credits skills and knowledge individuals have when they enter
a course. In a competency-based program, students move
to the next unit as soon as they demonstrate mastery of the specified learning objectives.
Advisors would have access to data and tools that enable them to tailor guidance and degree-planning
support to help students maintain progress toward completion. Instructors see which students
need extra help and which would benefit from new challenges to keep them engaged.
This integration of tools and systems facilitates the kind of personalized learning that can
improve learning outcomes, boost student confidence and accountability, and increase rates of
retention and, ultimately, degree completion.