Personalized learning is a form of teaching tailored to meet each student’s individual needs, rather than using an “all-inclusive” approach to education. Educators can utilize adaptive technologies and other tech-enabled tools to personalize content and learning experiences for each student, encouraging them to become self-regulated learners and academically successful.
Adaptive learning is the practice of using a computer program to customize how a student learns based on their performance, prior knowledge and other data. It enables teachers to deliver information more efficiently for students while offering them feedback to help them improve their performance.
Personalized learning is defined differently depending on who you ask, but at its core it means educators customize courses according to each student’s interests and learning styles. This not only makes for more effective and in-depth instruction but also fosters a greater sense of self-worth as students discover how best they can learn.
Additionally, personalized learning environments tend to involve students in meaningful learning activities like problem-solving or creative projects rather than simply following a predetermined curriculum. Compared to traditional educational practices that tend to be programmed or individualized, personalized learning experiences are more collaborative and authentic (Yang et al. 2015).
Although many educators mistakenly confuse personalized learning and adaptive learning, the two concepts are distinct. While adaptive learning utilizes data from various sources to adjust instruction in real time, personalized learning refers to a philosophy and pedagogy that can be applied to any classroom setting or online course.
Personalized learning tends to be more efficient and flexible than adaptive learning, moving at a faster pace with instantaneous feedback and adjustments. Furthermore, personalized learning places greater emphasis on learner agency than adaptive does.
However, it’s more chaotic and less organized than adaptive learning due to its mix of algorithms and human intervention.
For over half a century, personalized and adaptive learning have been part of educational support systems. But they have now evolved into more sophisticated approaches tailored specifically towards students’ individual needs. To create a successful personalized adaptive learning system, you must integrate all its components into one seamless system that meets learners’ actual requirements so they can reach their educational objectives.
This task is complex as it necessitates a range of skillsets, such as how to interpret student behavior and use that data to identify what information will be most helpful for them. Furthermore, one must create an automated system which can make decisions quickly based on this data.
When designing an adaptive learning system, it is essential that it accommodates the various backgrounds, schedules and interests of today’s students. Otherwise, the system could significantly hinder the learning experience and lead to less successful outcomes.
