One-on-one instruction is highly effective in corporate training, as the instructor can individualize material. Current e-learning tools often cannot provide this type of individualization. With adaptive learning, technology uses inference algorithms to adapt content to the learning needs of students based on their responses to tasks and questions. In this way, adaptive learning emulates one-on-one instruction.

Adaptive technology is the future of employee training. It collects data as employees progress through modules and uses that data to personalize goals and training content and techniques, creating an optimal learning path for each employee. The data is then stored and used by training managers to determine the effectiveness of training and change future courses so they better meet the needs of employees.

Imagine a world where adaptive learning in corporate training enabled employees to “major” in a specific subject, come across skills they never knew they had, sharpen those skills, and use them to take on more responsibility and earn promotions. This is adaptive learning’s true value. Here’s an example: A reporter could take a course on a specific type of investigative journalism or feature writing and then show through tailored assignments and exercises, tracked via the online learning platform, that he or she obtained at least a beginner’s knowledge in those skills and is ready for the next assignment.

The adaptive learning platform’s ability to track of the performance of an employee in his or her “major” provides human resources and managers an objective measurement of whether he or she is now ready for a stretch assignment or a promotion. Just as importantly, the capability to opt for a major develops employees who are more engaged, as they are at least partially self-directing their learning and know that they aren’t being provided a one-size-fits-all training plan.

Adaptive learning also represents a step toward employers taking more responsibility for the future of their staff. Feedback and assessment loops are a significant part of adaptive learning. Becoming efficient at evaluating skills gaps can ensure that learners do not think they know more than they actually do.

Adaptive learning technologies can help organizations make sure they are getting their money’s worth in terms of employees’ learning, applicable skills and essential knowledge. Jan Sramek, the CEO of Erudify, stated in an article for Corporate Compliance Insights that adaptive learning can enable learners to rapidly move through information they know already, cutting the time for training by almost 50 to 80 percent. This saves a lot of money for the organization.

Adaptive learning solves many e-learning challenges by modeling what each learner knows and continuously, dynamically adapting his or her individual learning path. Adaptive learning has completely transformed the way organizations train their employees. Thus, the adaptive learning approach can enhance training and development programs by enabling employees to learn more, faster.