Personalized learning taps into the innate human tendency to seek information independently. With a growing emphasis on diversity, equity, and inclusion, offering personalized learning solutions is becoming increasingly attractive for organizations.
If you are familiar with adaptive learning, an approach to learning that uses technology and data to tailor educational experiences to the needs and abilities of individual learners, you may be wondering what personalized learning has more to offer.
There are some tangible differences between these two approaches.
Adaptive vs. Personalized Learning
Adaptive learning uses data and analytics to adjust the learning experience for each learner or target group, tailoring it based on their performance and behavior. Think of it as a personal fitness trainer that dynamically adapts your workout routine based on your real-time performance and fitness level. In the same way that the trainer adjusts exercises to suit your strengths and challenges, adaptive learning provides personalized recommendations for learning materials and activities, ensuring that the educational journey is tailored to each learner’s unique needs and progress.
Personalized learning not only incorporates adaptive learning but goes a step further by empowering learners to actively shape their learning journeys. Learners can modify their educational journey based on personal preferences, including goals, skills, and career aspirations. This concept mirrors the customization of a playlist in a music app, where user preferences play a key role in shaping the overall experience. Unlike adaptive learning, personalized learning is an ongoing, adaptive process that seamlessly blends technology-driven customization with user-driven preferences.
The key difference between telling employees what to learn and letting them choose is giving them a say in their own learning. Instead of dictating specific skills, your role is to find out what skills would help them do their jobs better, and then provide chances to learn those skills. It's about letting them decide what's most useful for their work now.
The benefits for both learners and therefore for organizations are multiple. Personalized learning pathways enable employees to develop the skills they need to excel in their roles and contribute to the organization’s overall success. It also aids individuals transitioning to new roles through upskilling or facilitates a smooth return to the workplace after extended periods of absence.
How to design personalized learning paths
From the instructional design perspective, a key starting point for crafting personalized learning paths, is understanding the learners’ diverse backgrounds, learning approaches, and prior knowledge. This lays the foundation for creating learner profiles which allow the design of suitable learning content that meets their needs.
Next up are the learning objectives; clarity is paramount. Each module should have specific and measurable goals, aligning with both individual learner aspirations and the broader organizational mission. To let learners reach these goals, it is crucial to craft the learning content in different formats so that it can be easily adapted to individual preferences.
Another key element is the visible progress tracking. This transparency provides learners with a clear overview of their learning journey and accomplishments. An effective tool to achieve this is the Interactive Hotspot Menu, a feature developed by LearnChamp for the Totara learning platform. The Hotspot Menu utilizes visual elements that can be customized to match your company's corporate identity, such as an individualized map or any desired graphics. This map not only showcases learners' progress but also introduces various areas of learning that can be explored. The design aims to increase learner engagement, foster a sense of curiosity, and create a dynamic and interactive learning atmosphere.
How to implement personalized learning paths
Learning management systems (LMS) play a crucial role in promoting adaptive and personalized learning experiences. Totara Learn is an excellent example of this, as a user-centered design has and places great emphasis on personalized learning paths that give employees an active role in their training.
For example, with the learning plans available in Totara Learn, managers can unlock learning content for different areas of development. These plans can be personalized by setting specific priorities and objectives. Competences and the corresponding courses can be included in the plans either automatically or only after approval by the manager, depending on the learner's position or department. Learners are thus encouraged to manage their own learning and development. They can build their learning into their work schedule, update their plans with new courses and programs, monitor their progress in their learning history and demonstrate their achievements with downloadable certificates such as course completion certificates.
AI-personalized learning paths
AI platforms can create personalized learning paths by leveraging advanced tools to automatically tag content in the library and suggest the most relevant information to each employee. This technology ensures that employees are matched with the right learning resources, providing tailored support for their individual development. Traditionally, learning paths are assigned based on job roles, but AI improves upon this model. It understands the content and uses that information to personalize the learning experience.
Companies like Cornerstone, Sana, and SuccessFactors are integrating AI into their platforms to enhance personalized learning. Cornerstone's AI fabric recommends courses based on specific skills, Sana connects tools like Galileo to learning, and SuccessFactors' new AI features provide users with a curated view of learning tailored to their roles and activities.
When dealing with AI however, it's essential to understand that results are generated based on patterns learned from data and are probabilistic. As a result, AI systems might not always provide accurate or unbiased information. This acknowledgment is important for users to exercise caution and critical thinking when interpreting and applying AI-generated results.
In light of the evolving landscape of corporate learning, Josh Bersin's recent insights on 'Autonomous Corporate Learning Platforms Arriving Now, Powered by AI' resonate deeply with the shift towards more personalized and adaptive learning environments. Bersin highlights the transformative potential of AI in revolutionizing how learning content is delivered and consumed within organizations, making a compelling case for the integration of AI-driven solutions in personalized learning strategies. This perspective underscores the importance of staying at the forefront of technological advancements in learning and development to foster a culture of continuous improvement and innovation.
Conclusion
According to Josh Bersin, the key challenge in corporate training lies in surpassing traditional methods and embracing a learning culture within organizations. This culture empowers employees to actively shape their educational paths based on their individual preferences and aspirations. Learning is a deeply personal pursuit that enables individuals to expand their knowledge, broaden their perspectives, and enhance their skills. Therefore, it is crucial to provide materials that align with each person's interests, needs, learning styles, and pace to ensure effective learning. This is where personalized learning plays a vital role, as it is an ongoing and adaptive process that combines technology-driven insights with user-driven choices. By giving employees a voice in their learning journey, organizations can cultivate a more engaged and efficient workforce.
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We'd love to hear your thoughts! Share your experiences with personalized learning in the comments below. How has it impacted your learning strategy?
