Education Technology Services
Adaptive Learning vs. Personalized Learning: A Guide to Both
Technology is playing an increasingly pivotal role in the world of education, especially when it comes to enterprise learning management and online learning solutions. As organisations and educational institutions work on providing the most efficient and impactful learning experiences, two key concepts that are gaining popularity are adaptive learning and personalised learning. Though these terms are sometimes used interchangeably, they represent two different approaches.
The role of technology in modern education
The advent of technology in education has brought about significant changes in how learning is delivered, assessed and managed. Systems like learning management systems (LMS), assessment management software and online learning management platforms enable organisations to streamline the process of delivering content, tracking learner progress and evaluating final outcomes. All these technologies have facilitated the growth of both adaptive and personalised learning, two approaches that focus on tailoring the educational experience to the learner's needs.
What is adaptive learning?
In adaptive learning, technology is used to modify the delivery of educational content in real time depending on a learner’s performance and level of readiness. This approach leverages algorithms and data analytics to monitor how well a learner is able to grasp concepts and adjusts the instructional material accordingly. By using adaptive learning algorithms, conventional education is being reshaped into a more efficient and individualised process. For example, if a learner struggles with a particular topic, an adaptive system might provide additional resources, such as video tutorials or extra practice questions, before allowing the learner to move on to the next concept.
In an enterprise learning management context, adaptive learning systems can be integrated into existing LMS management platforms to ensure that training programs are customised for employees based on their skill levels and learning pace. This approach can increase engagement and effectiveness in corporate training, as learners receive targeted support where and when they need it most.
Key features of adaptive learning
- Data-driven adjustments: The system continuously gathers data on the learner’s performance, making real-time adjustments to content delivery.
- Progressive difficulty: As learners demonstrate mastery of a topic, the system increases the difficulty level of subsequent material, ensuring that learners are consistently challenged.
- Inclusive: Learners at all stages of progress can be included in the same program since the system adapts to all levels of learning. Slow learners may receive extra materials or remedial classes to help them catch up.
- Immediate feedback: Learners receive instant feedback on their performance, enabling them to understand their mistakes and correct them right away
- Automated pathways: Learners are guided along different learning paths depending on their responses, thereby creating a more customised educational experience without the need for human intervention.
What is personalised learning?
Personalised learning goes beyond data-driven content adjustment and focuses on an educational approach that is more learner-centred. In personalised learning, the learner has more control over the pace, style and structure of the educational journey. The aim of this approach is to accommodate individual learning preferences, goals and interests. While personalised learning can also involve the use of LMS, it places a greater emphasis on customising not only the content but also the mode of delivery to fit each learner’s unique needs.
For instance, in a corporate setting, personalised learning could involve employees choosing specific courses that align with their career objectives. While adaptive learning adjusts content based on performance, personalised learning allows the learner to take the lead in deciding what to learn and how to approach it.
Key features of personalised learning:
- Learner autonomy: Learners have the freedom to choose the subjects they study and the pace at which they progress.
- Goal-oriented learning paths: Learning plans are often designed around the learner’s personal or professional goals. This ensures that the content is relevant and meaningful to them.
- Variety of resources: A range of instructional materials, such as videos, articles and podcasts may be available for learners to choose from depending on their learning preferences.
- Teacher or mentor involvement: In some personalised learning environments, educators or mentors play a role in helping learners craft their learning paths, providing guidance and support where needed.
How are adaptive and personalised learning different?
Though both adaptive and personalised learning seek to enhance the learner’s experience, they differ in certain key ways:
- Technology-driven vs. learner-centred: Adaptive learning is primarily driven by algorithms and data analytics that adjust the content automatically. In contrast, personalised learning puts the learner in the driver's seat, allowing them to have more control over their educational journey.
- Real-time adjustments vs. custom paths: Adaptive learning systems make adjustments in real time based on a learner’s performance, while personalised learning involves creating tailored learning paths that may not necessarily adjust dynamically during the learning process.
- Content control: Adaptive learning systems dictate the content based on a learner's strengths and weaknesses. Personalised learning, on the other hand, allows the learner to choose the content and delivery methods that best suit their preferences.
- Assessment approach: In adaptive learning, assessments are often built into the system, providing continuous feedback and adjusting learning paths as necessary. Personalised learning may involve more varied assessment methods, including self-reflection, project-based assessments or peer feedback.
Benefits of Adaptive Learning
Incorporating adaptive learning into enterprise learning management or educational environments offers many advantages:
- Efficient learning: Adaptive learning ensures that learners spend their time on areas where they need improvement, thereby streamlining the learning process.
- Scalability: As adaptive learning relies heavily on technology, it can be scaled to accommodate a large number of learners.
- Consistent feedback: Learners receive ongoing feedback, helping them stay aware of their progress and areas for improvement.
- Improved retention: By ensuring that learners fully understand each concept before moving on, adaptive learning helps improve long-term knowledge retention.
Benefits of personalised learning
While adaptive learning emphasises efficiency and precision, personalised learning offers its own set of benefits, particularly when paired with effective assessment management software and LMS:
- Learner engagement: By allowing learners to take ownership of their educational journey, personalised learning boosts motivation and engagement.
- Relevant learning: Learners can focus on content that aligns with their personal or professional goals, making the learning experience more meaningful.
- Flexibility: Personalised learning can accommodate various learning styles and preferences, offering a variety of instructional resources and assessments to choose from.
- Holistic approach: Personalised learning takes a more holistic view of education, focusing not only on academic achievement but also on personal growth and self-directed learning.
Picking the right approach
Whether to implement adaptive learning, personalised learning or a combination of both depends on organisational goals, learners' needs and available resources. Many modern LMS offer capabilities that support both adaptive and personalised learning, enabling institutions to deliver more customised and effective learning experiences. When combined with assessment management software, educators can ensure that learners are being challenged at the right level and receiving the support they need to succeed.
Challenges and considerations
Since adaptive learning depends on data analysis, it is important for organisations to pay attention to data collection methods, data protection and usage. Compliance with relevant data regulations and establishing strong privacy policies are important issues that must be considered. Ethical data practices and eliminating bias in algorithms are other critical factors to be integrated into the system.
Final word
Both adaptive learning and personalised learning represent two powerful approaches to modern education. Each has its own strengths and applications, and the best solution often lies in finding the right balance between them. By leveraging advanced online learning management tools and thoughtful instructional design, institutions can create learning environments that meet the diverse needs of today’s learners while improving outcomes across the board.
Using technology in learning programs gives employers the opportunity to help employees perform at their best by providing access to effective personalised or adaptive learning programs. And it gives employees an opportunity to work towards fulfilling their career goals.
How can Infosys BPM help?
The Infosys Wingspan Assessment services is an AI-enabled service that enables organisations to assess existing or future employees remotely and at scale. Our ready-to-use assessment platform can help you create, run and administer tests. We also offer virtual proctoring services, scheduling, reporting and analytics. Contact us to learn more.