What Is Adaptive Learning?
Adaptive learning is a process or advanced teaching technique that uses computer algorithms and AI to design unique and personalized interactions and deliver exceptional experiences to meet each learner's needs.
Adaptive learning is usually curated through platforms, with the aid of AI, these platforms can curate learning activities and content to meet each unique learner's needs and provide feedback and resources at the right time to ensure steady growth and experience.
Compared to traditional learning techniques where a one-size-fits-all approach is implemented, adaptive learning ensures each learner's needs are met while providing the right support and feedback to optimize their learning experience.
How Adaptive Learning Works?
With the aid of technology which is designed to emulate, enhance, and optimize the expertise and deliverables of great coaches and educators while also taking into consideration each learner's capabilities and adapting accordingly, adaptive learning can accommodate tens, hundreds, and even thousands of learners across various industries.
The process in which adaptive learning platforms adjust to individual learners varies, and these variations fall into two main approaches: Designed Adaptivity
Designed Adaptivity
This method involves designing a structured teaching sequence with the aid of an expert or educator to guide individuals in mastering content effectively. The expert is tasked with determining and controlling how lessons adapt, feedback, and content sequences, are based on certain factors known as adaptivity factors.
Using this expert-model approach, technology is programmed to operate based on unique situations on an "If THIS, then THAT" framework. This approach has the ability to respond dynamically to various inputs and learning scenarios, it can offer remediation to struggling individuals while also providing advanced content to high-performing individuals, or prompt those advancing too quickly to slow down. This adaptive learning approach gives the expert control and flexibility to customize adaptive learning platforms to fit needs and optimize the learning approach.
Algorithmic Adaptivity
This approach uses algorithms to answer two simple and important question:
What does the individual know?
What should the individual learn next?
Based on the answers to the question above, the algorithm picks the best content at the right moment. For example, algorithms like Bayesian Knowledge Tracing (BKT), which tracks and estimates the rate of learning, and Item Response Theory (IRT), are used to understand how individuals respond to certain questions and tasks.
Based on these algorithms and preset rules, the adaptive learning system adjusts in real-time to meet the learner’s needs just as a personal trainer would do during training sessions. Whether it is extra practice, additional content, a challenge to push you further, or encouragement to keep you motivated, the system makes learning feel unique and supportive all at the right time.
Pros and Cons of Adaptive Learning
Pros of Adaptive Learning:
Personalized Recommendations: delivers customized suggestions for learning materials and activities that align with each learner’s unique requirements.
Focused Skill Improvement: helps learners pinpoint specific skills and areas for improvement, helping learners progress efficiently.
Enhanced Engagement: compared to traditional learning methods, the system creates a more interactive and dynamic experience for learners.
Cons of Adaptive Learning:
Data-Intensive Requirements: platforms rely heavily on data collection and analysis, which tends to be complex and resource-intensive.
High Development Costs: the development and deployment of adaptive learning platforms often require heavy financial and technological investments.
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What Is Personalized Learning Definition?
Personalized learning is an educational approach that focuses on the unique requirements, interests, and goals of each learner. Unlike adaptive learning, where algorithms adjust the deliverables and contents, personalized learning gives each individual a more active role in shaping their learning journey and progress. Learners have the freedom on what, how, and when they learn, tailoring the experience to align with their personal interests and learning objectives. This approach enforces self-directed learning and flexibility, ensuring the learning experience is customized to meet each person’s unique preferences and needs.
How Personalized Learning Works?
Personalized learning adapts education to the specific needs, goals, and preferences of each learner. While there are multiple ways to customize learning programs, certain foundational elements are essential in creating an effective personalized learning experience:
Learner Profiles
The main foundational element of personalized learning is the creation of a detailed learner profile. These profiles capture critical information such as the learner’s background, preferences, goals, and assessment results. By leveraging these insights, platforms can provide targeted support and suggestions throughout the learner’s journey, ensuring that each goals are met.Customized Learning Paths
Personalized learning's main goal relies on individual learning paths that guide learners through unique activities and milestones. These paths are customized to each learner’s goals and starting points, offering a clear and concise path toward success. For instance, role-based training can fast-track new hires and align their activities with that of the organization.Competency-Based Progression
Unlike traditional learning activities where adhering to a fixed schedule is required, personalized learning grants learners the freedom to advance based on their preference and their mastery of specific skills and knowledge. Regular assessments are provided to determine readiness to advance, helping learners avoid information overload and focus.Data-Driven Instruction
Data plays an important role as the building block of personalized learning. insights acquired from analyzing assessments, evaluations, and screening allow Learning and Development(L&D) teams to pinpoint areas where learners need more or less support and focus. This approach ensures that each learning path is continuously refined and relevant to fit individuals evolving needs, reducing redundancies.Flexible Learning Environments
Creating or gaining access to flexible learning environments is essential for personalized learning. Whether online, in person, or both, these spaces allow learners the freedom to engage with content in a comfortable and stress-free approach, minimizing distractions and promoting focus and productivity. The flexibility also empowers learners to take command of their education, going forward at a suitable pace..
Pros and Cons of Personalized Learning
Pros of Personalized Learning:
Improve Motivation and Engagement: personalized learning keeps education relevant and keeps learners motivated and engaged by allowing them to align learning with goals and interests.
Flexibility and Adaptability: learners are allowed to progress at their own pace and preference, promoting a more accommodating and personalized experience.
Skill Development: personalized learning promotes the growth of essential learning skills such as creativity, critical thinking, and problem-solving by putting the learner in front of the wheels of their learning experience.
Cons of Personalized Learning:
Implementation Challenges: executing this approach in large groups or environments with limited resources can be excruciating and complex.
Resource-Intensive: this learning approach requires a substantial amount of complex resources necessary for planning and preparation to ensure learners gain the right support to achieve their goals.
The Differences Between Adaptive Learning and Personalized Learning
While adaptive and personalized learning share similarities, they have key differences that set them apart.
The main notable difference is the learner's role in shaping their learning experience. In adaptive learning, the learner’s role is minimal as the system automatically adjusts contents to meet the learner’s needs and goals by using algorithms to analyze data on the learner’s strengths and weaknesses and providing recommendations and materials based on these analyses. In personalized learning, the learner takes charge of actively designing their learning journey based on their goals and preferences.
Another key difference lies in the use of data and analytics. Adaptive learning relies heavily on data-driven algorithms to track performance and progress, making continuous adjustments to the learning experience. Personalized learning, on the other hand, is more dependent on learners' inputs, using feedback and the learner’s choice to make adjustments and guide the learning experience, with less dependence on complex analysis.
Gain the Best of Both Worlds?
Curiously presents a new perspective to look at personalized learning and adaptive learning, with generative AI. It’s like having a guide that adjusts to every learner’s needs while still letting them choose their own path.
Smarter Support with AI: Curiously’s AI-driven agents adapt in real-time, helping learners at their own pace with tailored recommendations. It’s like having a personal coach that’s always ready to step in when needed.
Learning, Your Way: With Curiously, learners stay in control. They can explore topics that interest them, dive into content at their speed, and shape their learning journey, while still having the structure and guidance of smart AI tools.
Made Just for You: You get to design the experience—customizing everything from the tone of your knowledge agent to how it interacts with your audience. It’s not just smart; it’s personal, and it reflects your unique voice and goals.
The Perfect Balance: Curiously combines the precision of adaptive technology with the flexibility of personalized learning, making it easier than ever to engage learners while keeping things dynamic and approachable.
Whether you’re an educator, trainer, or expert looking to share your knowledge, Curiously helps you create a learning experience that’s as unique as your audience
