Disha Gupta
To many employees, the words “workplace training” can bring unpleasant feelings like anxiety or even annoyance. Employees who are used to traditional training methods often associate training with having more work and less time for their regular duties.
Fortunately for organizations and the employees who work for them, technological improvements have brought about new approaches to learning and development (L&D).
One such approach is adaptive learning, which is all about designing learning experiences to fit individual team members’ learning styles and needs. Adaptive learning technologies leverage artificial intelligence (AI), learner behavior, and big data to apply this approach to digital workplace learning initiatives.
What Is an Adaptive Learning Platform?
An adaptive learning platform, such as learning portals and learning management systems, is software businesses use to facilitate employee learning and development. The “adaptive” aspect comes from artificial intelligence, which it uses to build individualized learning experiences based on each learner’s unique abilities and needs. This allows L&D teams to keep learners engaged throughout their learning journeys and track success.
These platforms allow L&D teams to create, curate, and disseminate digital learning experiences while tracking progress and efficacy. Adaptive learning programs use AI to tailor these learning experiences to the specific needs of individual learners and keep them engaged throughout the process.
How Does Adaptive Learning Technologies Work?
To understand how adaptive learning platforms deliver personalized experiences and adapt lessons on the fly, you must first understand adaptivity factors, input types, and experiences outputs:
Adaptivity factors
There are different ways to review learner behaviors and performance to personalize training courses appropriately, called adaptivity factors.
Adaptivity factors are what modifies a learning experience.
Adaptivity factors include employee performance, level of knowledge (prior or gained), content preferences, demographics, and other data sources.
- Learner profile and preferences: The learner profile captures essential information about the learner, including their background, preferences, demographics, learning style, and other data points. This profile forms the foundation for personalized instruction and content adaptation. By analyzing the learner profile, adaptive learning systems can identify individual strengths, weaknesses, and knowledge gaps, allowing for tailored learning experiences that meet the specific needs of each learner.
- Performance: Learner performance is how well an individual understands a concept. By continuously monitoring and analyzing learner performance data, adaptive learning systems can assess the learner’s level of understanding, identify areas of strength and weakness, and adapt the learning experience accordingly. If the learner demonstrates proficiency in a particular area, the system can provide more advanced or challenging content to further enhance their skills. Conversely, if the learner struggles with certain concepts, the system can offer additional support or alternative explanations to address specific skill gaps.
- Behaviors: Learner behavior provides insights into the learner’s actions, interactions, and engagement patterns throughout the learning process. By analyzing learner behavior, adaptive learning systems understand how learners navigate the content, their preferred learning styles, and their levels of motivation and engagement. This information enables the system to adapt the learning experience by providing targeted recommendations, personalized feedback, and content that aligns with the learner’s behavioral preferences. For example, if a learner tends to interact more with visual elements, the system can prioritize visual resources or multimedia content.
Adaptable types
Adaptivity factors then trigger unique responses using adaptivity types.
Based on what’s happened in a learner’s journey, what is the next action? Do you move them to the next planned lesson, modify the previous lesson and send them back through that path, or entirely reroute their learning pathway based on what has happened so far in their journey?
Here are two examples of how learning experiences can adapt based on learner adaptivity factors:
- Real-time feedback: As learners engage with learning activities or assessments, adaptive learning systems generate real-time feedback based on their responses, progress, and performance. This feedback is personalized, addresses learner’s strengths and weaknesses, and offers suggestions for improvement. Augmented with post-training surveys, real-time feedback enhances learner engagement, supports self-regulated learning, ultimately facilitating effective learning experiences.
- Different learning pathways: Adaptivity factors help recognize that learners have diverse backgrounds, preferences, and learning styles. And adaptive learning systems provide multiple learning pathways to accommodate these individual differences. Learners can choose from various paths that align with their interests, goals, or preferred modes of learning. These pathways may vary in content, format, or sequencing, allowing learners to navigate through the material at their own pace and in a way that resonates with their unique learning needs.
Types of adaptive learning experiences
Adaptive learning in nature is contextual to the learner, based on the adaptivity factors that make up their learner profile. Adaptive learning can be defined differently depending on your solution to deliver adaptable experiences and your learners’ contextual needs.
However, three main types of adaptive learning experiences can be delivered:
- Adaptive content: Adaptive content provides learners with contextual feedback based on their input. For example, if a learner answers a question, adaptive content can provide additional learning with tooltips or additional resources to further support the learner instead of simply marking an answer as correct or incorrect with no additional explanation.
- Adaptive sequence: Adaptive sequencing continuously collects and analyzes learner data and automatically adapts the content learners see next. An example may be if a learner already has a foundational set of skills in a subject, and the adapted learning platform recognizes this and skips the learner to an advanced step in the experience.
- Adaptive assessment: Adaptive assessments change the next question a learner sees based on their previous behavior or input. For example, if a learner incorrectly answers a question, you can present them with a similarly worded question. You can also increase the difficulty of questions if your learners have correctly answered a series of questions.
Benefits of Adaptive Learning Platforms
The application of AI to digital learning platforms supercharges all the benefits of more traditional L&D platforms:
1. Personalized learning paths
Each employee has unique learning styles, needs, and experience. The level of customization that is possible with AI-based adaptive learning platforms makes it possible to create personalized corporate learning experiences that precisely match individual learners’ previous experiences, learning styles, strengths, and pain points to build a more effective strategy for learning and development.
These unique learning paths are often presented to learners visually, reinforcing their accomplishments and keeping them mindful of what’s coming next.
2. Enhanced engagement and motivation
Moving away from pre-fab, generic training approaches toward curated lessons that are truly worth employees’ time and energy demonstrates to employees that organizational leaders value the growth and experience of individual employees.
By eliminating irrelevant and redundant content from learning experiences, AI-based adaptive learning platforms can provide more engaging, enriching learning materials that keep employees optimistic about the knowledge and skills they gain as they progress. These positive experiences translate to improvements in overall employee experience, boosting employee retention and making them eager to grow along with the organization.
3. Real-time feedback
Adaptive learning platforms provide employee learners with instantaneous, real-time feedback as they move along their learning paths. This quick turnaround gives employees clarity as they learn and confidence that they are on the right track. It also gives employees a reference point to bring to their managers for additional feedback and support.
Overall, the real-time feedback provided by adaptive learning platforms promotes a supportive and responsive learning environment that optimizes training programs and facilitates performance improvement.
4. Data-driven insights
The data collected by adaptive learning platforms are incredible tools for L&D teams. Insights derived from these data allow for creating more effective, individualized training experiences that improve learning outcomes while increasing engagement. Leaders can also use training data to more efficiently allocate training resources and eliminate inefficiencies to reduce costs in the long run.
Data-driven insights can optimize L&D programs and give an organization a competitive advantage in ever-changing markets.
7 Best Adaptive Learning Platforms
Adaptive learning platforms can be an LMS, learning portal, digital adoption platform, microlearning platform, and other L&D tools. Here are seven of the best adaptive learning platforms for corporate learning:
1. Whatfix
- Review rating: 4.6/5
- Pricing: Contact Whatfix for a quote – free trial
Whatfix is a digital adoption platform that enables adaptive learning experiences that overlay the digital workplace, providing personalized and context-sensitive guidance to users based on their specific needs and actions within an application or software.
It analyzes user interactions in real time and delivers relevant, just-in-time information, walkthroughs, and tips to guide users through complex processes or tasks. This adaptability ensures that users receive the right level of support precisely when they need it, making the learning process more efficient and effective.
Whatfix also adapts to users’ proficiency levels, allowing beginners to access fundamental guidance while offering more advanced assistance to experienced users. This personalized approach enhances user engagement, reduces frustration, and accelerates the learning curve, ultimately improving user proficiency and productivity.
Create personalized learning & training flows for your enterprise apps with Whatfix
2. EdApp
- Review rating: 4.7/5
- Pricing: self-authored plan is free
Edapp is a learning portal that incorporates AI to personalize learning experiences and track progress from both digital and in-person training initiatives. It also provides course authors with AI course-creation tools to alleviate writer’s block and reduce research time.
EdApp offers a library of customizable, ready-made training courses as well as templates that allow L&D team members to build courses in minutes. This solution also includes a Brain Boost feature, a spaced learning tool that helps learners retain new information by delivering automatic, personalized follow-up tests.
3. 360Learning
- Review rating: 4.6/5
- Pricing: Team plan starts at $8 per user per month
360Learning is an adaptive learning platform that focuses on collaborative learning to help organizations upskill teams quickly and promote continuous learning from within. Through collaborative learning, employees grow by teaching and learning from one another. By incorporating AI-based course creation tools, 360Learning allows employee experts to author and collaborate on training dynamic courses for their peers.
This solution combines the features of an automation-centered learning management platform with a collaborative learning experience platform into a powerful hub for adaptive corporate learning. Its AI features streamline course creation, generate custom courses for individual employees, and provide useful recommendations for employees who want to extend their learning journey.
4. Adaptemy
- Review rating:
- Pricing: contact for a quote
This aptly named learning platform allows L&D teams to create powerful learning experiences
Adaptemy provides adaptive learning solutions for employees by creating powerful courses that organizations can add to their existing learning management system. This solution allows organizations to integrate learning experiences with their current LMS and build custom courses with intuitive curriculum mapping and visually appealing UI and UX designs.
Adaptemy’s pre-built adaptive learning strategies include adaptive assessments, guided learning reinforcement, and detailed analytic tools to help L&D teams cater learning experiences directly to the needs of employee learners.
5. Knewton
- Review rating: 4.6/5
- Pricing: starts at $10.95 per person per month
Knewton alta is an adaptive learning platform that provides learners with personalized learning experiences focused on math, science, and economics. This solution will be most effective for companies in sectors like engineering or science manufacturing, where employees need to brush up on skills they may have learned at University.
Knewton Alta’s adaptive learning technology adjusts learning experiences based on learner proficiency levels with every interaction, providing employees with a personalized path to continent mastery. This platform provides personalized study plans, immediate feedback, and answer explanations to reinforce key learnings and fill knowledge gaps, empowering learners to grow from their missteps and enter a growth-based continuous learning mindset.
6. Realizeit
- Review rating: Not available
- Pricing: Not available
RealizeIT is an adaptive training platform designed to facilitate employee onboarding as well as reskilling employees to improve their day-to-day job proficiencies and ensure compliance with organizational and industry standards. This platform also includes solutions for product training as well as cross-training employees to help organizations become agile and adaptable in constantly evolving industries.
This solution provides journey mapping, and personalized pathway features that match up well with blended learning approaches to optimize the learning experience for employees. It also includes detailed knowledge progression measurement tools and instant feedback to keep employee learners engaged, confident, and immersed in a culture of continuous learning.
7. Pearson Interactive Labs
- Review rating: not available
- Pricing: Contact Pearson for pricing information
Pearson Interactive Labs is another platform focused on scientific learning, specifically made to replace or supplement in-person biology and microbiology labs. This solution engages learners in real-world scenarios made adaptive by immediate feedback and flexible course formats.
Subjects offered by Pearson Interactive labs include the Scientific Method, genetics, and microscopy for microbiology. By providing a virtual way for science professionals to learn by doing, this platform can help L&D teams ensure that employees are masters of their subject area.
Factors to Consider While Choosing an Adaptive Learning Platform
While there are a variety of quality adaptive learning platforms to choose from, picking the right solution for your organization can feel daunting. Consider the following factors to select the platform that fits best for your business L&D needs:
- Content relevancy and diversity: Many adaptive learning platforms offer pre-made content libraries and a variety of lesson formats. Review the particular features of different platforms to determine which one aligns best with your organization’s learning objectives.
- Adaptability and customization: If your company’s L&D needs are unique to a certain industry or internal processes, you might need a platform that offers robust customization features. If this is the case, choose a platform that allows L&D teams to import existing training materials to be adapted or to build training content from scratch.
- Integrations: Check whether the solutions you are choosing between are compatible with other learning management systems or other commonly used software. You may also want to choose platforms that can lie on top of software used by your organization for in-app training options.
- User-friendly interface: To provide optimal learning experiences, the adaptive learning platform you choose should be easy and intuitive to use. Learners should not have to spend as much time learning the training software as the content they are being trained on in the first place. If possible, arrange for your team to try out software demos to determine whether your platform choice is user-friendly enough for your organization.
- Data analytics and insights: One of the most important aspects of L&D initiatives is the utilization of data analytics to improve training initiatives continuously. Ensure that the adaptive learning platform chosen for your organization has all the necessary analytic features or that it can integrate with other analytic systems used by your company.
- Scalability and technical support: As your organization grows, the needs of your learning and development team may multiply. Choose an adaptive learning platform that can scale to accommodate a variety of user levels and training types as necessary.
Implement Adaptive Learning with Whatfix Digital Adoption Platform
Whatfix is a digital adoption platform (DAP) that helps organizations provide personalized training experiences for employees by giving them the guidance they need right when they need it. With adaptive learning capabilities, content customization, and personalized learning paths, Whatfix can serve as an effective in-app adaptive learning platform.
Software clicks better with Whatfix's digital adoption platform
Enable your employees with in-app guidance, self-help support, process changes alerts, pop-ups for department announcements, and field validations to improve data accuracy.
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Whatfix's digital adoption platform empowers your employees, customers, and end-users with in-app guidance, reinforcement learning, and contextual self-help support to find maximum value from software.
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