AI-Turbocharged LXP (with AI Quiz Generator and AI Course Creator)

Based on 15+ years of expertise in eLearning software development, we will analyze your business needs in-depth and recommend the system that will resolve all the challenges your company faces, whether it is LMS development, LXP development or even skills management software implementation. Get a free quote! What is LXP? LXP stands for Learning Experience Platform. As software for professional learning, LXP is a solution to the problem of the up-to-date content shortage typical for an LMS. There are a lot of high-quality learning libraries with content that is automatically updating. It's more cost-efficient just to integrate your e-learning platform with this ready-to-use content than to deal with old content that you need to import manually into your LMS. With LXP functionality both options are possible: you can import some courses manually, as well as integrate with courses providers via API. LXP provides high engagement. Compared with a strict predefined learning path in LMS, LXP's learners build their own path that gives them more control and more productivity, both in acquiring new skills and in upgrading their qualifications. Artificial Intelligence behind LXP accelerates the adoption of new knowledge. AI-driven algorithms recommend to the learner personally structured content that is exactly what the learner needs exactly at this time. Neither more nor less. Some experts compare LXP with Netflix in eLearning due to its consumer-oriented methodology and intelligent content recommendation. Here is how its interface usually looks like (example of Linkedin LXP). linkedin.com LMS vs LXP: Key Differences LMS development LXP development Learner’s course is predefined and scheduled. Learners choose content based on recommendations and their own interests. Learners follow predefined curricula. The learning path is laid out before them and they just need to complete each milestone to get to the finish. Learning paths are self-directed and built when learners pick what they want to learn about. Focus on corporate learning for onboarding, compliance training, and licensing. Perfect fit for mandatory training when learners must complete specific, predetermined steps. Focus on user experience and continuous professional development with company purpose to grow highly performing professionals. Administrator-centric system when an admin (HR, leadership member, trainer) creates and delivers formal training to workforces. Learner-centric system when learners choose content based on their interests. Based on an internal company course catalog. Based on materials from internal knowledge base, external resources, and user-generated content. The line between those two classes of software is blurry and will depend on the functionality of a given system. For example, many LMS’, including Docebo and D2L, have addons that let the system perform as an LXP. Any educational software that supports the LTI standard can stream third-party learning content. On the other hand, features like learning paths and social integration are pretty much industry standard for an LMS. So companies may have an LXP, an LMS, or both depending on their goals and employees’ training approach. Use the LXP and LMS in tandem to: launch and track LMS-created course in LXP; augment your LMS-based training with a vast content library that LXP provides; allow admins to easily manage all corporate learning processes; get all analytical data from different platforms in one place. Have an LMS and cannot decide if you need to switch to LXP or just add more functionality to upgrade your LMS to get all innovative features? Contact our eLearning expert to get professional advice based on your situation. How LXP resolves business challenges Learning Experience Platforms appeared as a response to new business challenges that stakeholders faced and couldn’t resolve without an innovative approach. Among the major business challenges that companies face now there are: the need for continuous upskilling and reskilling of the workforce; preventing talent shortage; organizing internal mobility; timely building of employees’ in-demand and future-proof skills; leadership retiring and preparation of the next generation; avoiding employees’ burnout and increasing engagement. To address the mentioned business challenges, the learning content within the LXP must be highly relevant and just-in-time, which is achieved through highly personalized recommendations.  Personalized recommendations allow learners to choose the learning path that will mostly favor their skill-building and keep up their engagement rates. Let’s turn to Josh Bersin, the expert researcher in the topics of corporate HR, talent management, and technology. He suggests that LXPs recommend content based on the following approaches: 1. Skills-based recommendations. An LXP associates a job position with a certain skill set. So creating a profile in an LXP requires mentioning your actual skills.  When employees decide to upskill or reskill they choose the desired position. The LXP detects the skills they are supposed to possess.  Then the system matches these skills with the available content. The content for learning will be recommended based on the gap between the actual skills and the skills required for the desired job position. degreed.com 2. AI-based recommendations. An AI engine collects data about learners, their performance, behavior, and learning paths. Imagine you give an AI engine 1000 learners’ profiles. AI labels all the data from the profiles (skills, expertise) and the requested content (course categories, difficulty level).  Then the engine finds patterns that allow making automatic predictions about the interest of learners and the content relevance. Essentially, the underlying task of Artificial Intelligence is to predict the engagement of learners, given contextual information about the learners and courses. valamis.com 3. Usage data-based recommendations. The LXP aggregates massive amounts of the data of other learners with similar profile information to use as a basis for your content recommendations.  Such an approach has its bottleneck. If some course is widely recommended, it outcompetes other content that could be more relevant and valuable. And the LXP developers are working to resolve the issue. Some LXPs also let learners segment into communities. Thanks to this, the platform can recommend the most relevant and popular content within the community.  linkedin.com 4. Recommendations based on learner’s personal choice. To find out what content to recommend you can directly ask the learner. This experience is similar to the first launch of Spotify when you need to choose your preferences.  In the case of LXPs, thanks to defining your interests and goals, the system gets relevant information about your learning preferences.  Except for the content recommendation directly, this approach can be used for the best learning process adjustment. So the system may ask you about your level of expertise and your preferable way of learning (e.g., through articles, podcasts, or videos). learn.filtered.com Have you thought about deploying one of these innovative content recommendation approaches into your corporate training? Discuss all the options with our eLearning expert. Key LXP features The first step to deploying an LXP in your company is to understand what your employees expect from the program. Based on this information, you can decide what LXP functionality would be the best fit.  However, there are the key LXP features every solid platform must have. Highly intuitive individualized interface The interfaces of LXPs are much like Netflix and Google have. They reveal past interactions, learning paths, preferences, and recommendations. The user interface is responsive, individualized, and ubiquitous in delivery. It provides highly immersive learning experiences to users of the platform. edcast.com Social learning This includes inbuilt functionality for communication and knowledge exchange (e.g. community-recommended or user-generated content); Many learning experience platforms have rating systems, public comments, and sharing options like in social media networks. Moreover, learners can showcase their expertise in the topic to their peers. thrivelearning.com Microlearning LXPs include brief learning pieces that answer topic questions precisely (e.g. “How to create a diagram in Google Doc”).  Such bite-sized learning allows employees to learn within the working environment, easily switching to the LXP on the desktop or a mobile device.  The microlearning method supports different types of learning, including blended learning, group-based learning, problem-based learning, ILT.  linkedin.com Gamification in LXP Gamification is using game-design elements in a non-game environment. For example, a system of points, levels, and badges awarded for diligent study and high test grades is gamification. Gamification is used much more often, as it requires less investment to implement. Yet it has proven its effectiveness. Here’s what it brings: Better learning outcomes. Studies show that gamified software is more effective at teaching than its non-gamified counterparts. Improved motivation. Game elements make people willingly spend more time studying, thus increasing the overall effectiveness of learning. Fun. People who participate in gamified learning as part of their work report increased enjoyment and loyalty towards their company. For more information on gamification, its benefits, and risks see our article. And for examples of this approach in corporate training, read another one. Don’t confuse gamification with game-based learning. Game-based learning, on the other hand, is using play to teach skills or transfer knowledge. Solving equations quickly to make your racecar run faster than the opponents is an example of game-based learning. servicetick.com Extensive integration capabilities Being a learning gateway, an LXP is usually just a part of a corporate L&D and HR system. It integrates with many other types of business software, including CRM, HRM, ERP, LRS, etc. It permits the platform to collect the data it needs to curate content more effectively and to get valuable data for improving employee management. For example, an LXP integrates with an LRS to deliver trends and patterns through data analytics. The purpose is to help in personalizing learning even further. In-Built Artificial Intelligence A key feature of the LXP is the Artificial Intelligence engine for content recommendation and personalization of a learning path. The platform automatically recommends relevant learning materials based on a learner’s job position, experience level, previously completed courses, and other relevant information.  The use of AI includes the recommendation of lessons from third parties and “non-learning” systems such as YouTube. Artificial Intelligence also performs a prediction function.  Thanks to the integration with HR, LRS, CRM platforms, AI collects data and identifies trends and patterns in the on-demand skills and jobs So based on these data, business stakeholders can make informed training and learning decisions. Advanced analytics with xAPI (SCORM, cmi5, LTI) One of the primary goals of an LXP as a basis of a corporate learning culture is to connect learning with on-the-job performance. To perform it successfully, LXPs have adopted advanced standards, such as experience API (xAPI), cmi5, LTI, or SCORM (as the one of the previous generation but still highly in use). For example, it allows tracking how learners succeed in the course, what certificates they get, what skills they master, which courses are the most relevant and effective, etc. All this information helps business stakeholders understand how the learning process influences the work that people perform and whether your training is truly effective. Seamless access to multiple devices  It’s critical to give learners the ability to access content anytime and anywhere so that they could start a desktop course and be able to complete it later on a mobile device.  For that, your content must be available on any device, including desktop, native mobile, and progressive web apps.  edcast.com How Belitsoft Can Help Being in the eLearning market for more than 15 years and having delivered several LXPs, we know what we are talking about. Here’s how we can help you: Custom LXP development. If none of the boxed solutions fit your needs we can make you a new one from scratch. LXP customization. If you need to make a few tweaks to an existing open-source system (whether it is changing a logo and a color scheme or adding new features and modules) we can do that. LXP consulting. We can discuss your needs in depth and recommend the system that would be the most beneficial for your company. Content development. Should also need to create lessons and quizzes or repackage the existing ones in a different format, we can do it for you. GET A FREE QUOTE Frequently Asked Questions

Want to get one of the AI-powered tools in your eLearning product or create a personalized learning platform using AI from scratch? Our LMS development company will implement the features that will bring you the maximum benefit. Let's talk! Example of AI-based Personalization in Corporate Learning The importance of effective workforce training is becoming critical. To cope with this issue, the forward-looking leaders already started to adopt progressive tools, including AI in talent management and continuous education. The management of the US-based air medical transport company (Air Methods, a 2,800-person helicopter company in Englewood, Colorado), understood the importance of well-organized continuous education to train pilots. When using traditional webinar-based training, every employee used to receive the same course, regardless of their learning speed and current skills. Such a method required a lot of time, drew little engagement, and didn’t motivate pilots to grow. So the company adopted an aviation training system built on Artificial Intelligence. Process of Implementing Personalized Learning Using AI The system tested every learner using short quizzes and games. Then AI adapted the learning path to each learner’s knowledge of a topic based on the test results.  If a pilot struggled with a certain topic, the AI LMS repeated it by presenting the information in a new way. After completing a section, every pilot was retested and progressed to the next module. Results after Implementing Personalized Learning Using AI According to the company leaders, the implementation of AI personalized learning in corporate training not only boosted the effectiveness of the training course but also helped to attract talent. The company could also significantly reduce their training and onboarding costs by cutting half the number of personal instructor-led training classes together with the duration of their onboarding program from 10 to 5 days.  Belitsoft has experience in developing personalized eLearning solutions for Healthcare, Aviation, Finance, and other important industries. And we know what tools and features can become your competitive advantage. Let's discuss your case! What is Personalized eLearning? Personalized learning is an educational approach to address the individual learning needs and interests of each learner. The goal of personalized online learning is faster knowledge acquisition and better knowledge retention. According to the L&D Global Sentiment Survey, the two hottest topics in online education now are personalization and Artificial Intelligence. But why? By personalizing your learning content with the help of AI, you make the learning process faster and more effective.  In its turn, this leads to shorter training time, reduced training costs, and higher productivity of the trained workforce.  Features of Personalized Learning Software using AI The major components of the personalized learning platforms that can be customized for each learner are: Relevant information. Using only relevant content that is based on learner’s interests leads to faster and better results. Preferred eLearning content types. By detecting the preferences of each learner, the system builds a personalized path majorly using preferred content types (video, audio, text, etc.) to increase engagement. Individual pace of learning. Thanks to adjusting the learning pace, every learner gets the necessary amount of time needed to master every topic or skill. Corresponding difficulty level. Using the right tools, especially an AI-powered skill map, the system more quickly identifies the competency level and learning gaps that impede progress, allowing learners to achieve the desired results faster. Immediate feedback. Thanks to more frequent and immediate feedback, learners can understand their performance and progress in real-time. It happens through formative assessments, quizzes, and knowledge checks. Get all benefits of customized e-learning. Our experts will consult you about selecting the best way to personalize your training course. Benefits of AI in Personalized Learning for Any Business With more companies facing the challenge of upskilling and reskilling or arranging an effective professional education and licensing for their workforce, personalized learning has become a proven method that can bring success to businesses in a scalable manner. And the most obvious benefits that using personalized learning software brings to business are: Speed up the professional education process and increase its quality. Licensing and professional education require a lot of time, which negatively affects the working process.  But personalized learning makes learning targeted. Learners receive tailor-made information they require to fill gaps and achieve learning goals quickly. Also, the information is usually bite-sized, which makes classes short and increases knowledge retention. Such an approach encourages employees to self-direct their training and favors creating a culture of continuous learning within a company. Boost engagement and motivation that leads to higher productivity. When adult learners can control and self-direct the learning process, they are likely to feel more motivated.  Learners pick up lessons skipping unwanted information that doesn’t correspond to their role, need, experience, or skill level. Besides, they take a proactive role in their education and study at a comfortable pace.  That’s why personalized learning is a good choice to introduce professional learning on a regular basis. Reduce training hours and boost ROI. Profit margin growth is the result of higher productivity and shorter training time.  Personalization usually implies a bite-sized learning (microlearning) method. So learning at the working place becomes shorter and quicker. It equates to less learning time and fewer training payroll hours. Besides, personalized learning information is consumed faster and with better results. So employees spend less time on training and demonstrate equal or even better outcomes. Want to increase revenue, boost productivity, and streamline internal mobility within a company? Personalize your LMS or LXP with the help of AI tools. Or create an AI-powered platform from scratch. We'll recommend the tools and features that will bring you the maximum benefit. Let's talk! How to Get Started with AI Personalized Learning in a Company? Deep personalization that includes key aspects of training is performed with the help of algorithms. And even though traditional algorithms can perform this task, their possibilities are limited.  Only AI-powered systems can provide a high level of personalization that improves over time. The reason is the AI engine constantly refines recommendations without the intervention of developers or admins by updating themselves based on previous outcomes. Personalized learning with AI encompasses all the core aspects of online training: personalized learning path; relevant content based on knowledge level, skills, interests, and goals; automated knowledge checks; prediction of knowledge gaps; proactive learners’ support; tutoring, etc. Here is an example of AI-powered training software with individual learning paths and personally recommended content. linkedin.com Setting up personalized learning with an AI engine requires the following steps: Step 1. Create a skill matrix. To determine the learner's knowledge and then build a learning profile, start with creating a skill matrix. For this, skills should be described by humans once. It can be done by analyzing employees’ CVs with the help of text analytics. Or employees can fill in a simple form with skills in rows and knowledge levels in columns. And then these data will be parsed by a machine. As a result, every learner will have an individual profile that reveals their current knowledge level and skills. Step 2. Aggregate data about the learning background. However, knowing only skills will not give a complete picture. Artificial Intelligence captures, gathers, and analyzes employees’ learning backgrounds from different sources within the company. This can be easily performed with the help of xAPI. With xAPI you will collect information about employees' previous and current learning experience from LMS, LXP, TMS, HRIS, etc with a great degree of detail. Step 3. Use the AI engine to find patterns. Having aggregated all the data, the AI spots trends and builds patterns for each learner.  These data give admins or an L&D team valuable insights about learners’ performance and educational preferences. In the next step, this information will be used to suggest the most relevant content. Step 4. Build a training course based on AI-driven recommendations. By identifying learning trends, the system can provide learners with study materials in the formats and of the difficulty level that best suit their learning preferences and skills.  For example, AI informs an admin that a certain employee uses short videos as the major content resource and tends to watch about “Technical SEO”. Based on this data, the recommendation engine starts suggesting this learner more videos instead of a textual format, all around the preferred topic. Thanks to getting highly relevant content in a preferred format, more learners succeed in the training course. Step 5. Measure and assess regularly to adjust the course. Learners start training using an LMS or LXP. The performance of each learner is measured and assessed regularly.  The AI engine takes the latest results of a learner and adjusts the course. And this cycle constantly repeats. Any business that implements AI in training courses gets a strategic advantage thanks to the possibility to detect missing skills in the workforce and arrange effective upskilling and reskilling to address this problem in time. 5 Pillars of Personalized Learning using AI-powered LMS/LXP AI-based knowledge checks to detect the current knowledge level and gaps. To discover a learner’s educational background and knowledge gaps, an AI-based system starts with a knowledge check. This is a test that has no predefined consequence of questions. Every next question depends on a previous learner’s answer. In the case of correct answers, the difficulty level of questions constantly grows. In the case of an incorrect answer, the difficulty level lowers.  The AI-powered LMS or LXP tests learners’ knowledge regularly to guide and adjust learning activities in time.  After understanding the baseline proficiency, the learner is given a personalized learning path corresponding to the current knowledge level. pluralsight.com AI-selected training content to address individual learning goals Artificial Intelligence tracks how a learner is performing and progressing in the course. The previous performance is also taken into consideration.  Then AI uses the gathered data to detect the level of learners’ proficiency and their interests. The next step that AI makes is finding and recommending corresponding learning materials. So the course starts from the tasks revealing the learners' knowledge level. The proper selection of the content translates into faster knowledge acquisition and higher productivity of the workforce after completing such training.  When it comes to the personalization of content types, modern LXPs and LMSs can also suggest multiple content types.  For example, some learners get information better when watching short videos. Others learn quickly through reading. So the course will be majorly built on these preferences.  linkedin.com AI-created learning path to target detected knowledge gaps After detecting your knowledge, interests, and goals as well as selecting relevant content, AI builds a non-linear learning path. Non-linear means not predefined, chosen by learners by their needs and allowing them to complete the course at their own pace.  Learners are not forced to learn what they already know. They skip certain segments of a course and start learning what they actually need.  This is a key to higher motivation and engagement. Besides, it saves a lot of valuable time that will be spent on work thanks to efficient to-the-point learning.  valamis.com AI-powered tutoring to provide proactive assistance in learning AI virtual assistants and chatbots for education now act like tutors giving proactive recommendations about learning materials and assisting during the process. They teach by simulating a human tutor like in the learning app Duolingo and can also remind learners about assignments and due dates. Another aim of AI assistants is the selection and recommendation of the right courses for learners based on the topic, skills, duration, goals, and other factors.  Besides suggesting optimal courses based on the user’s profile, it can also recommend educational information in the public domain (TED, HBR, BBC, etc) or help find a human tutor when needed. juji.io AI-enabled feedback to give a responsive assessment immediately AI algorithms guide a learner through the learning path giving an immediate responsive assessment.  For example, a learner struggles with a certain topic, there can be additional tools like pop-up hints, dictionaries, calculators, etc. Meaningful and immediate feedback helps learners understand how they are progressing, detect weak and strong points, and get information that addresses their weaknesses. An immediate machine-driven assessment also excludes a direct interaction with an admin or instructor, which represents an effective trial-and-error method of problem-solving ( eliminating the fear and hesitation of direct interaction with an instructor).