The standard LMS offers a one-size-fits-all learning program. Its AI peer analyzes the initial level of knowledge, identifies gaps, and compiles an individual training program.
The global market for digital education is going to reach $400 billion in 2026, as statistics show. It is twice as much as it was in 2019. $18 billion of the figure is taken by learning management systems (LMS). Both educational institutions and businesses are currently benefiting from AI in education.
What is an AI LMS?
LMS stands for learning management system. AI-powered technologies allow gathering information about each learner, such as their skills, learning speed, preferences, and performance. The algorithm uses this data to create personalized learning paths. As a result, learners receive a program tailored to their needs, goals, and priorities. For the business, the main advantage of applying LMS lies in increasing the competence level of the employees. It is cheaper to educate the staff than to hire new experts. Besides, it is possible to fit the learning path to trainees’ behavior patterns and requests.
What are the differences between an AI LMS and a standard LMS?
Experts often refer to AI LMS as a learning experience platform (LXP). We prefer to call it AI LMS to avoid confusion.
- The standard LMS offers a one-size-fits-all learning program. Its AI peer analyzes the initial level of knowledge, identifies gaps, and compiles an individual training program.
- Learners of the traditional LMS receive feedback from human curators. Therefore, they can only communicate with their teachers during the latter’s working hours. The AI system provides virtual tutors that are available 24 hours a day.
- With a standard LMS, people perform the administrative work of compiling the training course, selecting materials, and assessing learners. It takes a lot of time and effort. An AI-powered LMS automates all the routine tasks. Machine learning algorithms explore the input data and develop personalized learning strategies.
How can AI be used in LMS?
Big companies with hundreds of employees prefer to cover several goals with one AI LMS. For instance, the Belitsoft company has developed a customized AI LMS for a design corporation. We managed to identify their employees’ skill gaps, create individual learning paths for them with automatic updates of the content, and assess their performance in real-time. If I were asked to name the aims that AI LMS can reach, I would group them in the following way:
Placement tests
Before starting the education process, students usually undergo placement tests that include several questions. Generally, those tests correspond to some particular level of proficiency. Students take on a certain level, depending on how many questions they answered correctly. With AI tools, every next question is selected based on a preceding answer. If a learner answers correctly, the system chooses a more difficult question. As a result, the LMS sees each student’s gaps in knowledge and decides on the priorities for the learning process. Human trainers can also monitor the results if they curate the course.
Personalized learning paths
After an AI-powered placement test, learners receive their score, which serves as a starting point for their training. When they finish the course, they can compare the initial result with the outcome and assess progress. The system sees the gaps in the skills and recommends certain courses to cover those gaps. For example, if an employee wants to change a position, their skills are mapped to the competency matrix of the selected vacancy. The algorithms grade a candidate and suggest courses for them to suit it. After the learning process, the system evaluates the results and sends the shortlisted candidates to the department heads.
Assessment and recommendations
Assessment is essential not only for the learners themselves but also for the CEOs to understand if they invest in the right solutions and how high the ROI is. AI algorithms monitor the results of the tests, the percentage of missed assignments, and the speed of passing courses. After that, the system might calculate average benchmarks for the learning performance. The data might later be used for predictive analytics, indicating the possibility of an employee successfully passing a definite course. High training results lead to increased motivation and better staff retention. AI-powered assessment guarantees an unbiased approach to employee evaluation.
If the assessment grade is insufficient, a learner might receive further recommendations. The micro-learning approach helps cover missed skills faster and more productively. This approach divides long courses into short modules devoted to particular topics, allowing learners to choose the content with the highest relevance. Short pieces of information do not require strong intellectual efforts and are better for memorizing. Therefore, students easily fit the learning process into their daily routine.
How do you get the most out of AI tools for educating staff?
McKinsey reported on how the world’s school systems can benefit from the experiences of countries with the most successful educational systems. I believe businesses can also apply the same expertise while training their staff.
- Introducing AI technologies should not be an aim but a tool for achieving more general goals. Companies should thoroughly analyze what they expect to improve with better-qualified employees and what the requirements for educating the staff are. Managers should systematically assess the results and use the mentoring methods that work best.
- A chosen strategy for implementing AI tools in training should be transparent to all stakeholders. Mentors, coaches, employees, and business leaders should understand their goals and what is currently being performed within a company to achieve them.
- Regular measurement of the outcomes demonstrates the efficiency of the chosen strategy. The results of the students and their feedback can reveal important insights about the success of the learning path, methods of teaching, and terms.
Final thoughts
After identifying the necessity of upskilling or reskilling employees with eLearning software, it is important to design a proper strategy. Companies may choose to:
- Integrate an AI add-on to a current corporate LMS.
- Purchase a ready-made solution.
- Develop and tailor an AI LMS to the requirements of your particular organization.
Regardless of your choice, AI tools require regular training of their large language models (LLMs) to perform their features flawlessly. Therefore, your eLearning tools will guarantee relevant output data and be aware of trends.
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