AI-powered tools: what education challenges can be solved?

AI takes eLearning to a new level

Artificial intelligence (AI) is increasingly becoming one of the disruptive factors in the educational field. AI in education market expected to grow by 45.12% per year and reach $10.38 billion by 2026 . Generally speaking, eLearning makes education accessible anytime, anywhere, which has become crucial in the era of pandemic and remote working. Businesses, ed-tech start-ups, training companies, universities, schools and students – all parties benefit from many important benefits of online learning, such as reaching a wider audience online. At the same time, AI-powered tools are taking eLearning to a new level by addressing challenges that are not obvious at first glance.

Challenge: Closing skills gaps through onboarding, upskilling and reskilling

Studies show that nine in ten executives recognize or expect staff skills gaps over the next five years, and that fewer than half of them know how to overcome this challenge. 56% of respondents indicated that one of the most popular tactics for closing skills gaps is upskilling or reskilling within the organization. However, around 70% of HR professionals are dissatisfied with how their organization addresses these aspects within their internal mobility.

An AI-powered individual career path builder can help acquire the necessary skills through a learning experience platform (LXP). An employee, when looking for new opportunities, can use the tool for a clear understanding of the open positions within their organization and the skills required for each role. AI algorithms analyze an individual’s current skills, compare the skills to the job requirements, emphasize the missing ones, and advise appropriate courses to fill these skill gaps.

Challenge: Matching the right talent to the right roles, at scale

Enterprises, training companies and edtech startups are leveraging AI-powered tools to assess workforce skills, helping match the right talent to the right jobs at scale . How it works? Humans only need to describe skills once. Then the machine will analyze the data itself. An AI-powered algorithm automatically ranks each employee’s job skills, analyzing their profiles and skills matrix. Through the implementation of AI in the Learning and Development (L&D) and talent management departments, the manager will get a list of candidates with their skill level ranked. Additionally, the data will be matched to the skills the company needs.

Challenge: Ensure faster acquisition of knowledge and improve learning outcomes

Automatically creating personalized AI-powered learning paths with targeted content recommendations can help each employee or student in multiple ways. For example, once a learner passes an initial knowledge check or skills assessment, AI in the L&D sector builds a personalized learning path that starts with the subject most ready to learn.

Additionally, while going through the topic, the trainee is offered a series of questions with guidance and detailed explanations in case of incorrect answers. Thus, learners complete a certain number of subjects and pass the determined number of hours. After that, the AI ​​knowledge checker automatically re-assess learners to show the topics they have learned. Materials that a trainee did well with will go into the mastered category, and topics that they had difficulty with will return to the learning path to be reviewed again.

Challenge: measuring the effectiveness of training programs

An AI-powered learning progress tracker is able to check whether employees or students are mastering or lacking the necessary skills. This measures the impact of learning and optimizes it accordingly.

How it works? The software aggregates trainee performance data and grades from a learning management system (LMS), including overall scores and skills, missing assignments or late assignments. An AI-powered progress tracking tool analyzes each learner’s progress based on their individual activities and performance. Teachers and L&D teams see collected data in a single dashboard and get intuitive reports. Additionally, the system flags at-risk students or low-performing employees, allowing faculty and L&D managers to follow up quickly.

Challenge: predicting future learning outcomes and potential problems

The AI-powered predictive analytics tool gathers data on past and current activities. Based on the collected data, the software creates learning behavior models for each learner and projects future skills for final assessments. The system automatically generates accurate reports and sends them to educational staff so that they can uncover pitfalls in a timely manner. Through early interventions, learner success and retention rates increase.

L&D departments and educators use predictive reporting to help their employees or students improve their skills earlier in the learning cycle and fill knowledge gaps. The AI-based system could also provide alerts to notify mentors of events that may require their intervention or discussion.

In addition to the listed challenges, AI in education can solve other problems, such as increasing user retention and course completion rates in language learning, or reallocating students’ time. L&D, HR and education managers to meaningful and strategic tasks by assigning routine tasks to meaningful and strategic tasks. AI chatbots.

Conclusion

These days you can discover a billion competing products, and the lion’s share of them promise a lot but don’t deliver much. It’s crucial to understand what solution works and what doesn’t. When investing in an AI-based LMS, it is important to get proper advice from eLearning experts. This will help you understand how to integrate AI into your current LMS or perhaps create an LMS from scratch.

One of the main steps is to choose the type of eLearning software that will perfectly suit the target audience and learning objectives, like AI LMS, LXP, mobile or web app learning. Implementing AI features converts a traditional admin-centric LMS into a learner-centric LXP. The AI ​​in LXP functions as a recommendation engine, replacing a unified curriculum with personalized learning content.

The central idea of ​​eLearning mobile and web applications is to make the process available anytime and anywhere through personal devices. To get early results, test solutions that are easy to apply. Additionally, it may be more cost-effective to not only replace your existing systems with entirely new ones, but also to consider opportunities to use them in new environments.

Originally published on www.forbes.com.