How the demand for skills is shaping the future of learning

Top trends in eLearning that are shaping the future of learning and development

As technologies, regulations and business practices continue to rapidly change, employees are required to learn new skills to effectively perform their roles.

• Gartner found nearly one in three skills needed for jobs in 2018 weren’t needed by 2023 
• According to PwC, 74% of CEOs say the lack of availability of the right skills is a problem and the demand for new skills is only growing 
• LinkedIn Learning found 76% of Gen Z believe learning is the key to a successful career.

Are you providing the right learning environment for employees to develop their knowledge and skills?

To fill skills gaps, organisations should:

• Match job roles with specific skill requirements that provide real value 
• List current employee skills in each role 
• Analyse the gaps between skill requirements and existing skills 
• Create a learning plan to upskill employees to fill the skill gaps 
• Develop a strong learning culture – give employees time to learn 
• Embrace new technologies that support skills development.

Shaping the future of learning

As the demand for new skills and competencies increases, eLearning continues to adapt with the changing trends and opportunities. We explore some of the top trends in eLearning that are shaping the future of learning and development.

Artificial intelligence and machine learning

Artificial intelligence (AI) and machine learning (ML) are two of the most disruptive and influential technologies. AI and ML enables eLearning to provide personalised, adaptive and intelligent learning experiences for learners. It can also automate and optimise various aspects of the learning process, such as content creation, delivery, assessment, feedback and analytics.

Chatbots

Conversational agents, such as chatbots, interact with learners through natural language to provide learners with instant and personalised responses, guidance and support, as well as facilitate social and collaborative learning. They’re particularly relevant for performance support.

Personalised and adaptive learning

Personalised and adaptive learning tailors learning content to an individual’s needs, preferences and goals. Data collected from learners’ interactions, behaviours and performance is used by AI and ML to create and deliver customised and relevant learning experiences for each learner.

Immersive learning

Immersive learning is a form of eLearning that uses technologies, such as virtual reality (VR), augmented reality (AR) and mixed reality (MR), to create realistic and engaging learning environments and scenarios. AI and ML can enhance immersive learning by providing learners with interactive, adaptive and intelligent feedback, guidance and support, as well as generating realistic and dynamic content, characters and situations.

Generative AI

Large language models such as ChatGPT and AI image generators such as Image Creator from Microsoft Designer, can be used by eLearning authors to speed up the content creation process, make it easier to produce new and updated content, while allowing the eLearning author to focus on elements of content creation such as media and user experiences.

Blockchain

Blockchain can store and verify data in a secure, transparent and decentralised way. It can be used in mobile learning to provide learners with verifiable and portable digital credentials, such as badges and certificates. It enables learners to showcase their learning achievements and competencies – which can be used to support promotions or new careers.

User-generated content

User-generated content (UGC) continues to empower learners to create and share their own learning content – text, images, videos or audio – and experiences, as well as to access and learn from the content and experiences of others. UGC can also foster social and collaborative learning, as well as promote learner autonomy, creativity and ownership.