Technology is transforming the learning and development (L&D) environment, creating the path for novel techniques such as personalised online learning.

It has become evident in recent years that one-size-fits-all training does not, in fact, fit every learner. As a result, businesses are increasingly relying on technology to personalise training to individual learners’ talents, requirements, and interests.

While personalised learning has numerous advantages, implementing the appropriate technology can be difficult. After all, there are hundreds of tools to pick from, each with its own set of technological needs.

With this in mind, we will look at the role of technology in implementing personalised online learning in this two-part essay.

Recognising Personalised Online Learning

Personalised online learning refers to customised online learning experiences that are personalised to the specific requirements and preferences of your individual learners.

The goal is to provide interesting training material and teaching that is tailored to your learners’ learning preferences, pace, skill gaps, existing knowledge, and interests.

There are several approaches to personalised online learning. You may utilise adaptive learning systems, gamification, and other digital technologies to engage learners in information and activities that are completely relevant to them.

The Advantages of Personalised Training

Personalization is the key to unleashing your learners’ greatest potential. You may enable individual learners to advance at their own speed and discover topics that connects with them by personalising the learning experience to their requirements.

Relevance produces results. Employees who receive personalised training remember more information and find it simpler to apply it to their jobs. As a result, job performance and efficiency may increase.

Furthermore, personalised training can increase learner engagement and motivation. Learners will be more motivated if they believe their learning experience is relevant, valuable, and pleasurable.

Above all, customised training can make your employees feel valued and supported. It sends a strong message that you care about their growth and development. As a result, greater employee retention rates and a more contented staff are possible.

Supporting Technology for Personalised Online Learning

Choosing the correct technology is critical for effectively implementing personalised learning in an online context. After all, when it comes to delivering personalised training interventions, not all tools are created equal.

LMS stands for Learning Management System

A learning management system (LMS) is a software programme that allows you to manage and distribute information and learning activities to your students. It is possibly today’s most popular personalised learning tool.

In reality, an LMS may assist you in personalising your training programme in a variety of ways. You may, for example, utilise your LMS to offer rapid feedback, send content recommendations, and provide access to relevant subject matter experts (SMEs), among other things.

Similarly, features such as gamification and social learning allow you to create personalised learning pathways that are tailored to the needs of individual learners. These learning paths lead users via a distinct level structure based on content interventions.

Learning Analytics and Data Management

To provide personalized learning experiences, it is crucial to have access to accurate and up-to-date data about your learners’ skills, performance and progress. After all, this data enables you to identify where your learners are excelling and areas where they need additional support.

While most LMSs come with extensive reporting suites, you can also choose to use learning analytics or data management tools. These tools help you to collect, process and analyze data effectively.

When choosing your tools, make sure that they allow for the collection of data from multiple sources. In addition, ensure they provide actionable insights by creating clear and concise reports.

Platforms for Adaptive Learning

To measure your learners’ progress, adaptive learning platforms employ complicated algorithms and data. The software then modifies and customises the learning experience in real time.

The platform, for example, knows how to adjust the difficulty level, pace, and material based on your learner’s present activity, training objectives and goals, and historical performance.

These platforms may optimise learning outcomes and guarantee that each student is engaged and challenged at their right level by allowing them to change material, assessments, and quick feedback.

When selecting an adaptive learning platform, it is critical to consider factors such as content quality, algorithm accuracy, and platform usability.

Content Creation and Authoring Software

Personalised learning often entails producing and curating customised material for your learners. This material should be relevant to individual learners’ interests, requirements, and preferences.

After all, there is no better way to distract learners than to force them to study about things unrelated to their responsibilities and interests.

As a result, content production tools, such as authoring tools, make this process more efficient and effective. These tools allow you to easily develop and update interactive content. You may also clone material to tailor it to the diverse needs of your learners.

AI stands for artificial intelligence

Artificial intelligence (AI) has grown in popularity, and the learning and development (L&D) business is no exception. In reality, the majority of today’s modern learning platforms have begun to use AI to construct personalised training programmes.

For example, you can collect data to generate algorithms that can assist you in creating personalised training. These algorithms can analyse data using machine learning techniques to uncover patterns that may be used to tailor training.

Similarly, AI may assist you in easily planning and scheduling training, monitoring progress, and evaluating outcomes. You may, for example, create AI-powered content suggestions that are personalised and completely relevant to the needs of each individual learner.

References

Training bioinformaticians in High Performance Computing
2009 William Allan Award Address: Life in The Sandbox: Unfinished Business
Science-Industry Collaboration: Sideways or Highways to Ocean Sustainability?
Neuroethics and public engagement training needed for neuroscientists
Main gamification concepts: A systematic mapping study