machine-learning-development

Machine learning involves computational methods to utilise data in the form of experience (past information) to improve performance and to make predictions. The Mediasphere team is very interested in the emergence of machine learning and artificial intelligence in improving human resources. 

Machine learning can improve decisions on hiring, firing and performance reviews as well as eliminate a number of biases that may occur in HR tasks.

The breakdown

The most well-known example of machine learning, and the easiest way to understand it, is Google. Every time we search something in Google, or any search browser, we are seeing the work of machine learning. The algorithms are utilised to output relevant data of what many others are searching for and make suggestions accordingly. 

Machine learning can access a large quantity of data in an incredibly short amount of time and learns from those searches in the process. Understanding this consistent and reliable process, many will find that machine learning can improve their industry, such as investments, insurance, medical fields etc. Machine learning also has the chance to improve the training industry and the way we learn today.

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Personalised learning

Utilising big data to create a more customised training program is the way of the future for training. With machine learning, large quantities of data is sorted and organised to find learning patterns that instructional designers can then use when creating training courses. 

Machine learning becomes your new work pal

In 2018, machine learning will be that new work pal that shows a new employee around the office, the ins and outs of the organisational structure and acts as a mentor, guiding the new employee on a path to professional success. 

Setting up a learning program as soon as a new person is hired means that the organisation can then easily and effectively gather data and help mould a program that suits the person’s developmental needs. As a machine learning program gathers information and finds patterns, the LMS could then offer new insights and recommendations for the developing employee as well as managerial insights for their professional manager. 

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Hey, focus!

We all know how difficult it can be to keep individuals engaged in learning and with machine learning, engagement gets a lot easier. When creating the learning programs for 2018, look to machine learning as a guide to develop predictions for individual learning. Understanding how your employees learn can help to create a better and more engaging learning program. 

Don’t forget about reports

All good training programs have engaging and detailed learning objectives. At the end of each course, the learner should be able to express the main objectives of each learning course and how it may relate in real-world experiences.

Creating these objectives makes it easier to scale learning development and report the learning capabilities of every individual in the workplace. 

Reporting with your LMS can greatly improve the work of machine learning and make it much easier for managers to visualise the progress learning programs have on the workplace. 

Managers and machine learning can also identify key gaps in knowledge and then employ the instructional designers to create programs to fill those gaps.

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Machine learning evaluates, learns and adopts with your LMS to create a perfect solution for your corporate learning. Find out how machine learning can benefit your PowerHouse LMS by talking with one of our representatives at Mediasphere. 

 

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