In the world of structured on-the-job training, the emphasis is on how learning is applied not just in work-based scenarios, but also in the very real context of the specific duties of the learner’s job.
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On-the-job training gives learners the convenience of hands-on learning at their own pace within their workday. It gives learners the autonomy over their learning and development, reframing training as a tailored experience for their own learning journey.
Learning technologies powered by artificial intelligence (AI) can help deliver on-the-job training to manufacturing employees.
Let’s explore some strategies learning and development (L&D) teams can use to maximize knowledge acquisition, practice and application to bridge that gap.
OJT offers a more engaging training style that allows employees to “learn by doing,” which is easier to remember for many learners, especially for task-specific instructions.
Of all the workflow-embedded learning opportunities, experience-based development offers an important and distinctive benefit: Real-time contribution.
Our organizations are in desperate need of training options that empower learners to gain knowledge and skills without having to gather in a classroom.
Regardless of the source of the training content, learning is of little value unless it prepares the participant to perform better on the job and makes a measurable contribution to organizational results.
Many workplaces are practicing an informal approach to on-the-job training. Formalizing this process provides a means of measuring its efficacy.
A sound leadership training strategy can be the difference between lackluster courses with disappointing results and improved job performance that drives organizational success.