Abstract

Problem: Workers and adult learners face several challenges with regard to keeping ahead of digital disruption in the Fourth Industrial Revolution. They can be unclear about whether the tasks they currently do are at risk of automation, which new tasks to train for, which tasks are engaging or exhausting, and how automation impacts work. These challenges also impact the ability of leaders, organizations, policymakers, and educators to design better jobs and training programs. If these challenges are not addressed, they can lead to reduced participation in lifelong learning, reduced well-being, and decreased career resilience. Solution: This present study presents the Task Approach to training and adult learning. It provides a method to identify which tasks are at risk of automation, how to identify new tasks to train for, which tasks are engaging or exhausting, and how automation impacts work. Method: The Task Approach was utilized to understand the tasks and related attributes of workers. This included the use of the functional job analysis (FJA) and critical incidents technique (CIT) to understand how tasks and situations impacted the worker and adult learner. Outcome: The outcome of these research is the empirical demonstration of the Task Approach in addressing the abovementioned problems. This can help worker and adult learners in training and upskilling. The findings can help workers and adult learners improve their well-being at work while being more resilient and employable. The findings can enhance the ability of leaders, organizations, policymakers and educators to design better jobs and lifelong learning training programs.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.