A Model of Self-sustaining Automatic Corporate E-learning system - Dinko Bačun; Nives Bačun Lebarović (6th International OFEL Conference on Governance, Management and Entrepreneurship. New Business Models and Institutional Entrepreneurs: Leading Disruptive Change. April 13th - 14th, 2018, Dubrovnik, Croatia, 2018)
Challenging and volatile economic environment forced enterprises to seek alternative ways to optimize the cost and time needed to train their employees in adoption of new skills and technologies. Effective training shortens the time new skills are applied in practice, which results in shorter and more effective time to react to new market conditions. In the last two decades, technology advances revealed new possibilities. E-learning provided a large #of benefits over traditional classroom type training, providing consistent, world wide training, increased learner convenience and lower expenses. This type of training proved to be slightly more effective than the classroom presentation. Its effectiveness grows with the #of participants. The savings that corporations reached, run in order of tens of millions of US dollars. However, practitioners highlight a #of drawbacks that actual implementations revealed. The upfront costs require considerable investment in both information technology and staff, as well as the hardware and software needed to run the system. The time needed to design and build the actual courses and professional knowledge necessary, implies lengthy implementation with sluggish response to change. One aspect of corporate training is often overlooked and that is the training on internal procedures and best practices. When employee training is discussed in management circles, the courses to aquire new skills are considered in most cases. However, new employees need to be trained in corporate everyday practices, as well as experienced employees that are reassigned to new posts or to different departments. During the time they learn the processes, they are prone to errors which might go undetected for long periods of time and have serious consequences. Capturing the professional knowledge of everyday corporate practice proved to be a challenging task, as working professionals seldom have time to consistently describe the variations on prescribed corporate procedures. Traditionally, a tutor is assigned that introduces the newcomer to corporate everyday practices, but there is no measureable test that will reveal the level of knowledge adoption. This paper describes a model that seamlessly captures everyday practices, analyses the distribution of their attributes and uses this information to create a set of questions/answers that are automatically fed into an e-learning platform like Moodle which provides certification possibilities. Data capturing segment is based on the model of Multidimentional Preemptive Coordination which serves a an alert infrastructure. Captured data is analysed periodically (weekly, monthly) by Analyzer module that produces distributions of occurrence of different process attributes, their steps and resources. Generation module applies rules to thresholds in the distribution to detect segments that are basis to generated questions/answers pairs which are fed to the certification platform. Changes in practice are detected as variations in distribution, which, when significant, can provoke creation of a new class with corresponding new questions/answers pairs rendering automatic modification of e-learning content.
Keywords: 650; E-learning; Corporate knowledge management; Automatic knowledge extraction; Corporate certification