An Analytics Based Approach to Improving Digital Learning Efficacy in the Energy Sector

Abstract The supply of skills to fill modern job requirements in the energy sector has been overextended by the pace of advancing technology and increasing attrition. Underpinning this problem is the inadequate availability of effective training. This learning gap results primarily from four factors: Scarcity of qualified expertise, budget constraints, time requirements and curriculum relevance. Properly deployed online learning addresses these factors, but has so far not been widely adopted in the energy sector. It is hypothesized the adoption rate could be increased by focusing on what drives lesson completion velocity, or the pace at which a student completes their coursework. By encouraging learning methods that create positive momentum, they are more likely to have sustained engagement and complete their course. In this study of over 1600 students, multiple online-learning methods were tested to determine which method results in the highest lesson completion velocities. Three different learning methods were evaluated against completion velocity. These methods include: Unstructured, Cohorts and Enrolments. The Unstructured group were provided with access to digital courses without any program to follow. ‘Enrolments’ represents a single learner who has given him/herself specific time-bound learning goals. And ‘Cohorts’ is similar to Enrolments but where a group of learners are assigned to the same learning schedule and have visibility into each other's learning progress. Students have the option of learning in any one, or a combination of these formats. Two years of online learner data was reviewed. Other variables included within the analysis included the learner's job title, course and organization. The data was analyzed to determine what drives learner engagement. A Shapiro-Wilk test indicated the data was highly non-normal, which meant parametric approaches were not appropriate to use. It was found that the ‘Cohort’ method was most correlated to higher lesson completion velocity. When learners were part of a Cohort, the student completed an extra course day per month in comparison to the Unstructured approach (the baseline), representing an 82% increase. Within the confidence interval of the data, ‘Enrolment’ was not observed to increase the number of lessons completed. However, Enrolment did affect the completion velocity. Job title and organization was also found to influence completion velocity. Continuing education requires significant improvement to address the widening skills gap in the industry. While digital learning technology will undoubtedly play a strong role in fulfilling future training requirements, it is important to understand what drives learner engagement. To the knowledge of the authors, no study of this scale has been previously performed in the oil and gas digital learning space. The results of this study could be used to help design new, or improve existing online training programs.

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