David Boulanger, Jeremie Seanosky, Michael Baddeley, Vivekanandan S. Kumar, Kinshuk
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Learning Analytics in the Energy Industry: Measuring Competences in Emergency Procedures
Several major accidents in the oil and gas industry traced their source to deficient training resulting in serious injuries and even casualties along with extremely expensive damage to equipment and decrease in productivity. This paper presents a procedure evaluation/e-training tool called PeT to track the knowledge and confidence of trainees in emergency operating procedures. PeT was tested with two emergency procedures in an oil and gas company in Canada. A text-based knowledge test was implemented for each procedure. Each test consisted of multiple-choice questions. Answers were classified as perfectly correct, incomplete but correct, partially correct, mostly incorrect, and totally incorrect. The paper also describes the six-factor confidence model underlying the confidence computations in PeT: knowledge, reaction time, lingering, number of visits (revision), number of selections, and number of switching answers. Each confidence factor measures a specific aspect of the targeted behaviour in an emergency. The results of two experiments conducted in 2014 in an oil and gas company are also presented to show the types of analysis that PeT enables. A plan to move PeT into an interactive training environment to track the actions of operators in their work environment and translate their interaction into higher level competences is also briefly introduced.