In order to perform research using novel systems it is first important to distinguish if the collecteddata reflects the manipulations performed by the researcher or the fact that the system might beunfamiliar to the subject. Especially when using highly complex systems such as trainingsimulators, researchers should aim to begin their studies by ensuring that the system is fullylearned. The current study used a virtual reality simulation of a futuristic reconnaissance missionscenario to investigate how performance, mental workload and psychophysiologicalmeasurements changed during repeated training and how data would reflect an additional stimulusappearance after the system had been learned. The results confirmed pre-existing theories oflearning and showed that response to additional tasks after the system had been learned wouldfluctuate but not reach the same levels that were visible at the beginning of the training. Thissmaller increase in response could be assumed to accurately reflect the manipulation of thescenario rather than the novelty of the system.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-188657 |
| Date | January 2022 |
| Creators | Trinkune, Anna Marija |
| Publisher | Linköpings universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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