CCE Theses and Dissertations
Effectiveness of Video-Based Augmented Reality as a Learning Paradigm for Aerospace Maintenance Training
Date of Award
2004
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Graduate School of Computer and Information Sciences
Advisor
Maxine S. Cohen
Committee Member
Timothy Ellis
Committee Member
Dennis A. Vincenzi
Abstract
This dissertation focused on an application of augmented reality (AR) as a learning paradigm. Literature on the subject reveals a large body of knowledge on virtual reality and its effect on training and learning, but little research has been conducted to investigate the effects that AR-based training has on recall and retention. Evidence suggests that AR has a considerable effect on recall by establishing to-be-recalled items in a highly memorable framework. Using AR to develop augmented scenes in a highly memorable framework can complement human information processing, and such a complement can reveal itself in training efficiency applicable to a wide variety of aerospace maintenance-related tasks. The state of aerospace maintenance training can be advanced with AR because of the technology's unique characteristics of merging synthetic and real objects in unified, spatially integrated scenes. Continuing research in the field of AR applications for training is necessary because of the potential for increased learning performance and significant decreases in training time. This research determined that AR-based learning effects long-term memory by reducing the amount of information forgotten after a seven-day intervening time between an immediate-recall test and long-term-retention-recall test. Further research is necessary to isolate human variability associated with cognition, learning, and application of AR-based technologies as a training and learning paradigm for the aerospace industry.
NSUWorks Citation
Nickolas D. Macchiarella. 2004. Effectiveness of Video-Based Augmented Reality as a Learning Paradigm for Aerospace Maintenance Training. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Graduate School of Computer and Information Sciences. (691)
https://nsuworks.nova.edu/gscis_etd/691.