Examining the Effects of Learning Theory Implemented within an Online and Self-Paced Learning Path
Abstract
The United States military must continue to innovate and improve the way we fight and defend against our near-peer adversaries. Emerging technologies such as machine learning, artificial intelligence, and reverse engineering are paving the way for an increasingly complex security environment. A core tenant of winning in this new era of warfare is how we educate and train our military force. Many of the online trainings made available to servicemembers today fall short in the implementation of existing learning theories. This research identifies a gap in the current literature regarding common learning theories, noting that there is a lack of research regarding the implementation of active recall, spaced repetition, and elaboration into fully online and asynchronous learning paths (LPs). This research surveys the current literature regarding the topics at hand, produces a framework for LP development, develops a LP for Agile software development (an emerging topic of interest for the DoD), and examines the effects of three forms of learning theory within an online and self-paced LP through a human-subjects research experiment. A workshop and an associated LP are developed that implement and test the effects of these three learning theories. The results from the final assessment and pre- and post-workshop surveys showed a positive benefit for competence and confidence with presented material within the LP, but more research is necessary to determine how these three theories affect motivation.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2022
- Accession Number
- AD1173313
Entities
People
- Trenton M. Woods
Organizations
- Air Force Institute of Technology