Research Summaries

Back Deep Analytics for MarineNet with Personalized Learning - Using the Pilot Data (Continuation)

Fiscal Year 2019
Division Research & Sponsored Programs
Department NPS Naval Research Program
Investigator(s) Kendall, Walter A.
Zhao, Ying
Sponsor NPS Naval Research Program (Navy)
Summary The objective of the Phase II of the project is to utilize the MarineNet Content Management System (CMS) pilot data sets to personalize the learner's training experience and optimize the content training efficiency to improve knowledge retention and individual operational readiness.

In Year one of this research, we identified Measure's of Effectiveness (MoE), specifically MoEs with respect to content, learner-content interaction, and learner profile. We also examined the proposed big data for collection by the CMS and analytic techniques that can be indeed used for the proposed MoEs. The resulted analytics and reports from the big data can be used to inform stakeholders such as instructors, sponsors and developers to enhance the learning experience and content efficiency in order to improve knowledge retention by the MarineNet learners. We also identified the big data analytics tools that can be used for the collected data.

In phase II, we will utilize the CMS pilot data sets to validate the process from Phase I and also continue validating the process from these MOEs to smart data, integrating machine learning and artificial intelligence models with the MOE results. Ultimately the results will indicate to the learner recommended content for the individualized learning path, course of action for mediation of training objective knowledge discrepancies.
Keywords
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal