Adaptive Personalized Network Relationships in the CHUNK Learning Environment
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Authors
Andriulli, Mario
Smith, Maria
Smith, Shane
Gera, Ralucca
Isenhour, Michelle L.
Subjects
education
adaptive learning
learning systems
network theory (graphs)
adaptive algorithms
adaptive learning
learning systems
network theory (graphs)
adaptive algorithms
Advisors
Date of Issue
2019
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
How can learner profiles support personalized online learning? Our current research analyzes a personalized adaptive system for education called CHUNK Learning. The CHUNK Learning system builds on a network of modules, and a learner profile, both tagged with keywords. CHUNK Learning currently utilizes simple keyword relationships to suggest a tailored, personalized, adaptive learning plan guiding the learner through the network of modules. However, supervised machine learning methods may be more suitable to enable the implementation of an iterative algorithm for refined learning plans. In this paper, we investigate the relationship between learner profile and adaptive learning plans. Learners first create a profile in CHUNK Learning which establishes their baseline learning plan. Then, as learners begin to interact with the learning environment, the CHUNK Learning system updates the learning plan based on learner activities (learned, viewed, tested), keyword searches, and content ratings by increasing or reducing the strength of the connection between the learner profile and activities. Additionally, we demonstrate that by connecting all learners within an academic program, we create a stronger bond between learners, which results in a reduced path between activities. We conclude that by reducing the path length between activities, we strengthen connections in the CHUNK Learning environment resulting in a more concise academic plan for learners.
Type
Preprint
Description
Series/Report No
Department
Operations Research (OR)
Applied Mathematics
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
U.S. Department of Defense
Funder
Format
9 p.
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.