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An Adaptive Education Approach Using the Learners’ Social Network

Authors:
Ralucca Gera
Alex Gutzler
Ryan Hard
Bryan McDonough
Christian Sorenson

Keywords: Education; Chunk Learning; Adaptive Learning

Abstract:
How can the 21st century education system capitalize on online social networks to support formal education? As education transitions away from the traditional brick-and mortar style, so does the social network that supports learners. Traditional collegiate education lacks the use of an adaptive system through which students can optimize learning, and educators can promote such learning with the assistance of realtime digital feedback. We develop the means through which the Curated Heuristic Using a Network of Knowledge (CHUNK) learning can provide an adaptive learning framework by designing a dynamic social network of students based on social and academic attributes. Learners use a rating system to determine what educational methods are effective or ineffective in assisting their learning, and the CHUNK Learning system exploits this data to provide other learners more effective methods. We explore the impact that users have on each other when they are considered to be similar based on sharing similar interests. We learn that while different modeling methodology can capture the strength of similarity between users, our experiments show that strongly connected groups have a stronger influence on each other than the weakly connected ones.

Pages: 66 to 72

Copyright: Copyright (c) The Government of US DoD, 2019. Used by permission to IARIA.

Publication date: June 30, 2019

Published in: conference

ISSN: 2519-8351

ISBN: 978-1-61208-725-2

Location: Rome, Italy

Dates: from June 30, 2019 to July 4, 2019