An Intelligent Platform for Offline Learners Based on Model-Driven Crowdsensing Over Intermittent Networks

Shin’ichi Konomi, Lulu Gao, Doreen Mushi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Despite the continuous growth of global Internet users, almost 4 billion people do not use the Internet. The offline population includes people who live in developing regions or rural aging communities. In this context, we propose a learning-support platform for learners without an easy, reliable, and affordable means to access digital learning environments on the Internet. Unlike existing systems that provide little support for efficient educational data collection from offline learners, our proposed platform combines delay-tolerant networking mechanisms and active learning-based model-driven crowdsensing techniques to deliver learning materials and collect educational data efficiently.

Original languageEnglish
Title of host publicationCross-Cultural Design. Applications in Health, Learning, Communication, and Creativity - 12th International Conference, CCD 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
EditorsPei-Luen Patrick Rau
PublisherSpringer
Pages300-314
Number of pages15
ISBN (Print)9783030499129
DOIs
Publication statusPublished - 2020
Event12th International Conference on Cross-Cultural Design, CCD 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020 - Copenhagen, Denmark
Duration: Jul 19 2020Jul 24 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12193 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Cross-Cultural Design, CCD 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
Country/TerritoryDenmark
CityCopenhagen
Period7/19/207/24/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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