lnu.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
A Self-Adaptive Multi-Agent System Approach for Collaborative Mobile Learning
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för medieteknik (ME). (CeLeKT)
Pontificia Universidad de Chile, Chile.
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).ORCID-id: 0000-0002-1162-0817
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för medieteknik (ME). (CeLeKT)ORCID-id: 0000-0002-6937-345X
Visa övriga samt affilieringar
2015 (Engelska)Ingår i: IEEE Transactions on Learning Technologies, ISSN 1939-1382, E-ISSN 1939-1382, Vol. 8, nr 2, s. 158-172Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Mobile technologies have emerged as facilitators in the learning process, extending traditional classroom activities. However, engineering mobile learning applications for outdoor usage poses severe challenges. The requirements of these applications are challenging, as many different aspects need to be catered, such as resource access and sharing, communication between peers, group management, activity flow, etc. Robustness is particularly important for learning scenarios to guarantee undisturbed and smooth user experiences, pushing the technological aspects in the background. Despite significant research in the field of mobile learning, very few efforts have focused on collaborative mobile learning requirements from a software engineering perspective. This paper focuses on aspects of the software architecture, aiming to address the challenges related to resource sharing in collaborative mobile learning activities. This includes elements such as autonomy for personal interactive learning, richness for large group collaborative learning (indoor and outdoor), as well as robustness of the learning system. Additionally, we present self-adaptation as a solution to mitigate risks of resource unavailability and organization failures that arise from environment and system dynamism. Our evaluation provides indications regarding the system correctness with respect to resource sharing and collaboration concerns, and offers qualitative evidence of self-adaptation benefits for collaborative mobile learning applications.

Ort, förlag, år, upplaga, sidor
IEEE, 2015. Vol. 8, nr 2, s. 158-172
Nyckelord [en]
Mobile Learning, Software Architecture, Multi-Agent Systems, Self-Adaptation
Nationell ämneskategori
Datorsystem
Forskningsämne
Data- och informationsvetenskap, Datavetenskap; Data- och informationsvetenskap, Medieteknik
Identifikatorer
URN: urn:nbn:se:lnu:diva-39602DOI: 10.1109/TLT.2014.2367493ISI: 000358585000002Scopus ID: 2-s2.0-84933044339OAI: oai:DiVA.org:lnu-39602DiVA, id: diva2:784847
Tillgänglig från: 2015-01-30 Skapad: 2015-01-30 Senast uppdaterad: 2017-04-24Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Personposter BETA

Gil de la Iglesia, DidacWeyns, DannyMilrad, Marcelo

Sök vidare i DiVA

Av författaren/redaktören
Gil de la Iglesia, DidacWeyns, DannyMilrad, Marcelo
Av organisationen
Institutionen för medieteknik (ME)Institutionen för datavetenskap (DV)
I samma tidskrift
IEEE Transactions on Learning Technologies
Datorsystem

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetricpoäng

doi
urn-nbn
Totalt: 420 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf