Sustaining Continuous Collaborative Learning Flows in MOOCs: Orchestration Agent Approach

被引:0
|
作者
Amarasinghe, Ishari [1 ]
Hernandez-Leo, Davinia [1 ]
Manathunga, Kalpani [1 ]
Jonsson, Anders [1 ]
机构
[1] Univ Pompeu Fabra, ICT Dept, Barcelona, Spain
关键词
Computer-Supported Collaborative Learning (CSCL); Intelligent Agents; Massive Open Online Courses (MOOCs); Collaborative Learning Flow Patterns (CLFPs);
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Collaborative learning spaces deployed in Massive Open Online Courses (MOOCs) provide productive social learning opportunities. However, sustaining collaboration in these spaces is challenging. This paper provides a classification of MOOCs participants based on their behavior in a structured collaborative learning space. This analysis leads to requirements for new technological interventions to orchestrate collaborative learning flows in MOOCs. The paper proposes the design of an intelligent agent to address these requirements and reports a study which shows that the intervention of the proposed orchestration agent in a MOOC facilitates to maintain continuous yet meaningful collaboration learning flows.
引用
收藏
页码:1034 / 1051
页数:18
相关论文
共 50 条
  • [21] An Approach for the Identification and Tracking of Learning Styles in MOOCs
    Hmedna, Brahim
    El Mezouary, Ali
    Baz, Omar
    EUROPE AND MENA COOPERATION ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGIES, 2017, 520 : 125 - 134
  • [22] A Machine Learning Approach to Identify and Track Learning Styles in MOOCs
    Hmedna, Brahim
    El Mezouary, Ali
    Baz, Omar
    Mammass, Driss
    PROCEEDINGS OF 2016 5TH INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS), 2016, : 212 - 216
  • [23] A Sample Efficient Multi-Agent Approach to Continuous Reinforcement Learning
    Corcoran, Diarmuid
    Kreuger, Per
    Boman, Magnus
    2022 18TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT (CNSM 2022): INTELLIGENT MANAGEMENT OF DISRUPTIVE NETWORK TECHNOLOGIES AND SERVICES, 2022, : 338 - 344
  • [24] Collaborative agent learning using neurocomputing
    Farooque, S
    Abraham, A
    Jain, L
    NEURAL INFORMATION PROCESSING, 2004, 3316 : 619 - 624
  • [25] Improving and Sustaining Breastfeeding Practices through a Statewide Learning Collaborative
    Stagg, Julie
    Ustianov, Jennifer
    JOGNN-JOURNAL OF OBSTETRIC GYNECOLOGIC AND NEONATAL NURSING, 2015, 44 : S55 - S55
  • [26] Collaborative Multi-agent Reinforcement Learning for Landmark Localization Using Continuous Action Space
    Kasseroller, Klemens
    Thaler, Franz
    Payer, Christian
    Stern, Darko
    INFORMATION PROCESSING IN MEDICAL IMAGING, IPMI 2021, 2021, 12729 : 767 - 778
  • [27] An Adaptive Learning Approach for Better Retention of Learners in MOOCs
    El Miloud, Smaili
    Soukaina, Sraidi
    Salma, Azzouzi
    El Hassan, Charaf My
    3RD INTERNATIONAL CONFERENCE ON NETWORKING, INFORMATION SYSTEM & SECURITY (NISS'20), 2020,
  • [28] MOOCs and blended learning models. A practical approach
    Torres-Coronas, Teresa
    Vidal-Blasco, Maria-Arantzazu
    RIED-REVISTA IBEROAMERICANA DE EDUCACION A DISTANCIA, 2019, 22 (02): : 325 - 343
  • [29] A Multi-Agent Reinforcement Learning Architecture for Network Slicing Orchestration
    Mason, Federico
    Nencioni, Gianfranco
    Zanella, Andrea
    2021 19TH MEDITERRANEAN COMMUNICATION AND COMPUTER NETWORKING CONFERENCE (MEDCOMNET), 2021,
  • [30] A Self-Adaptive Multi-Agent System Approach for Collaborative Mobile Learning
    de la Iglesia, Didac Gil
    Felipe Calderon, Juan
    Weyns, Danny
    Milrad, Marcelo
    Nussbaum, Miguel
    IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 2015, 8 (02): : 158 - 172