A Survey on Data-Driven Evaluation of Competencies and Capabilities Across Multimedia Environments

被引:8
作者
Strukova, Sofia [1 ]
Ruiperez-Valiente, Jose A. [1 ]
Marmol, Felix Gomez [1 ]
机构
[1] Univ Murcia, Dept Informat & Commun Engn, Murcia, Spain
来源
INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2023年 / 8卷 / 04期
关键词
Artificial Intelligence; Competencies; Computational Social Science; Data Mining; Multimedia Environments; SOCIAL NETWORK SITES; BIG DATA; EMPIRICAL-EVIDENCE; HIGHER-EDUCATION; COMPUTER GAMES; ENGAGEMENT; RANKING; TWITTER; SKILLS; COMMUNICATION;
D O I
10.9781/ijimai.2022.10.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The rapid evolution of technology directly impacts the skills and jobs needed in the next decade. Users can, intentionally or unintentionally, develop different skills by creating, interacting with, and consuming the content from online environments and portals where informal learning can emerge. These environments generate large amounts of data; therefore, big data can have a significant impact on education. Moreover, the educational landscape has been shifting from a focus on contents to a focus on competencies and capabilities that will prepare our society for an unknown future during the 21st century. Therefore, the main goal of this literature survey is to examine diverse technology-mediated environments that can generate rich data sets through the users' interaction and where data can be used to explicitly or implicitly perform a data driven evaluation of different competencies and capabilities. We thoroughly and comprehensively surveyed the state of the art to identify and analyse digital environments, the data they are producing and the capabilities they can measure and/or develop. Our survey revealed four key multimedia environments that include sites for content sharing & consumption, video games, online learning and social networks that fulfilled our goal. Moreover, different methods were used to measure a large array of diverse capabilities such as expertise, language proficiency and soft skills. Our results prove the potential of the data from diverse digital environments to support the development of lifelong and lifewide 21st-century capabilities for the future society.
引用
收藏
页码:182 / 201
页数:217
相关论文
共 50 条
  • [31] Developing a data analytics toolbox for data-driven product planning: a review and survey methodology
    Panzner, Melina
    von Enzberg, Sebastian
    Dumitrescu, Roman
    AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 2024, 38
  • [32] A new data-driven effectiveness evaluation model of temporary plugging fracturing for horizontal wells
    Sheng M.
    Zhang J.
    Zhang Y.
    Li C.
    Li Y.
    Li G.
    Natural Gas Industry, 2023, 43 (09) : 132 - 140
  • [33] Artificial intelligence and big data-driven evaluation research and practices: A systematic literature review
    Bouyousfi, Salah E.
    Ouedraogo, Miche
    EVALUATION, 2024,
  • [34] DATA-DRIVEN APPROACH FOR QUALITY EVALUATION ON KNOWLEDGE SHARING PLATFORM
    Xu, Lu
    Xiang, Jinhai
    Wang, Yating
    Ni, Fuchuan
    PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), 2019, : 649 - 654
  • [35] AI-based modeling and data-driven evaluation for smart farming-oriented big data architecture using IoT with energy harvesting capabilities
    Ouafiq, El Mehdi
    Saadane, Rachid
    Chehri, Abdellah
    Jeon, Seunggil
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 52
  • [36] MURAME parameter setting for creditworthiness evaluation: data-driven optimization
    Corazza, Marco
    Fasano, Giovanni
    Funari, Stefania
    Gusso, Riccardo
    DECISIONS IN ECONOMICS AND FINANCE, 2021, 44 (01) : 295 - 339
  • [37] A Data-Driven Evaluation of the Current Security State of Android Devices
    Leierzopf, Ernst
    Mayrhofer, Rene
    Roland, Michael
    Studier, Wolfgang
    Dean, Lawrence
    Seiffert, Martin
    Putz, Florentin
    Becker, Lucas
    Thomas, Daniel R.
    2024 IEEE CONFERENCE ON COMMUNICATIONS AND NETWORK SECURITY, CNS 2024, 2024,
  • [38] Data-driven predictions of summertime visits to lakes across 17 US states
    Nelson, Erik
    Rogers, Maggie
    Wood, Spencer A. A.
    Chung, Jesse
    Keeler, Bonnie
    ECOSPHERE, 2023, 14 (04):
  • [39] Towards a Multimedia Big Data-Driven Approach for Earthquake Monitoring and Forecasting Early Warning System
    Ye Q.
    Xia B.
    Ren Y.
    Informatica (Slovenia), 2024, 48 (09): : 53 - 64
  • [40] Assessing sustainability competencies in contemporary STEM higher education: a data-driven analysis at Tecnologico de Monterrey
    Valdes-Ramirez, Danilo
    de Armas Jacomino, Laidy
    Monroy, Raul
    Zavala, Genaro
    FRONTIERS IN EDUCATION, 2024, 9