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    Evaluation of Domain-specific Rule Generation Framework based on Usability Criteria

    Access Status
    Fulltext not available
    Authors
    Mani, N.
    Nimmagadda, Shastri
    Helfert, M.
    Reiners, Torsten
    Date
    2018
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Mani, N. and Nimmagadda, S.L. and Helfert, M. and Reiners, T. 2018. Evaluation of Domain-specific Rule Generation Framework based on Usability Criteria. In: 22nd Pacific Asia Conference on Information Systems, PACIS 2018, 26 Jun 2018, Yokohama, Japan.
    Source Title
    https://aisel.aisnet.org/pacis2018/95
    Source Conference
    22nd Pacific Asia Conference on Information Systems, PACIS 2018
    ISBN
    9784902590838
    Faculty
    Faculty of Business and Law
    School
    School of Management
    URI
    http://hdl.handle.net/20.500.11937/81149
    Collection
    • Curtin Research Publications
    Abstract

    The challenges faced by domain experts, commitments made to domain-specific rule (DSR) languages and process design are described. We investigate the business application developments and existing challenges of evaluation strategies of DSR articulations. Often, multiple domain scenarios pose end-user predicaments complicating the computational ability of DSR. In addition, implementation of DSR and its configuration are belated due to poorly evaluated usability criteria. A new framework is needed, facilitating the DSR language and enhancing the computational intelligence. We intend to evaluate the performance of DSR generation and framework integration with variety of usability conditions including efficiency and effectiveness of configuration through system usability score (SUS). Empirical research involving experimental data, questionnaire surveys, and interview outcomes provide conclusive evaluation attributes and their fact instances from SUS. Both manual and semi-automatic configurations are tested. Semiautomatic configuration appears to be more efficient and satisfactory with regard to artifact performance, quality, learnability, user-friendly and reliability.

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