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Enhancing Usability Inspection Through Data-Mining Techniques: An Automated Approach for Detecting Usability Problem Patterns of Academic Websites

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Intelligent Human Computer Interaction (IHCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10127))

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Abstract

Usability is one of important attribute of software quality. It is associated with the “ease of use” of any system. Usability evaluation is becoming significant component of software development. Usability evaluation is performed through qualitative assessments. Qualitative assessments can be attained through Qualitative usability inspection (QUI). QUI methods emphasize on evaluating the interface of a specific system. These methods turn out to be complicated when huge number of systems related to similar context of use, are considered jointly to impart a general diagnosis. The principal cause for this is due to substantial quantity of information that should be conceptualized simultaneously. To handle substantial quantity of information, this paper proposes a novel approach that integrates QUI with automated woorank tool and data-mining techniques (association rules and decision tree). To validate this proposed approach, 50-academic websites are evaluated and usability problems patterns related to academic websites are identified by processing 2475 records.

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Notes

  1. 1.

    QUIc represents Qualitative usability inspection for context of use.

  2. 2.

    Top-50 academic websites listed in National Institutional Ranking Framework are considered.

  3. 3.

    The detailed description of attribute along with categories are listed in Table 1.

  4. 4.

    https://www.nirfindia.org/univ.

  5. 5.

    In this approach, 7-different categories are considered, namely Design, Content, Navigation, Security, Search, Mobile, and Social Media, for evaluation of usability of academic websites.

  6. 6.

    Out of 50-top universities, woorank could not evaluate 5-universities due to some security reasons.

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Authors and Affiliations

  1. University School of Information and Communication Technology, GGSIPU, Sector 16-C, Delhi, 110078, India

    Kalpna Sagar & Anju Saha

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  1. Kalpna Sagar
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  2. Anju Saha
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Correspondence to Kalpna Sagar .

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Editors and Affiliations

  1. IIT Kharagpur , Kharagpur, India

    Anupam Basu

  2. IIT Madras , Chennai, India

    Sukhendu Das

  3. Telecom SudParis , Evry, France

    Patrick Horain

  4. IIT Guwahati , Guwahati, India

    Samit Bhattacharya

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Sagar, K., Saha, A. (2017). Enhancing Usability Inspection Through Data-Mining Techniques: An Automated Approach for Detecting Usability Problem Patterns of Academic Websites. In: Basu, A., Das, S., Horain, P., Bhattacharya, S. (eds) Intelligent Human Computer Interaction. IHCI 2016. Lecture Notes in Computer Science(), vol 10127. Springer, Cham. https://doi.org/10.1007/978-3-319-52503-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-52503-7_19

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