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An approach to predict the task efficiency of web pages

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Abstract

Usability is generally considered as a metric to judge the efficacy of any interface. This is also true for the web pages of a website. There are different factors - efficiency, memorability, learnability, errors, and aesthetics play significant roles in order to determine usability. In this work, we proposed a computational model to predict the efficiency with which users can do a particular task on a website. We considered seventeen features of web pages that may affect the efficiency of a task. The statistical significance of these features was tested based on the empirical data collected using twenty websites. For each website, a representative task was identified. Twenty participants completed these tasks using a controlled environment within a group. Task completion times were recorded for feature identification. The one Dimensional ANOVA study reveals sixteen out of the seventeen are statistically significant for efficiency measurement. Using these features, a computational model was developed based on the Support Vector Regression. Experimental results show that our model can predict the efficiency of web pages’ tasks with an accuracy of 90.64%.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Central Institute of Technology Kokrajhar, Kokrajhar, 783370, Assam, India

    Sangita Saha, Apurbalal Senapati & Ranjan Maity

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  1. Sangita Saha
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  2. Apurbalal Senapati
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  3. Ranjan Maity
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Correspondence to Sangita Saha.

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Apurbalal Senapati and Ranjan Maity are contributed equally to this work.

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Saha, S., Senapati, A. & Maity, R. An approach to predict the task efficiency of web pages. Multimed Tools Appl 82, 25217–25233 (2023). https://doi.org/10.1007/s11042-023-14619-3

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  • DOI: https://doi.org/10.1007/s11042-023-14619-3

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