Towards qualitative and quantitative data integration approach for enhancing HCI quality evaluation

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Abstract

Over the two past decades, various HCI quality evaluation methods have been proposed. Each one has its own strengths and its own shortcomings. Different methods are combined to enhance the evaluation results. To obtain better coverage of design problems and to increase the system performance, subjective and objective methods can complement each other. However, the variability of these methods features poses a challenge to effectively integrate between them. The purpose of this paper is to enhance the evaluation of HCI quality by suggesting new approach intended for improving evaluation results. This method supports a mapping model between evaluation data. It aims to specify new quality indicators that effectively integrate qualitative and quantitative data based on a set of pre-defined quality criteria. Qualitative (items) and quantitative data are respectively extracted from highly cited HCI quality questionnaires and from existing tools. © 2014 Springer International Publishing.

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Assila, A., De Oliveira, K. M., & Ezzedine, H. (2014). Towards qualitative and quantitative data integration approach for enhancing HCI quality evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8510 LNCS, pp. 469–480). Springer Verlag. https://doi.org/10.1007/978-3-319-07233-3_43

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