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Empirical Investigation of Usability Evaluation Methods for Mobile Applications Using Evidence-Based Approach

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Microservices in Big Data Analytics

Abstract

Mobile learning or m-learning is novel learning medium, and consequently, there is a lot of research required to design usable m-learning applications. With the advent of new m-learning applications and their indulgence in imparting education, it poses new usability challenges. M-learning has to be investigated from various perspectives for its effectiveness and efficiency. So to have an effective and usable m-learning application, it is quintessential to discover an appropriate set of usability evaluation methods [UEMs] to evaluate the usability of m-learning application. For the aforesaid purpose, an evidence-based study of UEMs is carried out in this paper to compare and then assess different UEMs. To bridge the gaps between research evidence and software development practices and to avoid expensive and ineffective decision making during application development, an evidence-based approach is suggested by [1, 2]. Evidence-based study is the process of systematically finding, evaluating, and using contemporary research conclusions as the basis for decision making. An evidence-based study is required before the adoption of UEM/UEMs because sufficient evidences should be gathered as a decision factor before testing an application. This study presents an empirical analysis for selecting effectual UEM(s) for a set of mobile learning applications using evidence-based approach [EBA].

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Mathur, P., Chande, S.V. (2020). Empirical Investigation of Usability Evaluation Methods for Mobile Applications Using Evidence-Based Approach. In: Chaudhary, A., Choudhary, C., Gupta, M., Lal, C., Badal, T. (eds) Microservices in Big Data Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-15-0128-9_9

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