Abstract
This study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results’ description, established by the apps’ quality assessment, using the Mobile App Rating Scale (MARS) tool. However, because of the restrictions of MARS outputs, the identification of critical quality factors could not be established, requiring the search for an answer for a new rule. Finally, the explanation of the case (the last component of the abductive approach) to test the rule’s new hypothesis. This problem was solved by applying a new quantitative model, compounding data mining techniques, which identified MARS’ most relevant quality items. Hence, this research defines a much-needed theoretical and practical tool for academics and also practitioners. Academics can experiment utilizing the abduction reasoning procedure as an alternative to achieve positivism in research. This study is a first attempt to improve the MARS tool, aiming to provide specialists relevant data, reducing noise effects, accomplishing better predictive results to enhance their investigations. Furthermore, it offers a concise quality assessment of disability-related apps.
Highlights
Horváth’s (2016) theory explains the concepts and facts in a given context, matching ideas and events logically based on their meaning, which indicates the limits of the theory, facilitates the applicability and permits the recognition of new hypotheses to cover a broader field
The objective of this work is to simplify the Mobile App Rating Scale (MARS) tool to increase its performance without losing the quality of the evaluation
The following is the new hypothesis: the results of apps’ quality evaluation enable selecting quality features, using data mining techniques ordered in a new processing model
Summary
Philipsen (2018) and Ngwenyama (2014) establish the distinctions between deductive, inductive, and abductive reasoning with the connections between the entities; rule, case, and result. The abductive reasoning process addresses the situation where the findings differ from the theory’s anticipated result, which guides the research study. The starting point coincides with that of induction but is concerned with the search for an explanation of the results, which are complex to explain applying the initial guiding theory. The search for reason demands the need for a new hypothesis, leading to the specific investigated case (Philipsen, 2018). Aliseda (2006) assumes that abduction in the scientific sense refers to empirical progress, pragmatism, and epistemic change
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