Background Many open source software (OSS) quality assessment models are proposed and available in the literature. However, there is little or no adoption of these models in practice. In order to guide the formulation of newer models so they can be acceptable by practitioners, there is need for clear discrimination of the existing models based on their specific properties. Based on this, the aim of this study is to perform a systematic literature review to investigate the properties of the existing OSS quality assessment models by classifying them with respect to their quality characteristics, the methodology they use for assessment, and their domain of application so as to guide the formulation and development of newer models. Searches in IEEE Xplore, ACM, Science Direct, Springer and Google Search is performed so as to retrieve all relevant primary studies in this regard. Journal and conference papers between the year 2003 and 2015 were considered since the first known OSS quality model emerged in 2003.ResultsA total of 19 OSS quality assessment model papers were selected. To select these models we have developed assessment criteria to evaluate the quality of the existing studies. Quality assessment models are classified into five categories based on the quality characteristics they possess namely: single-attribute, rounded category, community-only attribute, non-community attribute as well as the non-quality in use models. Our study reflects that software selection based on hierarchical structures is found to be the most popular selection method in the existing OSS quality assessment models. Furthermore, we found that majority (47%) of the existing models do not specify any domain of application.ConclusionsIn conclusion, our study will be a valuable contribution to the community and helps the quality assessment model developers in formulating newer models and also to the practitioners (software evaluators) in selecting suitable OSS in the midst of alternatives.

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A plethora of approaches exists for the evaluation and selection of open-source software (OSS) in the literature. However, these approaches are hardly ever used in practice for the following reasons: first, the lack of a situational-based procedure to define the evaluation criteria for OSS given its varied and dynamic nature; second, the inability of existing evaluation techniques, such as the analytic hierarchy process, to cope well with uncertainty factors, thus producing misleading results that affect the quality of decisions made; and third, a significant number of existing approaches require the prototyping of alternatives being considered in order to facilitate evaluation and decision-making. This study addresses the aforementioned challenges by evolving a process framework for evaluating and selecting OSS. The proposed framework is validated by applying it to a case study. In addition, expert opinion was elicited via questionnaires from 10 experts, and overall feedback suggests that 80% of them are willing to adopt the approach. KEYWORDS analytic hierarchy process, evidential reasoning, MCDM, open-source software, process framework, weighted scoring model 780The MCDM problem can be referred to as the process of choosing software among available alternatives based on a number of conflicting attributes. 8 MCDM is aimed at 9 (1) helping decision makers choose the best alternative, (2) sorting out the alternatives that seem good among the set of available alternatives, and (3) ranking the alternatives in decreasing order of their performance. A large number of well-known MCDM methods exist, such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), data envelopment analysis, the analytic hierarchy process (AHP), the analytic network process, VIKOR, decision-making trial and evaluation laboratory, the Preference Ranking Organization Method for Enrichment Evaluations, and the Elimination and Choice Expressing Reality method, to mention a few. 10 The AHP is the most popular in terms of its application in software evaluation and selection. 7,11,12 However, the AHP has some known limitations, which can easily be surmounted by using the evidential reasoning (ER) approach in place of the AHP. 13 The ER approach is different from most conventional MCDM methods in that it employs a belief structure to represent an assessment as a distribution. For instance, the distributed assessment of a given software's quality may be {(Excellent, 70%), (Good, 30%), (Average, 0%), (Poor, 0%), (Worst, 0%)}, which means that the quality of the software is assessed to be Excellent with 70% of belief degree and Good with 30% of belief degree. Some of the advantages of using ER over the AHP 13 include the following:i. ability to handle very large multi-attribute decision-making problems compared to the AHP; ii. ability to assess newly added alternatives independently, whereas the AHP would have to repeat an assessment procedure to incorporate new alternatives; iii. ability to produce consistent ranking after n...

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The higher education landscape in developing countries is faced with many challenges, one of which is high faculty to student ratio. An obvious implication of this is compromise on the quality of classroom engagement. The distractions caused by the not conducive learning space and instructors' inability to elucidate correct feedbacks from students usually lead to poor learning outcomes. Feedback mechanisms that are unobtrusive and efficient in processing large data in real-time are needful to measure quality learning experience in such large classroom settings. With the latest impact of penetration and adoption of internet and mobile technologies in most developing counties, wearable technology is a feasible solution to manage and monitor classroom involvement; as real time student feedback can be integrated in the design and delivery of instruction in and out of the classroom. In this paper, we present state of the art of wearable technology and explored the opportunities of wearable technology in the higher education. Specifically, we presented scenarios in which wearable technology can be employed to understand and analyze physiological signals and emotional responses from learners in real-time; the end result of which would increase the quality of classroom engagement, inspire new pedagogy, drive new trends in peer-to-peer collaborations, and increase the learning outcomes. Moreover, we identified some challenges that may hinder this development such as: inconclusive user studies of wearable technology in developing countries and inadequate infrastructure. Finally, we make appropriate recommendations on how these challenges can be surmounted