The programming-like-analysis of an innovative media tool

This paper describes a case study in which evaluation techniques have been developed and applied to a novel commercially developed tool for supporting efficiency and effectiveness of a digital film production processes. The tool is based upon a familiar concept in digital publishing that of separating style from content, and as such, it represents a challenge for intended end users since it moves them away from traditional working practices and towards programming-like-activity. Two alternative user interfaces have been developed following a commercial development route. Approaches to analyzing the effectiveness of the tool and its interfaces prior to its widespread adoption are described and the conclusions from this analysis are illustrated and discussed

Benefits and challenges of cloud computing adoption and usage in higher education

The aim of this article was to provide evidence pertaining to cloud computing (CC) adoption in education, namely higher education institutions (HEIs) or Universities. A systematic literature review (SLR) of empirical studies exploring the current CC adoption levels in HEIs and the benefits and challenges for using CC in HEIs was performed. A total of 20 papers were included in the SLR. It was discovered that a number of universities have a keen interest in using CC in their institution, and the evidence indicates a high level of successful CC adoption in the HEIs reviewed in the SLR. In conclusion, the SLR identified a clear literature gap in this research area: there exists limited empirical studies focusing on CC utilisation in HEIs

On Evaluating Commercial Cloud Services: A Systematic Review

Background: Cloud Computing is increasingly booming in industry with many competing providers and services. Accordingly, evaluation of commercial Cloud services is necessary. However, the existing evaluation studies are relatively chaotic. There exists tremendous confusion and gap between practices and theory about Cloud services evaluation. Aim: To facilitate relieving the aforementioned chaos, this work aims to synthesize the existing evaluation implementations to outline the state-of-the-practice and also identify research opportunities in Cloud services evaluation. Method: Based on a conceptual evaluation model comprising six steps, the Systematic Literature Review (SLR) method was employed to collect relevant evidence to investigate the Cloud services evaluation step by step. Results: This SLR identified 82 relevant evaluation studies. The overall data collected from these studies essentially represent the current practical landscape of implementing Cloud services evaluation, and in turn can be reused to facilitate future evaluation work. Conclusions: Evaluation of commercial Cloud services has become a world-wide research topic. Some of the findings of this SLR identify several research gaps in the area of Cloud services evaluation (e.g., the Elasticity and Security evaluation of commercial Cloud services could be a long-term challenge), while some other findings suggest the trend of applying commercial Cloud services (e.g., compared with PaaS, IaaS seems more suitable for customers and is particularly important in industry). This SLR study itself also confirms some previous experiences and reveals new Evidence-Based Software Engineering (EBSE) lessons

EVIDENCE-BASED INFORMATION SYSTEMS: A DECADE LATER

The “evidence-based practice” paradigm was proposed to IS researchers a decade ago. Since then evidence-based practice has become established across a range of disciplines, but it has received relatively little attention in IS. This paper explains the idea of evidence-based practice and reviews the related work found in the IS research literature. Some possible reasons for the lack of widespread adoption in IS are suggested. Systematic literature reviews (SLRs), a key research method in evidence-based practice, are explained. Recent developments in SLRs are discussed, which enable a richer and more nuanced approach to understanding information systems than found in conventional SLRs. It is proposed that these developments now make SLRs more suitable for synthesising empirical studies in IS. Greater use of SLRs by IS researchers would enable us to develop a cumulative knowledgebase of use to both researchers and practitioners

Mobile Learning Technologies for Education: Benefits and Pending Issues

Today’s world demands more efficient learning models that allow students to play a more active role in their education. Technology is having an impact on how instruction is delivered and how information is found and share. Until very recently, the educational models encouraged memorization as an essential learning skill. These days, technologies have changed the educational model and access to information. Knowledge is available online, mostly free, and easily accessible. Reading, sharing, listening and, doing are currently necessary skills for education. Mobile devices have become a complete set of applications, support, and help for educational organizations. By conducting an analysis of the behavior and use of mobile devices on current students, efficient educational applications can be developed. Although there are several initiatives for the use of mobile learning in education, there are also issues linked to this technology that must be addressed. In this work, we present the results of a literature review of mobile learning; the findings described are the result of the analysis of several articles obtained in three scientific repositories. This work also lists certain issues that, if properly addressed, can avoid possible complications to the implementation of this technology in education.This work was supported by the EduTech project (609785-EPP-1-2019-1-ES-EPPKA2-CBHEJP) co-funded by the Erasmus+ Programme of the European Union

Employability skill development in work-integrated learning: Barriers and best practice

Work-integrated learning (WIL) is widely considered instrumental in equipping new graduates with the required employability skills to function effectively in the work environment. Evaluation of WIL programs in enhancing skill development remains predominantly outcomes-focused with little attention to the process of what, how and from whom students acquire essential skills during work placement. This paper investigates best practice in the classroom and placement activities which develop employability skills and identifies factors impeding skill performance during WIL, based on survey data from 131 undergraduates across different disciplines in an Australian university. What students actually experienced during placement, or what they felt was important to their learning, broadly aligns with best practice principles for WIL programs and problems experienced in performing certain skills during placement can be largely attributed to poor design. Implications for academic and professional practitioners are discussed

Techniques for calculating software product metrics threshold values: A systematic mapping study

Several aspects of software product quality can be assessed and measured using product metrics. Without software metric threshold values, it is difficult to evaluate different aspects of quality. To this end, the interest in research studies that focus on identifying and deriving threshold values is growing, given the advantage of applying software metric threshold values to evaluate various software projects during their software development life cycle phases. The aim of this paper is to systematically investigate research on software metric threshold calculation techniques. In this study, electronic databases were systematically searched for relevant papers; 45 publications were selected based on inclusion/exclusion criteria, and research questions were answered. The results demonstrate the following important characteristics of studies: (a) both empirical and theoretical studies were conducted, a majority of which depends on empirical analysis; (b) the majority of papers apply statistical techniques to derive object-oriented metrics threshold values; (c) Chidamber and Kemerer (CK) metrics were studied in most of the papers, and are widely used to assess the quality of software systems; and (d) there is a considerable number of studies that have not validated metric threshold values in terms of quality attributes. From both the academic and practitioner points of view, the results of this review present a catalog and body of knowledge on metric threshold calculation techniques. The results set new research directions, such as conducting mixed studies on statistical and quality-related studies, studying an extensive number of metrics and studying interactions among metrics, studying more quality attributes, and considering multivariate threshold derivation. 2021 by the authors. Licensee MDPI, Basel, Switzerland.Funding: Authors thanks to the Molde University College-Specialized Univ. in Logistics, Norway for the support of Open access fund.Scopus2-s2.0-8512089773

Reducing the effort for systematic reviews in software engineering

Context: Systematic Reviews (SRs) are means for collecting and synthesizing evidence from the identification and analysis of relevant studies from multiple sources. To this aim, they use a well-defined methodology meant to mitigate the risks of biases and ensure repeatability for later updates. SRs, however, involve significant effort. Goal: The goal of this paper is to introduce a novel methodology that reduces the amount of manual tedious tasks involved in SRs while taking advantage of the value provided by human expertise. Method: Starting from current methodologies for SRs, we replaced the steps of keywording and data extraction with an automatic methodology for generating a domain ontology and classifying the primary studies. This methodology has been applied in the Software Engineering sub-area of Software Architecture and evaluated by human annotators. Results: The result is a novel Expert-Driven Automatic Methodology, EDAM, for assisting researchers in performing SRs. EDAM combines ontology-learning techniques and semantic technologies with the human-in-the-loop. The first (thanks to automation) fosters scalability, objectivity, reproducibility and granularity of the studies; the second allows tailoring to the specific focus of the study at hand and knowledge reuse from domain experts. We evaluated EDAM on the field of Software Architecture against six senior researchers. As a result, we found that the performance of the senior researchers in classifying papers was not statistically significantly different from EDAM. Conclusions: Thanks to automation of the less-creative steps in SRs, our methodology allows researchers to skip the tedious tasks of keywording and manually classifying primary studies, thus freeing effort for the analysis and the discussion