{"title":"An ISO/IEC 25010 Based Software Quality Assessment of a Faculty Research Productivity Monitoring and Prediction System","authors":"Ranie B. Canlas, K. Piad, A. Lagman","doi":"10.1145/3512576.3512619","DOIUrl":null,"url":null,"abstract":"A known primary indicator of performance of academic institutions is the productivity of their academic personnel in terms of research outputs. Monitoring the outputs of faculty requires systematic and technology-based methods for easy access and creation of repository. This study generally aimed to provide solution in monitoring the research undertakings of faculty through the development of a system for effective and efficient management of research outputs. Specifically, it tried to identify necessary features that can be integrated in the development of research productivity monitoring and prediction system; assess system performance based from the parameters of ISO/IEC 25010 Software Quality Model; and identify differences on the assessment of the respondents in terms of evaluation of software quality. The key features of the developed system include support submission of paper proposals, review and approval of proposal, monitoring of ongoing approved papers, utilization of research outputs, research outputs repository and predictive analysis. The assessment of the expert-respondents resulted to a grand mean of 3.87 which corresponds to a verbal interpretation of “Strongly Agree”. Results showed that the system has the necessary features in determining research productivity of faculty along with the high evaluation of system performance based from the assessment of expert-respondents.","PeriodicalId":278114,"journal":{"name":"Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3512576.3512619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A known primary indicator of performance of academic institutions is the productivity of their academic personnel in terms of research outputs. Monitoring the outputs of faculty requires systematic and technology-based methods for easy access and creation of repository. This study generally aimed to provide solution in monitoring the research undertakings of faculty through the development of a system for effective and efficient management of research outputs. Specifically, it tried to identify necessary features that can be integrated in the development of research productivity monitoring and prediction system; assess system performance based from the parameters of ISO/IEC 25010 Software Quality Model; and identify differences on the assessment of the respondents in terms of evaluation of software quality. The key features of the developed system include support submission of paper proposals, review and approval of proposal, monitoring of ongoing approved papers, utilization of research outputs, research outputs repository and predictive analysis. The assessment of the expert-respondents resulted to a grand mean of 3.87 which corresponds to a verbal interpretation of “Strongly Agree”. Results showed that the system has the necessary features in determining research productivity of faculty along with the high evaluation of system performance based from the assessment of expert-respondents.