SELECTION AND REVIEW OF MEASUREMENT ITEM OF STUDENTS’ LEARNING ENVIRONMENT

The learning environment plays important roles in the cognitive, effective and social students. Reviewing the learning environment is given due attention to this day because of its importance in helping to improve learning outcomes. This study will look at the selection and review of the measurement items of learning environment factors in Technical Institutions in the country. Variables to be examined in this study are assessment, teaching approaches, learning community, learning resources, work load, the clear objectives. Respondents consisted of 455 final semester engineering students. Data were analyzed descriptively for reliability (Cronbach Alpha values) and factor analysis was used to obtain 6 factor solutions (Eigenvalues and KMO) using SPSS 17 software. Results showed that 6 factor solutions with Eigen values above 1.0. The value of Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.868> 0.6 is adequate for inter-correlation while Barlett Test was significant(Chi Square = 5962.485, p <0.05). The anti-image correlation matrix by The Measure of Sampling Adequacy (MSA) is more than the value of 0.5. Items O2, PP6, PP7, PP5, P1, SP3 and SP4 dropped based on the criteria by Hair et al (2006), where each item should exceed the value of 0.50. Total variance explained for this loading was 61.51%assessment, teaching approach, learning community, learning resources, work load, clear objectives

Sustainability and interoperability: An economic study on BIM implementation by a small Civil Engineering firm

[EN] Sustainability and interoperability are two closely related concepts. By analyzing the three fundamental facets of sustainability-economic, ecological and ethical/social-it is easier to address their connection with the concept of interoperability. This paper focuses on the economic aspect, in the field of civil engineering. In this area, due to the local nature of many of the software tools used, interoperability problems are frequent, with few studies addressing the economic impact of this, especially in small engineering firms. The main contribution of this paper is a design methodology for linear works based on the federation of building information modelling (BIM) models created with different software tools, conceived to break the interoperability issues between these applications. As an example, this methodology is applied to a mountain road widening project. A detailed economic analysis of the application of this methodology by an engineering Spanish firm reveals the important cost reductions that the integration of the software tools provides versus the prior practices.The authors wish to acknowledge support from ISTRAM, CivileStudio and the engineering firm for the information provided.Aranda Domingo, JÁ.; Martin-Dorta, N.; Naya Sanchis, F.; Conesa-Pastor, J.; Contero, M. (2020). Sustainability and interoperability: An economic study on BIM implementation by a small Civil Engineering firm. Sustainability. 12(22):1-16. https://doi.org/10.3390/su12229581S1161222Grilo, A., & Jardim-Goncalves, R. (2010). Value proposition on interoperability of BIM and collaborative working environments. Automation in Construction, 19(5), 522-530. doi:10.1016/j.autcon.2009.11.003Bynum, P., Issa, R. R. A., & Olbina, S. (2013). Building Information Modeling in Support of Sustainable Design and Construction. Journal of Construction Engineering and Management, 139(1), 24-34. doi:10.1061/(asce)co.1943-7862.0000560BuildingSMART Internationalhttps://www.buildingsmart.org/Modelos digitales del terreno: Introducción y aplicaciones a las ciencias ambientales. Oviedo Univ. Oviedo 1994, 118http://www.etsimo.uniovi.es/~feliBaltsavias, E. P. (1999). A comparison between photogrammetry and laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2-3), 83-94. doi:10.1016/s0924-2716(99)00014-3Hirpa, D., Hare, W., Lucet, Y., Pushak, Y., & Tesfamariam, S. (2016). A bi-objective optimization framework for three-dimensional road alignment design. Transportation Research Part C: Emerging Technologies, 65, 61-78. doi:10.1016/j.trc.2016.01.016Yepes, V., Alcala, J., Perea, C., & González-Vidosa, F. (2008). A parametric study of optimum earth-retaining walls by simulated annealing. Engineering Structures, 30(3), 821-830. doi:10.1016/j.engstruct.2007.05.023Nehate, G., & Rys, M. (2006). 3D Calculation of Stopping-Sight Distance from GPS Data. Journal of Transportation Engineering, 132(9), 691-698. doi:10.1061/(asce)0733-947x(2006)132:9(691)Borga, M., Tonelli, F., & Selleroni, J. (2004). A physically based model of the effects of forest roads on slope stability. Water Resources Research, 40(12). doi:10.1029/2004wr003238Vanmarcke, E. H. (1977). Reliability of Earth Slopes. Journal of the Geotechnical Engineering Division, 103(11), 1247-1265. doi:10.1061/ajgeb6.0000518Istram Softwarehttps://www.istram.netCivileStudio Softwarehttps://www.civilestudio.comBates, P. ., & De Roo, A. P. . (2000). A simple raster-based model for flood inundation simulation. Journal of Hydrology, 236(1-2), 54-77. doi:10.1016/s0022-1694(00)00278-xBryde, D., Broquetas, M., & Volm, J. M. (2013). The project benefits of Building Information Modelling (BIM). International Journal of Project Management, 31(7), 971-980. doi:10.1016/j.ijproman.2012.12.001Ghaffarianhoseini, A., Tookey, J., Ghaffarianhoseini, A., Naismith, N., Azhar, S., Efimova, O., & Raahemifar, K. (2017). Building Information Modelling (BIM) uptake: Clear benefits, understanding its implementation, risks and challenges. Renewable and Sustainable Energy Reviews, 75, 1046-1053. doi:10.1016/j.rser.2016.11.083Love, P. E. D., & Matthews, J. (2019). The ‘how’ of benefits management for digital technology: From engineering to asset management. Automation in Construction, 107, 102930. doi:10.1016/j.autcon.2019.102930Shin, M., Lee, H., & Kim, H. (2018). Benefit–Cost Analysis of Building Information Modeling (BIM) in a Railway Site. Sustainability, 10(11), 4303. doi:10.3390/su10114303Barlish, K., & Sullivan, K. (2012). How to measure the benefits of BIM — A case study approach. Automation in Construction, 24, 149-159. doi:10.1016/j.autcon.2012.02.008Ham, N., Moon, S., Kim, J.-H., & Kim, J.-J. (2018). Economic Analysis of Design Errors in BIM-Based High-Rise Construction Projects: Case Study of Haeundae L Project. Journal of Construction Engineering and Management, 144(6), 05018006. doi:10.1061/(asce)co.1943-7862.0001498Hong, Y., Hammad, A. W. A., Akbarnezhad, A., & Arashpour, M. (2020). A neural network approach to predicting the net costs associated with BIM adoption. Automation in Construction, 119, 103306. doi:10.1016/j.autcon.2020.10330

Usability Inspection in Model-Driven Web Development: Empirical Validation in WebML

There is a lack of empirically validated usability evaluation methods that can be applied to models in model-driven Web development. Evaluation of these models allows an early detection of usability problems perceived by the end-user. This motivated us to propose WUEP, a usability inspection method which can be integrated into different model-driven Web development processes. We previously demonstrated how WUEP can effectively be used when following the Object-Oriented Hypermedia method. In order to provide evidences about WUEP’s generalizability, this paper presents the operationalization and empirical validation of WUEP into another well-known method: WebML. The effectiveness, efficiency, perceived ease of use, and satisfaction of WUEP were evaluated in comparison to Heuristic Evaluation (HE) from the viewpoint of novice inspectors. The results show that WUEP was more effective and efficient than HE when detecting usability problems on models. Also, inspectors were satisfied when applying WUEP, and found it easier to use than HE.Fernández Martínez, A.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE.; Matera, M. (2013). Usability Inspection in Model-Driven Web Development: Empirical Validation in WebML. Lecture Notes in Computer Science. 8107:740-756. doi:10.1007/978-3-642-41533-3_457407568107Abrahão, S., Iborra, E., Vanderdonckt, J.: Usability Evaluation of User Interfaces Generated with a Model-Driven Architecture Tool. In: Maturing Usability: Quality in Software, Interaction and Value, pp. 3–32. Springer (2007)Atterer, R., Schmidt, A.: Adding Usability to Web Engineering Models and Tools. In: Lowe, D.G., Gaedke, M. (eds.) ICWE 2005. LNCS, vol. 3579, pp. 36–41. Springer, Heidelberg (2005)Basili, V., Rombach, H.: The TAME Project: Towards Improvement-Oriented Software Environments. IEEE Transactions on Software Engineering 14(6), 758–773 (1988)Briand, L., Labiche, Y., Di Penta, M., Yan-Bondoc, H.: An experimental investigation of formality in UML-based development. IEEE TSE 31(10), 833–849 (2005)Carifio, J., Perla, R.: Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes. Journal of Social Sciences 3(3), 106–116 (2007)Ceri, S., Fraternali, P., Bongio, A.: Web modeling language (WebML): a modeling language for designing Web sites. In: 9th International World Wide Web Conference, pp. 137–157 (2000)Ceri, S., Fraternali, P., Acerbis, R., Bongio, A., Butti, S., Ciapessoni, F., Conserva, C., Elli, R., Greppi, C., Tagliasacchi, M., Toffetti, G.: Architectural issues and solutions in the development of data-intensive Web applications. In: Proceedings of the 1st Biennial Conference on Innovative Data Systems Research, Asilomar, CA (2003)Conte, T., Massollar, J., Mendes, E., Travassos, G.H.: Usability Evaluation Based on Web Design Perspectives. In: Proceedings of the International Symposium on Empirical Software Engineering and Measurement (ESEM 2007), pp. 146–155 (2007)Fernandez, A., Insfran, E., Abrahão, S.: Usability evaluation methods for the Web: a systematic mapping study. Information and Software Technology 53, 789–817 (2011)Fernandez, A., Abrahão, S., Insfran, E.: A Web usability evaluation process for model-driven Web development. In: Mouratidis, H., Rolland, C. (eds.) CAiSE 2011. LNCS, vol. 6741, pp. 108–122. Springer, Heidelberg (2011)Fernandez, A., Abrahão, S., Insfran, E., Matera, M.: Further Analysis on the Validation of a Usability Inspection Method for Model-Driven Web Development. In: 6th International Symposium on Empirical Software Engineering and Measurement (ESEM 2012), pp. 153–156 (2012)Fernandez, A., Abrahão, S., Insfran, E.: Empirical Validation of a Usability Inspection Method for Model-Driven Web Development. Journal of Systems and Software 86, 161–186 (2013)Fraternali, P., Matera, M., Maurino, A.: WQA: an XSL Framework for Analyzing the Quality of Web Applications. In: Proceedings of IWWOST 2002 - ECOOP 2002 Workshop, Malaga, Spain (2002)Hornbæk, K.: Dogmas in the assessment of usability evaluation methods. Behaviour & Information Technology 29(1), 97–111 (2010)Hwang, W., Salvendy, G.: Number of people required for usability evaluation: the 10±2 rule. Communications of the ACM 53(5), 130–113 (2010)International Organization for Standardization: ISO/IEC 25000, Software Engineering – Software Product Quality Requirements and Evaluation (SQuaRE) – Guide to SQuaRE (2005)Juristo, N., Moreno, A.M.: Basics of Software Engineering Experimentation. Kluwer Academic Publishers (2001)Juristo, N., Moreno, A., Sanchez-Segura, M.I.: Guidelines for eliciting usability functionalities. IEEE Transactions on Software Engineering 33(11), 744–758 (2007)Matera, M., Costabile, M.F., Garzotto, F., Paolini, P.: SUE inspection: an effective method for systematic usability evaluation of hypermedia. IEEE Transactions on Systems, Man, and Cybernetics, Part A 32(1), 93–103 (2002)Matera, M., Rizzo, F., Carughi, G.: Web Usability: Principles and Evaluation Methods. In: Web Engineering, pp. 143–180. Springer (2006)Maxwell, K.: Applied Statistics for Software Managers. Software Quality Institute Series. Prentice Hall (2002)Molina, F., Toval, A.: Integrating usability requirements that can be evaluated in design time into Model Driven Engineering of Web Information Systems. Advances in Engineering Software 40(12), 1306–1317 (2009)Moreno, N., Vallecillo, A.: Towards interoperable Web engineering methods. 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Estimation Procedures and TFP Analysis of the JIP Database 2006 Provisional Version

(Introduction) The purpose of this paper is to explain the preliminary version of the newly compiled Japan Industrial Productivity Database (JIP 2006) and report some results of our growth accounting analysis based on this database. The JIP 2006 contains information on 108 sectors from 1970 to 2002 that can be used for total factor productivity analyses. These sectors cover the whole Japanese economy. The JIP Database was compiled as part of the RIETI (Research Institute of Economy, Trade and Industry) research project "Study on Industry-Level and Firm-Level Productivity in Japan." The original version of the JIP Database (ESRI/Hi-Stat JIP Database 2003) was compiled in a collaboration between ESRI (Economic and Social Research Institute, Cabinet Office, Government of Japan) as part of its research project on "Japan's Potential Growth" and Hitotsubashi University as part of its Hi-Stat project (A 21st-Century COE Program, Research Unit for Statistical Analysis in the Social Sciences). The authors are grateful to ESRI and members of the Hi-Stat team for the support and cooperation provided for our present RIETI project. At this moment, the major data available are sectoral capital service input indices and labor service input indices, including information on real capital stocks and the nominal cost of capital by type of capital and by industry, the nominal and real values of sectoral gross output and intermediate input, as well as some supplementary tables, such as statistics on trade, inward and outward FDI, and Japan's industrial structure. All real values are based on 1995 prices. For growth accounting, nominal labor costs and nominal capital services for 108 industries are also estimated. The sum of these two values for each industry is not adjusted to be equal to the value added of that industry at factor cost base. The final version of the JIP 2006 is scheduled to be released by November, 2006. The final version will include nominal and real annual input-output tables, detailed information on ICT capital services and some additional statistics, such as R&D stocks and capacity utilization rates at the detailed sectoral level. For scholars familiar with the JIP 2003, we here briefly summarize the main differences between and the main similarities of the 2006 and 2003 versions of the JIP. 1. The JIP 2003 is based on the 1968 SNA, while the JIP 2006 is based on the 1993 SNA. The capital stock of the JIP 2006 includes order-made software, plant engineering, and assets accumulated by the search for minerals. The JIP 2003 uses SNA statistics as control totals. Following Japan's present SNA statistics, capital stock in the preliminary version of the JIP 2006 does not include prepackaged and in-house software. However, the final version of the JIP 2006 will include two sets of statistics, one in which capital stock does not include prepackaged and in-house software and one in which it does. 2. In the case of the JIP 2006, labor input data include detailed information on labor input cross-classified by categories of labor. The paper is organized as follows: In the next section, we report the estimation procedures of our annual input-output tables. In Sections 2 and 3, we explain the capital service input data and the labor input data of the JIP 2006, respectively. Finally, in Section 4, we analyze Japan's sectoral and macro TFP growth.

WEAK MEASUREMENT THEORY AND MODIFIED COGNITIVE COMPLEXITY MEASURE

Measurement is one of the problems in the area of software engineering. Since traditional measurement theory has a major problem in defining empirical observations on software entities in terms of their measured quantities, Morasca has tried to solve this problem by proposing Weak Measurement theory. In this paper, we tried to evaluate the applicability of weak measurement theory by applying it on a newly proposed Modified Cognitive Complexity Measure (MCCM). We also investigated the applicability of Weak Extensive Structure for deciding on the type of scale for MCCM. It is observed that the MCCM is on weak ratio scale

Requirements Prioritization Based on Benefit and Cost Prediction: An Agenda for Future Research

In early phases of the software cycle, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper presents results of a systematic review of literature, which investigates how existing methods approach the problem of requirements prioritization based on benefit and cost. From this review, it derives a set of under-researched issues which warrant future efforts and sketches an agenda for future research in this area

Automatic Software Repair: a Bibliography

This article presents a survey on automatic software repair. Automatic software repair consists of automatically finding a solution to software bugs without human intervention. This article considers all kinds of repairs. First, it discusses behavioral repair where test suites, contracts, models, and crashing inputs are taken as oracle. Second, it discusses state repair, also known as runtime repair or runtime recovery, with techniques such as checkpoint and restart, reconfiguration, and invariant restoration. The uniqueness of this article is that it spans the research communities that contribute to this body of knowledge: software engineering, dependability, operating systems, programming languages, and security. It provides a novel and structured overview of the diversity of bug oracles and repair operators used in the literature

Deriving Models for Software Project Effort Estimation By Means of Genetic Programming

Software engineering, effort estimation, genetic programming, symbolic regression. This paper presents the application of a computational intelligence methodology in effort estimation for software projects. Namely, we apply a genetic programming model for symbolic regression; aiming to produce mathematical expressions that (1) are highly accurate and (2) can be used for estimating the development effort by revealing relationships between the project’s features and the required work. We selected to investigate the effectiveness of this methodology into two software engineering domains. The system was proved able to generate models in the form of handy mathematical expressions that are more accurate than those found in literature.