|
UPSI Digital Repository (UDRep)
|
|
| ||||||||||||||||||||||||||
| Abstract : Universiti Pendidikan Sultan Idris |
| Ranking the strengths and weaknesses of software engineering students in software development life cycle (SDLC) process level is a challenging task owing to (1) data variation, (2) multievaluation criteria, (3) criterion importance and (4) alternative member importance. According to the existing literature, no specified procedure can rank the ability of software engineering students based on SDLC process levels to figure out the strengths and weaknesses of each student. This study aims to present a novel triplex procedure for ranking the ability of software engineering students to address the literature gap. The methodology of the proposed work is presented on the basis of three phases. In the identification phase, four steps are implemented, namely, processing dataset, identifying the criteria, distributing the courses to the software engineering body of knowledge and proposing the pre-decision matrix (DM). The data comprise the GPA and soft skills from 60 software engineering students who graduated from Universiti Pendidikan Sultan Idris in 2016. In the pre-processing phase, three steps are involved as follows. Analytic hierarchy process (AHP) is first used to assign weights to the courses and then multiply the assigned weight by courses, which is the first procedure in the proposed work. In this phase, the construction of DM is presented based on multimeasurement criteria (GPA and soft skills), with SDLC process levels as alternatives. In the development phase, AHP is used again to weight the multimeasurement criteria, and this is the second procedure. In such case, the coordinator and head of the software engineering department are consulted to obtain subjective judgments for each criterion. Technique for order performance by similarity to ideal solution (TOPSIS) is then used to rank the students, which is the third procedure. In the validation, statistical analysis is performed to validate the results by checking the accuracy of the systematic ranking. Results show that (1) integrating AHP and group TOPSIS is suitable for ranking the ability of students. (2) The 60 students are categorized into five ranking groups based on their strength level: 14 collector requirements, 13 designers, 5 programmers, 13 testers and 15 maintenances. (3) Significant differences are observed between the groups' scores for each level of SDLC, indicating that the ranking results are identical for all levels. ? 2021 World Scientific Publishing Company. |
| References |
Abdeljaber, H. A. M., & Ahmad, S. (2017). Program outcomes assessment method for multi- academic accreditation bodies: Computer science program as a case study. International Journal of Emerging Technologies in Learning, 12(5), 23-35. doi:10.3991/ijet.v12i05.6410 Abdullateef, B. N., Elias, N. F., Mohamed, H., Zaidan, A. A., & Zaidan, B. B. (2016). An evaluation and selection problems of OSS-LMS packages. SpringerPlus, 5(1), 1-35. doi:10.1186/s40064-016-1828-y Abdullateef, B. N., Elias, N. F., Mohamed, H., Zaidan, A. A., & Zaidan, B. B. (2016). An evaluation and selection problems of OSS-LMS packages. SpringerPlus, 5(1), 1-35. doi:10.1186/s40064-016-1828-y Aruldoss, M., Lakshmi, T. M., & Venkatesan, V. P. (2013). A survey on multi criteria decision making methods and its applications. American Journal of Information Systems, 1(1), 31-43. Retrieved from www.scopus.com Baneres, D. (2017). Towards a particular prediction system to evaluate student’s success doi:10.1007/978-3-319-49109-7_91 Retrieved from www.scopus.com Barrios, M. A. O., De Felice, F., Negrete, K. P., Romero, B. A., Arenas, A. Y., & Petrillo, A. (2016). An AHP-topsis integrated model for selecting the most appropriate tomography equipment. International Journal of Information Technology and Decision Making, 15(4), 861-885. doi:10.1142/S021962201640006X Beikkhakhian, Y., Javanmardi, M., Karbasian, M., & Khayambashi, B. (2015). The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods. Expert Systems with Applications, 42(15-16), 6224-6236. doi:10.1016/j.eswa.2015.02.035 Bennett, C. (2016). Assessment rubrics: Thinking inside the boxes. Learn.Teaching, 9(1), 50-72. Retrieved from www.scopus.com Bezerra, R. M. M., Da Silva, F. Q. B., Santana, A. M., Magalhaes, C. V. C., & Santos, R. E. S. (2015). Replication of empirical studies in software engineering: An update of a systematic mapping study. Paper presented at the International Symposium on Empirical Software Engineering and Measurement, , 2015-November 132-135. doi:10.1109/ESEM.2015.7321213 Retrieved from www.scopus.com Bourque, P., Robert, F., Lavoie, J. M., Lee, A., Trudel, S., & Lethbridge, T. C. (2002). Guide to the software engineering body of knowledge (SWEBOK) and the software engineering education knowledge (SEEK) - A preliminary mapping. Paper presented at the Proceedings - 10th International Workshop on Software Technology and Engineering Practice, STEP 2002, 8-23. doi:10.1109/STEP.2002.1267595 Retrieved from www.scopus.com Cain, A. (2013). Developing assessment criteria for portfolio assessed introductory programming. Paper presented at the Proceedings of 2013 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2013, 55-60. doi:10.1109/TALE.2013.6654399 Retrieved from www.scopus.com Çalişkan, H. (2013). Selection of boron based tribological hard coatings using multi-criteria decision making methods. Materials and Design, 50, 742-749. doi:10.1016/j.matdes.2013.03.059 Chandrasekaran, S., Long, J. M., & Joordens, M. A. (2015). Evaluation of student learning outcomes in fourth year engineering mechatronics through design based learning curriculum. Paper presented at the Proceedings - Frontiers in Education Conference, FIE, , 2015 doi:10.1109/FIE.2015.7344384 Retrieved from www.scopus.com Damaj, I., & Yousafzai, J. (2016). Simple and accurate student outcomes assessment: A unified approach using senior computer engineering design experiences. Paper presented at the IEEE Global Engineering Education Conference, EDUCON, , 10-13-April-2016 204-211. doi:10.1109/EDUCON.2016.7474554 Retrieved from www.scopus.com Demir, K. A. (2015). Requirements for systems development life cycle models for large-scale defense systems. Journal of Defense Resources Management, 6(2) Retrieved from www.scopus.com Deni, W., Sudana, O., & Sasmita, A. (2013). Analysis and implementation fuzzy multi-attribute decision making SAW method for selection of high achieving students in faculty level. International Journal of Computer Science, 10(1), 674-680. Retrieved from www.scopus.com Felemban, S., Gardner, M., & Callaghan, V. (2017). An event detection approach for identifying learning evidence in collaborative virtual environments. Paper presented at the 2016 8th Computer Science and Electronic Engineering Conference, CEEC 2016 - Conference Proceedings, 42-47. doi:10.1109/CEEC.2016.7835886 Retrieved from www.scopus.com Godfrey, B. (2000). Emergency medical guidelines. Sunshine Act of Florida, Retrieved from www.scopus.com Guelfi, N., Capozucca, A., & Ries, B. (2016). Measuring the SWEBOK Coverage: An Approach and a Tool, Retrieved from www.scopus.com Guelfi, N., Capozucca, A., & Ries, B. (2017). A product line of software engineering project courses. 30th Int.Conf.Software Engineering Education and Training, Retrieved from www.scopus.com Gurupur, V. P., Pankaj Jain, G., & Rudraraju, R. (2015). Evaluating student learning using concept maps and markov chains. Expert Systems with Applications, 42(7), 3306-3314. doi:10.1016/j.eswa.2014.12.016 Hamidi, S. R., Shaffiei, Z. A., Sarif, S. M., & Ashar, N. (2013). Exploratory study of assessment in teaching and learning. Paper presented at the International Conference on Research and Innovation in Information Systems, ICRIIS, 398-403. doi:10.1109/ICRIIS.2013.6716743 Retrieved from www.scopus.com Hyun, K. -., Min, S., Choi, H., Park, J., & Lee, I. -. (2015). Risk analysis using fault-tree analysis (FTA) and analytic hierarchy process (AHP) applicable to shield TBM tunnels. Tunnelling and Underground Space Technology, 49, 121-129. doi:10.1016/j.tust.2015.04.007 Ingoley, S. N., & Bakal, J. W. (2013). Evaluating students' performance using four-node fuzzy controller. Paper presented at the 2013 Nirma University International Conference on Engineering, NUiCONE 2013, doi:10.1109/NUiCONE.2013.6780063 Retrieved from www.scopus.com Jumaah, F. M., Zadain, A. A., Zaidan, B. B., Hamzah, A. K., & Bahbibi, R. (2018). Decision-making solution based multi-measurement design parameter for optimization of GPS receiver tracking channels in static and dynamic real-time positioning multipath environment. Measurement: Journal of the International Measurement Confederation, 118, 83-95. doi:10.1016/j.measurement.2018.01.011 Jumaah, F. M., Zaidan, A. A., Zaidan, B. B., Bahbibi, R., Qahtan, M. Y., & Sali, A. (2018). Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers. Telecommunication Systems, 68(3), 425-443. doi:10.1007/s11235-017-0401-5 Kajko-Mattsson, M. (2012). A method for designing software engineering educational programs. Paper presented at the Proceedings - 2012 25th IEEE Conference on Software Engineering Education and Training, CSEE and T 2012, 139-143. doi:10.1109/CSEET.2012.34 Retrieved from www.scopus.com Kakani, B., Dalal, D., & Dabhi, A. (2016). Improved solution on students answer sheet assessment using fuzzy rules. Paper presented at the Conference on Advances in Signal Processing, CASP 2016, 435-439. doi:10.1109/CASP.2016.7746210 Retrieved from www.scopus.com Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., Albahri, O. S., & Albahri, A. S. (2018). Based on real time remote health monitoring systems: A new approach for prioritization “Large scales data” patients with chronic heart diseases using body sensors and communication technology. Journal of Medical Systems, 42(4) doi:10.1007/s10916-018-0916-7 Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., Albahri, O. S., & Albahri, A. S. (2018). Based on real time remote health monitoring systems: A new approach for prioritization “Large scales data” patients with chronic heart diseases using body sensors and communication technology. Journal of Medical Systems, 42(4) doi:10.1007/s10916-018-0916-7 Kandakoglu, A., Celik, M., & Akgun, I. (2009). A multi-methodological approach for shipping registry selection in maritime transportation industry. Mathematical and Computer Modelling, 49(3-4), 586-597. doi:10.1016/j.mcm.2008.09.001 Kissel, R., Stine, K., Scholl, M., Rossman, H., Fahlsing, J., & Gulick, J. (2008). Security considerations in the system development life cycle. Security Considerations in the System Development Life Cycle, Retrieved from www.scopus.com Kron, F. W., Fetters, M. D., Scerbo, M. W., White, C. B., Lypson, M. L., Padilla, M. A., . . . Becker, D. M. (2017). Using a computer simulation for teaching communication skills: A blinded multisite mixed methods randomized controlled trial. Patient Education and Counseling, 100(4), 748-759. doi:10.1016/j.pec.2016.10.024 Leau, Y. B., Loo, W. K., Tham, W. Y., & Tan, S. F. (2012). Software development life cycle AGILE vs traditional approaches. International Conference on Information and Network Technology, 37(1), 162-167. Retrieved from www.scopus.com Lesmes, D., Castillo, M., & Zarama, R. (2009). Application of the analytic network process (ANP) to establish weights in order to re-accredit a program of a university. Proceedings of the International Symposium on the Analytic Hierarchy Process, , 1-14. Retrieved from www.scopus.com Leyva Lopez, J. C. (2005). Multicriteria decision aid application to a student selection problem. Pesquisa Operacional, 25(1), 45-68. Retrieved from www.scopus.com Macek, O., & Komárek, M. (2012). Evaluation of student teamwork. Paper presented at the Proceedings - 2012 25th IEEE Conference on Software Engineering Education and Training, CSEE and T 2012, 130-133. doi:10.1109/CSEET.2012.23 Retrieved from www.scopus.com Mahboob, T., Irfan, S., & Karamat, A. (2017). A machine learning approach for student assessment in E-learning using quinlan's C4.5, naive bayes and random forest algorithms. Paper presented at the Proceedings of the 2016 19th International Multi-Topic Conference, INMIC 2016, doi:10.1109/INMIC.2016.7840094 Retrieved from www.scopus.com Molins-Ruano, P., Rodriguez, P., Atrio, S., & Sacha, G. M. (2016). Modelling experts' behavior with e-valUAM to measure computer science skills. Computers in Human Behavior, 61, 378-385. doi:10.1016/j.chb.2016.03.044 Mollaghasemi, M., & Pet-Edwards, J. (1997). Making Multiple-Objective Decisions, Retrieved from www.scopus.com Myers, J. A., Vigneswaran, Y., Gabryszak, B., Fogg, L. F., Francescatti, A. B., Golner, C., & Bines, S. D. (2014). NBME subject examination in surgery scores correlate with surgery clerkship clinical experience. Journal of Surgical Education, 71(2), 205-210. doi:10.1016/j.jsurg.2013.07.003 Nilsson, H., Nordström, E. -., & Öhman, K. (2016). Decision support for participatory forest planning using AHP and TOPSIS. Forests, 7(5) doi:10.3390/f7050100 O'Brocta, R., & Swigart, S. (2013). Student perceptions of a top 200 medication course utilizing active learning techniques. Currents in Pharmacy Teaching and Learning, 5(1), 49-53.e2. doi:10.1016/j.cptl.2012.09.001 Ortíz, M. A., Cómbita, J. P., La De Hoz, Á. A., De Felice, F., & Petrillo, A. (2016). An integrated approach of AHP-DEMATEL methods applied for the selection of allied hospitals in outpatient service. International Journal of Medical Engineering and Informatics, 8(2), 87-107. doi:10.1504/IJMEI.2016.075760 Qader, M. A., Zaidan, B. B., Zaidan, A. A., Ali, S. K., Kamaluddin, M. A., & Radzi, W. B. (2017). A methodology for football players selection problem based on multi-measurements criteria analysis. Measurement: Journal of the International Measurement Confederation, 111, 38-50. doi:10.1016/j.measurement.2017.07.024 Qaradaghi, M. (2016). Investigation of Multi-Criteria Decision Consistency: A Triplex Approach to Optimal Oilfield Portfolio Investment Decisions, Retrieved from www.scopus.com Radack, S. (2009). System development life cycle. National Institute of Standards and Technology, Retrieved from www.scopus.com Rahmatullah, B., Zaidan, A. A., Mohamed, F., & Sali, A. (2017). Multi-complex attributes analysis for optimum GPS baseband receiver tracking channels selection. Paper presented at the 2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017, , 2017-January 1084-1088. doi:10.1109/CoDIT.2017.8102743 Retrieved from www.scopus.com Ren, J., & Sovacool, B. K. (2015). Prioritizing low-carbon energy sources to enhance china's energy security. Energy Conversion and Management, 92, 129-136. doi:10.1016/j.enconman.2014.12.044 Roszkowska, E. (2013). Rank ordering criteria weighting methods-A comparative overview. Optimum.Studia Ekonomiczne, 5(65), 14-33. Retrieved from www.scopus.com Rowntree, D. (1987). Assessing Students: How Shall we Know them?, Retrieved from www.scopus.com Saaty, T. L. (1980). The Analytic Hierarchy Process, Retrieved from www.scopus.com Saaty, T. L., & Ozdemir, M. S. (2003). Why the magic number seven plus or minus two. Mathematical and Computer Modelling, 38(3-4), 233-244. doi:10.1016/S0895-7177(03)90083-5 Salman, O. H., Zaidan, A. A., Zaidan, B. B., Naserkalid, & Hashim, M. (2017). Novel methodology for triage and prioritizing using "big data" patients with chronic heart diseases through telemedicine environmental. International Journal of Information Technology and Decision Making, 16(5), 1211-1245. doi:10.1142/S0219622017500225 San Miguel, C., & Rogan, F. (2015). Assessing students' english language proficiency during clinical placement: A qualitative evaluation of a language framework. Nurse Education Today, 35(6), 771-776. doi:10.1016/j.nedt.2015.02.014 Sarwar Sindhu, M., Rashid, T., & Kashif, A. (2019). Modeling of linear programming and extended TOPSIS in decision making problem under the framework of picture fuzzy sets. PLoS ONE, 14(8) doi:10.1371/journal.pone.0220957 Sharma, K. K., Banerjee, K., Mandal, C., & Vikas, I. (2016). A benchmark programming assignment suite for quantitative analysis of student performance in early programming courses. Paper presented at the Proceedings of the 2015 IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education, MITE 2015, 199-203. doi:10.1109/MITE.2015.7375314 Retrieved from www.scopus.com Shen, K. -., & Wang, J. -. (2018). Z-VIKOR method based on a new comprehensive weighted distance measure of Z-number and its application. IEEE Transactions on Fuzzy Systems, 26(6), 3232-3245. doi:10.1109/TFUZZ.2018.2816581 Shih, H. -., Shyur, H. -., & Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(7-8), 801-813. doi:10.1016/j.mcm.2006.03.023 Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods: A Comparative Study, Retrieved from www.scopus.com Triantaphyllou, E., Shu, B., Nieto Sanchez, S., & Ray, T. (1998). Multi-criteria decision making: An operations research approach. Encyclopedia of Electrical and Electronics Engineering, 15, 175-186. Retrieved from www.scopus.com Veltri, L., Kaakinen, J. R., Shillam, C., Arwood, E., & Bell, K. (2016). Controlled postpartum-newborn simulation with objective evaluation exchanged for clinical learning. Clinical Simulation in Nursing, 12(5), 177-186. doi:10.1016/j.ecns.2016.01.005 Walia, S., & Marks-Maran, D. (2014). Leadership development through action learning sets: An evaluation study. Nurse Education in Practice, 14(6), 612-619. doi:10.1016/j.nepr.2014.06.004 Wang, X., Wang, J., & Zhang, H. (2019). Distance-based multicriteria group decision-making approach with probabilistic linguistic term sets. Expert Systems, 36(2) doi:10.1111/exsy.12352 Yas, Q. M., Zadain, A. A., Zaidan, B. B., Lakulu, M. B., & Rahmatullah, B. (2017). Towards on develop a framework for the evaluation and benchmarking of skin detectors based on artificial intelligent models using multi-criteria decision-making techniques. International Journal of Pattern Recognition and Artificial Intelligence, 31(3) doi:10.1142/S0218001417590029 Yas, Q. M., Zaidan, A. A., Zaidan, B. B., Rahmatullah, B., & Abdul Karim, H. (2018). Comprehensive insights into evaluation and benchmarking of real-time skin detectors: Review, open issues & challenges, and recommended solutions. Measurement: Journal of the International Measurement Confederation, 114, 243-260. doi:10.1016/j.measurement.2017.09.027 Yildiz, Z., & Baba, A. F. (2014). Evaluation of student performance in laboratory applications using fuzzy decision support system model. Paper presented at the IEEE Global Engineering Education Conference, EDUCON, 1023-1027. doi:10.1109/EDUCON.2014.6826230 Retrieved from www.scopus.com Yoon, K. P., & Hwang, C. L. (1995). Multiple Attribute Decision Making: An Introduction, Retrieved from www.scopus.com Yousef, N. F., & Siti Nur Fazillah Mphd,Siti Nur Fazillah Mphd. (2013). Students performance in practical training: Academicians evaluation. Procedia-Social and Behavioral Sciences, 93, 1275-1280. Retrieved from www.scopus.com Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., Yas, Q. M., & Hashim, M. (2018). A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: Coherent taxonomy, open issues and recommendation pathway solution. Health and Technology, 8(4), 223-238. doi:10.1007/s12553-018-0223-9 Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390-404. doi:10.1016/j.jbi.2014.11.012 Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390-404. doi:10.1016/j.jbi.2014.11.012 Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390-404. doi:10.1016/j.jbi.2014.11.012 Zaidan, A. A., Zaidan, B. B., Hussain, M., Al-Haiqi, A. M., Mat Kiah, M. L., & Abdulnabi, M. (2015). Multi-criteria analysis for OS-EMR software selection problem: A comparative study. Decision Support Systems, 78, 15-27. doi:10.1016/j.dss.2015.07.002 Zaidan, A. A., Zaidan, B. B., Hussain, M., Al-Haiqi, A. M., Mat Kiah, M. L., & Abdulnabi, M. (2015). Multi-criteria analysis for OS-EMR software selection problem: A comparative study. Decision Support Systems, 78, 15-27. doi:10.1016/j.dss.2015.07.002 Zaidan, B. B., & Zaidan, A. A. (2018). Comparative study on the evaluation and benchmarking information hiding approaches based multi-measurement analysis using TOPSIS method with different normalisation, separation and context techniques. Measurement: Journal of the International Measurement Confederation, 117, 277-294. doi:10.1016/j.measurement.2017.12.019 Zaidan, B. B., & Zaidan, A. A. (2017). Software and hardware FPGA-based digital watermarking and steganography approaches: Toward new methodology for evaluation and benchmarking using multi-criteria decision-making techniques. Journal of Circuits, Systems and Computers, 26(7) doi:10.1142/S021812661750116X Zaidan, B. B., Zaidan, A. A., Abdul Karim, H., & Ahmad, N. N. (2017). A new approach based on multi-dimensional evaluation and benchmarking for data hiding techniques. International Journal of Information Technology and Decision Making, , 1-42. doi:10.1142/S0219622017500183 Zaidan, B. B., Zaidan, A. A., Karim, H. A., & Ahmad, N. N. (2017). A new digital watermarking evaluation and benchmarking methodology using an external group of evaluators and multi-criteria analysis based on ‘large-scale data’. Software - Practice and Experience, 47(10), 1365-1392. doi:10.1002/spe.2465 Zughoul, O., Momani, F., Almasri, O. H., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., . . . Hashim, M. (2018). Comprehensive insights into the criteria of student performance in various educational domains. IEEE Access, 6, 73245-73264. doi:10.1109/ACCESS.2018.2881282 |
| This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials. You may use the digitized material for private study, scholarship, or research. |