A decision matrix for optimize the ability of software engineering students
This research aimed to propose a decision matrix based on multi-criteria analysis to aiddecision-makers in optimizing the ability of software engineering students. In thisstudy, an experiment was conducted on the basis of several stages. First, decision matrixwas constructed to rank the ability of s...
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| 主要作者: | |
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| 格式: | thesis |
| 語言: | eng |
| 出版: |
2019
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| 主題: | |
| 在線閱讀: | https://ir.upsi.edu.my/detailsg.php?det=6266 |
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| 總結: | This research aimed to propose a decision matrix based on multi-criteria analysis to aiddecision-makers in optimizing the ability of software engineering students. In thisstudy, an experiment was conducted on the basis of several stages. First, decision matrixwas constructed to rank the ability of software engineering students based on multimeasurementcriteria (Grade Point Average (GPA) and soft skills) and SoftwareDevelopment Life Cycle (SDLC) process levels as alternatives. Then, the constructeddecision matrix was adapted by distributing the courses of SDLC process levels basedon Software Engineering Body of Knowledge (SWEBOK) standard and expert opinionsusing Multi-Criteria Decision Making (MCDM) techniques based on AnalyticHierarchy Process (AHP) to weight the alternatives. Next, the ability of students wasranked based on the adapted decision matrix using the integrated AHP to weight themulti-measurement criteria, and Technique for Order Performance by Similarity toIdeal Solution (TOPSIS) was used to rank the alternatives. The data consisted of thegrades of courses and soft skills of 60 students of Universiti Pendidikan Sultan Idris(UPSI), who had graduated in 2016. The results of this study showed the integration ofAHP and TOPSIS was effective in ranking the ability of students based on their scoresof strengths, indicating that 14 (23%) of the students were requirements collectors, 13(22%) were designers, 5 (8%) were programmers, 13 (22%) were testers, and 15 (25%)were maintenance personnel. In conclusion, significant differences were observedbetween the groups scores for each level of SDLC, indicating that the ranking resultswere identical for all levels. The implication of this study is that lecturers gain thebenefits by identify the strengths and weaknesses of their students such that they canprovide better supervision. Likewise, benefits to students by determine their actualability, allowing them to take the necessary measures to improve their learningperformance. |
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