Assessment of Implementing Cloud-based Career and Educational Guidance System using Fuzzy Logic Modelling
Hosam F. El-Sofany
Hosam F. El-Sofany*, King Khalid University, Abha. Cairo Higher Institute for Engineering, Computer Science and Management, Cairo, Egypt, Kingdom of Saudi Arabia.
Manuscript received on February 01, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 77-84 | Volume-9 Issue-3, February, 2020. | Retrieval Number: B3961129219/2020©BEIESP | DOI: 10.35940/ijeat.B3961.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The career guidance process for graduates and students is affected by many factors; this, in turn, has motivated researchers to use a variety of scientific methodologies and techniques for proposing career guidance systems and solving related problems. The choice of right career not only positively affects the professional life of graduates, but also the academic life of students. As a result, the significance of developing career and educational guidance systems has increased. In this paper, the researcher discusses the effectiveness of using the proposed cloud-based career and educational guidance system to help students and graduates move to the professional world. The main objectives of the system include helping students choose their majors; helping graduates choose a career that is appropriate to their educational skills, practical experiences, and scientific ability; providing graduates and students with training courses required for specific careers. The proposed system is presented as a “Career-as-a-Service” cloud model. In this paper, the use of Fuzzy Logic for defining system inputs, processes, and outputs as a new representation for career and educational guidance system parameters is introduced. Cronbach’s alpha tests are used for measuring the validity and reliability of the study questionnaires’ content. In this study, several analysis methods such as Spearman correlation, stepwise multiple linear regression, skewness, mean, and standard deviation have been used to determine the effect and performance of the proposed system through dominating factors such as gender, age, class standing, enrolment status, specialization, and city.
Keywords: Career guidance, Educational guidance, Cloud computing, Fuzzy Logic.