A fuzzy based conceptual framework for career counselling

In the education system, student find many counselors who will guide them for a particular career path but generally no one guides the student after entering into the particular career stream. This project is a system which is based on the analysis and suggestions. This is helpful for the students for analyzing their career and choosing the right future path. Results and suggestions or even the career preferences will be provided based on the input which is provided by the student. It will be so adaptive that administrator can handle the database even without knowing the details of the database. The system will contain the whole area of the course in conjunction with the guidelines and necessary crucial information. This project aims to explore an objective and effective mean of analyzing student. The system consists of the basic automated career counseling, guidelines, decision making and so on. The system can obtain the relevant information automatically from students then propose some solutions and recommendations. The analysis starts from when the student gives a thought about taking admission into engineering. Student evaluation plays an important part in university custom relationship management. The system is supposed to guide the candidate regarding his/her academics.

British Journal of Education, Society & Behavioural Science, 2015

The concept of Multiple Intelligences has come out after Howard Gardner redefined intelligence. According to Gardner's theory, human beings have different types of intelligence and based on their respective intelligence types, human beings have different skills in different areas. Human beings can be more successful and productive on areas they are skillful. Therefore, choosing appropriate professions, in accordance with one's intelligence type, is important for individuals as well as for the society. This study aims to develop a technique to help high school students in the profession selection process using artificial intelligence. Questionnaire has been utilized as the research method and the data have been analyzed via Fuzzy Logic Toolbox which is subunit of the software called MATLAB. It was aimed to direct students to appropriate profession and build more successful and productive professions.

2006

With the vast opportunities available for IT education, career guidance has become a crucial theme for deciding the appropriate career path of students. The lack of such expert career guidance systems in this domain inspired us to come up with the initial idea. This paper reports on a Career Advisory Expert System, named iAdvice to guide students engaged in their higher education to determine their career paths and to select their course subjects to be inline with their career goals. Expert System features such as reasoning ability, providing explanations providing alternative solutions, providing uncertainty and probability measures, questioning ability are found in iAdvice. The design of Career Advisory Expert System takes into consideration factors such as past examination performance, student preferences and skills, industry alignment with subjects, which are the main factors also considered by a human expert in providing career guidance. According to the evaluation carried out it was found out that the model has a capability of about 70% accuracy in predicting the performance, about 85% relevance of the advice provided, the self-explanatory nature of the system and about 87% provision of informative and useful advice.

2021

Since the future of the society depends upon the role of students and their services construct the prosperous and advanced society, so suitable career selection for the students' is considered to be an important problem to explore. As per psychology, if a student has the required capability, and positive attitudes towards a subject in terms of interest, attitude, memory, knowledge, environment, and career, then the student will achieve more in that subject. To consider this kind of uncertain issues, picture fuzzy set and rough set are found to be appropriate due to their inherent characteristics to deal with incomplete and imprecise information. In this study, picture fuzzy set and rough set-based approaches are proposed to help the student to choose an appropriate subject and consequently provide a good service or contribution to the society particularly in that domain. The main purpose of the article is to analyse student's features in terms of career, memory, interest, kn...

2021

This study identifies the priority employability skills of vocational education students using Fuzzy AHP. The purpose of this study is to find out the uniformity of employability skills attributes globally, identify which attributes are the most priority needed by vocational graduates based on the perspective of vocational teachers and to know the perspective of vocational teachers regarding the importance of employability skills attributes for vocational graduates. This study involved 378 SMK teachers in Indonesia as respondents. Content analysis techniques are used to determine a set of attributes that are used in several frameworks and the MCDM based Fuzzy AHP method is used to help determine priorities and decision makers. The results show that communication skills, collaboration skills, problem solving skills, self-management skills, planning and organizing skills, the ability to use technology and lifelong learning skills are attributes of employability skills that are widely ...

International Journal of Engineering Trends and Technology, 2022

The point of this exploration work exhibits a classification technique for analyzing engineering student's employment opportunities. From the given 60 attributes, take 46 attributes as inputs. In view of this input data, we design the fuzzy logic system. This design is utilized for finding the employment opportunity potential score of particular individuals. Based on these 46 attributes, generate the rule as low and high. At that point, we need to take the count of low and high; after analyzing the count, find the output level (low, medium, high). In the outcome, three diverse membership functions such as trapezoidal, Gaussian and triangle have been designed. In this three-membership function, we explore diverse designing and validation points (50-50, 60-40, 70-30 and 80-20). The sensitivity value for the triangle is 76%, the specificity value for the triangle is 93%, and the accuracy value for a triangle is 89%. From this, the triangle membership function is enhanced contrasted with other membership functions.

In this research, a quantitative model to measure the "career readiness" performance level of the current curriculum of the Industrial Technology and Packaging program at California Polytechnic State University is proposed. Career readiness is first defined through performance attributes and these attributes are further classified into specific categories and metrics. Using a fuzzy logic computational approach, "career readiness" measures are developed and a "career readiness" score referred to as (CRS) is calculated. The model is designed to be flexible, dynamic and easy to use. It should enable a systematic measurement of career readiness by producing a final integrated unit-less score. Results from the data collected for the Industrial Technology program's main employers and graduates provided various insights about the level of career readiness the program currently provides in terms of strengths and weaknesses. In addition, these results, and the developed CRS approach, may serve as a practical tool for decision-making and improvement to various educational components to increase readiness level. Finally, the overall CRS, as well as its constituting scores, can be used to monitor progress along such improvements programs.

The lack of quality career guidance in African high schools, caused by shortage of human and time resources that the process demands, has led to the choice of unsuitable careers resulting in widespread poor performance at the workplace. The focus of this paper is the use of Expert Systems that store the highly specialized knowledge of career counseling and dispenses it to the needy youth in a cheap and quick process. Initial results of the evaluation of the model, has shown a career diagnosis accuracy of 71%. 124 Information Systems 124 Information Systems

International Journal of Advanced Computer Science and Applications

This research is a documentary research aimed at designing the architecture of the intelligent career prediction system based on the cognitive technology for producing graduates to the digital manpower. The research methods were divided into three phases: Phase 1, Composition Synthesis of Intelligent Career Prediction System. Phase 2, Intelligent Career Prediction System Architecture Designing based on the Cognitive Technology for producing graduates to the digital manpower. Phase 3, an assessment of the suitability of the architecture of the intelligent career prediction system based on the cognitive technology for producing graduates to the digital manpower. The architecture of the intelligent career prediction system by using the cognitive technology can be divided into three parts: 1) People involved in the architecture of the intelligent career prediction system consisting of five groups of related persons: students, staff, teachers, digital Enterprises, system administrator. 2) The architecture of the intelligent career prediction system consisting of four components: 1) User management, 2. Prediction Data Management, 3) Prediction Management system, 4) Prediction Display system, and cloud computing, an assessment of the suitability the architecture of the intelligent career prediction system based on the cognitive technology for producing graduates to the digital manpower by nine experts in the intelligent career prediction system and cognitive technology. The statistics used in the research are Mean and standard deviation. The evaluation results showed that the developed architecture was the most suitable, with the combined mean of 4.54, and the standard deviation was 0.49.