CAREER TECHNOLOGY HARARE INSTITUTE OF TECHNOLOGY ABSTRACT The

CAREER ADVISORY USING DISTRIBUTED NEURAL NETWORKS

Amose Suwali, Supervised by Mr. A.
Ndlovu.

Department of Computer Science

SCHOOL OF INFORMATION SCIENCES AND
TECHNOLOGY

HARARE INSTITUTE OF TECHNOLOGY

ABSTRACT

The project aims to develop an artificial intelligent web-based software
agent that learns to recommend career fields to students based on their
personality type, past academic performance, and interests. The project
attempts to address the problem of the lack of personalized career guidance
raising due to the shortage of human and time resources that the process
demands through a machine learning web-based expert system.

Furthermore, since the project is low budgeted it seeks to address the
lack of high powered computer system through the design of a horizontally
scalable solution architecture model that distributes computational work
proportionally to the nodes in hybrid network architecture (client-server and
peer to peer network).

                 
1.                       
INTRODUCTION

Career advice
is a necessity every student ought to receive at any academic level. Unless
this advice is personalized and tailored to one`s personal attributes this
advice proves ineffective. There is a rise in the lack of quality personalized
career guidance due to the shortage of human and time resources that the
process demands.

The project
aimed at developing a career advisory expert system that recommends career
fields to a student based on personalized career recommendation model. The
system implements machine learning techniques to develop a progressively
improving model that learns to recommend a career field for a student.

However,
implementing such a system requires high computational resources and introduces
another limitation to the success of this low-budgeted project. Thus, the
project aims to design a system architecture that distributes computational
work of the above-proposed system. 

                 
2.                       
GOALS AND OBJECTIVES

 

This survey paper is compiled based
on a research project aimed at developing a career advisory expert system with the
below listed goals and objectives. A career advisory solution that

 

?

Highly values and considers the user`s interest and
passions.

?

Provides personalised career advice tailored to the
user`s academic strengths and abilities.

?

Continuously improves/learns to provide relevant
advice based on user`s feedback

?

Utilizes leverageable processing power available at
the client nodes of the used RESTful client-server architecture.

 

RELATED WORK

Research work was perform based on existing solutions
in two domains highlighted in the goals and objectives. These are

       
i.           
Career Guidance Models.

      ii.           
Processing load distribution in client-server architectures.

 

                 
3.                       
CAREER GUIDANCE MODELS.

·        
Automated
Career Counselling System for Students using CBR and J48

This research
intends to solve the career assortment problems by making use of the CBR
(Case-Based Reasoning) and Decision Tree J 48 algorithm. The system establishes
an automated process similar to a one-to-one meeting with a career counsellor
and aids to ‘plan’ a career true to the student’s grade, IQ, hobbies and,
predominantly, gender. Students can later determine a career from the proposed
options and the illustration of related jobs. The system’s distinction is to
nominate Universities offering education for the recommended careers. 1

·        
iAdvice
is a Career Advisory expert system designed by Chathra Hendahewa et al.to guide
students for faculty of B.Sc. IT students of Moratuwa University, engaged in
their higher education to determine their career paths and to select their
course subjects to be in-line with their career goals. 16. The System
consists of three components viz; knowledge base, Inference Engine, and user
interface. This expert system uses features such as reasoning ability,
providing explanations, alternative solutions, uncertainty and probability
measures, questioning ability and also forward chaining, backward chaining and
rule-based inference in designing expert system. This system was divided into
two main subsystems i.e. Career known subsystem and Career unknown subsystem.
The first subsystem provides advice to students who have a specific career goal
and the second subsystem provides advice to students who are unclear about
career objectives. Past examination performance, student preferences, and
skills, industry alignment with subjects, are the main factors considered by a
human expert in providing career guidance. 3

·        
CPSRS

Career Path
Selection Recommendation System (CPSRS) was proposed and developed by Razak,
Hashim, Noor, Hazwam, & Halim. This system was developed using the fuzzy
logic technique. CPSRS was designed for providing direction and guidance to
final year students for faculty of computer and mathematical science, University
Teknologi MARA (UiTM) students of Malaysia for choosing a suitable career.
Factors considered for career selection are student’s strengths, skills, and
personality, interest, past academic records. The use of fuzzy logic approach
helps students by giving career recommendation based on career test. They used
Fuzzy Associate Memory (FAM) as fuzzy inference because FAM will contain the
knowledge from an expert that is believed to be able to reach nearly any sort
of control objectives. The operator MIN and intersection AND is used as an
inference rule. 4

CGM- (Career
Guidance Model)

Winston &
Lawrence developed expert system model (CGM) for African high school students.
The survey was carried out to estimate the level of professional satisfaction
with the task and nature of their career and also determined what career
practices are carried out in Kenyan high school. It was found that
approximately 90% of public high school students in Kenya were not getting
reasonable career guidance due to limited resources and time. The proposed
model consists of three sections, personality analysis, decision making
regarding selecting specific job category (simulation of activity), and
Scholastic Aptitude Testing (SAT) for evaluating one’s cognitive ability.
Personality analysis model created knowledge and rules based on Myers-Briggs
Typology Indicator (MBTI). The proposed system was designed using visual basic
and Access. 4

·        
CMS
(Career Master System):

Balogun,
Thompson specifies the development of career master DSS that  counsellors can use to help students in identifying
the right discipline for secondary school leaving students of Nigeria who have
problems with their choice of careers as they intend to study at tertiary
institutions of their choice. This career master system implemented using
Visual Basic. This system is designed for desktop and counselors, and system
recommendation was based on parameters such as ability, skills, Intelligent
Quotient, interest, parents and friends influence, preferences, parent
occupation and hobbies, past academic performance. For the development of this
career master system author considers four databases subject, study, pass, and
course. Author checked this DSS system with career counselors result, it found
that developed system recommendations are correlated with counsellor’s
recommendations. The system provides the desktop for the counsellors to enhance
the duty of choosing the best and most appropriate discipline for clients.
(Balogun, Thompson, & State, 2009) 5

·        
Rule-Based
DSS:

Muhammad
Zaheer Aslam, et al. presents the design and development of a proposed rule
based Decision Support System that helps students in selecting the best
suitable faculty/major decision while taking admission in Gomal University.
They designed a model using visual basic for testing and measuring the
student’s capabilities like intelligence, understanding, comprehension,
mathematical concepts his/her past academic record, intelligence level. They
divided tests into two parts one for testing capabilities and abilities and
another for testing intelligence. Capability and ability test consists of 100
questions i.e. 20 questions each for English, Mathematics, Physics, Chemistry,
Computer Science / Biology and intelligence test consisting of 50 questions.
They applied model resulting into a rule-based decision support system to
determine the compatibility of the available faculties/majors in Gomal
University. These DSS identify the most suitable faculty or major for the
student based on his abilities and capabilities extracted from the test module
results. They used CLIPS language to store knowledge base. Rules can be made
more customized and more criteria may be added to it for more data mined
results. It can be extended to include other universities faculties and majors
to be able to serve more students wishing to be enrolled in other universities
and make the criterion customized for that university. 7.

·        
Design
of an online expert system for career guidance

The system
will have the knowledge-base which contains the details about the colleges in
Pondicherry. This information is acquired from web pages using pattern matching
and jSoup parsing technique and the knowledge-base is constructed automatically
without manual efforts. Rules are framed and an inference engine is developed
which makes the Expert System. The constructed knowledge-base can be queried
with domain related queries and the Expert System provides the most relevant
details for the query. 8

 

4          LOAD DISTRIBUTION TECHNIQUES IN CLIENT-SERVER ARCHITECTURES

·        
Automated
Career Counselling System for Students using CBR and J48

This research
intends to solve the career assortment problems by making use of the CBR
(Case-Based Reasoning) and Decision Tree J 48 algorithm. The system establishes
an automated process similar to a one-to-one meeting with a career counsellor
and aids to ‘plan’ a career true to the student’s grade, IQ, hobbies and,
predominantly, gender. Students can later determine a career from the proposed
options and the illustration of related jobs. The system’s distinction is to
nominate Universities offering education for the recommended careers. 1

 

·        
iAdvice
is a Career Advisory expert system designed by Chathra Hendahewa et al.to guide
students for faculty of B.Sc. IT students of Moratuwa University, engaged in
their higher education to determine their career paths and to select their
course subjects to be in-line with their career goals. 16.

CONCLUSIONS

       
i.           
Career Guidance Models.

Based on the
related work research conducted currently the leading career guidance solutions
are based on the below-listed recommendation models

·        
Logic
Driven

·        
Rule-Based

·        
Fuzzy
Logic

·        
Knowledge
Base

·        
Case-Based
Reasoning & Decision Tree J48

• These
models above are implemented without the ability to improve or learn their
recommendation throughput over time.

• The
above-mentioned models have an input domain of 37 parameters which include a
student`s examination marks, parent’s occupation, cost of tuition fees, home
location, students attitude etc.

The
combination of the parameters input into those models does not map to a career
recommendation that is tailored to a student`s personal strength, skills and
interests.

• The
existing models do not consider the non-linear relationship between the input
parameters themselves but instead, they attempt to linearize them, for example:

A student`s
academic performance trend is not linearly related to his or her personality
type, thus a linear if-then-else function cannot phantom the pattern that maps
the two parameters but rather attempts to transform this non-linear
relationship into one which only has two possible states (True or False).

     
ii.           
Load distribution techniques in client-server architectures

A student`s academic performance
trend is not linearly related to his or her personality type, thus a linear
if-then-else function cannot phantom the pattern that maps the two parameters
but rather attempts to transform this non-linear relationship into one which
only has two possible states (True or False).

Database

Trained

Execute Trained

JS Model Stub

Server

Side

Client

Side

JavaScript

Web Workers

Web Browser

Logic
Engine

 

 

 

REFERENCES

1. Maha
Nawaz, Anum Adnan, Unsa Tariq, Jannat Fatima Salman, Rabia Asjad, and Maria
Tamoor, Department of Computer Sciences Kinnaird College for Women Lahore,
Pakistan, “Automated Career Counseling System for Students using CBR and J48”

2. C.
Hendahewa, M. Dissanayake, S. Samaraweera, A. Ruwanpathirana, and A. S.
Karunananda, “Artificial Intelligence Approach to Effective Career Guidance,”
no. September, pp. 32–42, 2006.

3. T. R.
Razak, M. A. Hashim, N. M. Noor, I. Hazwam, and A. Halim, “Career Path
Recommendation System for UiTM Perlis Students Using Fuzzy Logic,” 2014.

4. O.
Winston and M. Lawrence, “Career Guidance Using Expert System Approach,” pp.
123–131, 2000.

5. V. F.
Balogun, A. F. Thompson, and O. State, “Career Master: A Decision Support
System ( DSS ) for Guidance and Counseling in,” vol. 10, no. 2, pp. 337–354,
2009.

6. M. Z.
Aslam and A. R. Khan, “A Proposed Decision Support System / Expert System for
Guiding Fresh Students in Selecting a Faculty in Gomal University,” Ind. Eng.
Lett., vol. 1, no. 4, pp. 33–41, 2011.

7. S.
Saraswathi, M. Hemanth Kumar Reddy, S. Udaya Kumar, M. Suraj, Sk. Khaja Shafi,
Information Technology, Pondicherry Engineering College, Pondicherry, India,
“Design Of An Online Expert System For Career Guidance”

8. K.
Addison, T. Antwi, and F. Amissah, “Factors that influence junior high school
students’ choice of programmes for senior high school and its implication for
their career choice in Ghana.,” J. Educ. Curric. Dev. Res., vol. 2, no.
September, pp. 1–14, 2014.

9. OSORO,
B. ET AL. 2000. Career decision-making of high school students in Kenya. An
International Journal for the Advancement of Counseling

10. K. I.
N. N. A. O. ISSA, “Factors Affecting the Career Choice of Undergraduates in
Nigerian Library and Information Science Schools,” Nigeria, 2008.

11. Ojenge
Winston and Muchemi Lawrence, “Career Guidance Using Expert System Approach”..

AUTHOR BIOGRAPHY

ANU MARIA is an assistant professor in the
department of Systems Science & Industrial Engineering at the State
University of New York at Binghamton. She received her PhD in Industrial Engineering from the University of Oklahoma. Her
research interests include optimizing the performance of materials used in
electronic packaging (including solder paste, conductive adhesives, and
underfills), simulation optimization techniques, genetics based algorithms for
optimization of problems with a large number of continuous variables, multi
criteria optimization, simulation, and interior-point methods.

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