Proposed model for predictive mapping of graduate’s skills to industry Roles using machine learnining techniques
Date
2016Author
Muchemi, Lawrence
Omwenga, Isanda E
Mwakondo, Fullgence M
Type
ArticleLanguage
enMetadata
Show full item recordAbstract
he main focus in training evaluation is not only to determine whether training objectives were achieved but
also how to improve evaluation so as to enhance both employability of graduates and performance in the job.
This is in response to challe
nges facing not only graduates in choosing industry jobs that befit their skills, but
also employers in selecting graduates whose skills match to their needs.
Problem solving is one of the skills
acquired during training by graduates and
strongly
sought
fo
r
by employers
during evaluation
to promote
performance in the job. This paper presents a model for evaluating graduates’
by mapping
their problem
solving skills
to
industry jobs
’ competence requirements
and the potential of using machine learning techniqu
es
to train the model in predicting suitable industry jobs for new graduates from college
. The paper outlines
challenges
facing both graduates and industry in selecting industry jobs and skilled graduates respectively,
highlight
s
trends
,
methods
, and gaps
in skill
evaluation and prediction.
A brief discussion
is
made
of key
strategies
in skill evaluation and prediction
that need to be undertaken
and
evaluation theories behind the key
variables of the proposed model.
Citation
Mwakondo, Fullgence Mwachoo, Lawrence Muchemi, and E. I. Omwenga. "Proposed Model for Predictive Mapping of Graduate’s Skills to Industry Roles Using Machine Learning Techniques." The International Journal Of Engineering And Science (IJES) Vol 5 (2016).Publisher
University of Nairobi
Rights
Attribution-NonCommercial-NoDerivs 3.0 United StatesUsage Rights
http://creativecommons.org/licenses/by-nc-nd/3.0/us/Collections
The following license files are associated with this item: